Search results for "Recurrent Neural Network"
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The Book to Start You on Machine Learning">
This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.
The Book to Start You on Machine Learning
https://www.kdnuggets.com/2020/01/book-start-machine-learning.html
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A Comprehensive Guide to Natural Language Generation
Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.https://www.kdnuggets.com/2020/01/guide-natural-language-generation.html
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Automatic Text Summarization in a Nutshell
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about Automatic Text Summarization and the various ways it is used.https://www.kdnuggets.com/2019/12/automatic-text-summarization-nutshell.html
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The 4 Hottest Trends in Data Science for 2020">
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
The 4 Hottest Trends in Data Science for 2020
https://www.kdnuggets.com/2019/12/4-hottest-trends-data-science-2020.html
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10 Free Top Notch Machine Learning Courses">
Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.
10 Free Top Notch Machine Learning Courses
https://www.kdnuggets.com/2019/12/10-free-top-notch-courses-machine-learning.html
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The Rise of User-Generated Data Labeling
Let’s say your project is humongous and needs data labeling to be done continuously - while you’re on-the-go, sleeping, or eating. I’m sure you’d appreciate User-generated Data Labeling. I’ve got 6 interesting examples to help you understand this, let’s dive right in!https://www.kdnuggets.com/2019/12/rise-user-generated-data-labeling.html
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Data Science Curriculum Roadmap">
What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.
Data Science Curriculum Roadmap
https://www.kdnuggets.com/2019/12/data-science-curriculum-roadmap.html
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Text Encoding: A Review
We will focus here exactly on that part of the analysis that transforms words into numbers and texts into number vectors: text encoding.https://www.kdnuggets.com/2019/11/text-encoding-review.html
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Research Guide for Transformers
The problem with RNNs and CNNs is that they aren’t able to keep up with context and content when sentences are too long. This limitation has been solved by paying attention to the word that is currently being operated on. This guide will focus on how this problem can be addressed by Transformers with the help of deep learning.https://www.kdnuggets.com/2019/10/research-guide-transformers.html
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Anomaly Detection, A Key Task for AI and Machine Learning, Explained
One way to process data faster and more efficiently is to detect abnormal events, changes or shifts in datasets. Anomaly detection refers to identification of items or events that do not conform to an expected pattern or to other items in a dataset that are usually undetectable by a human expert.https://www.kdnuggets.com/2019/10/anomaly-detection-explained.html
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10 Free Top Notch Natural Language Processing Courses">
Are you looking to learn natural language processing? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to learning NLP and its varied topics.
10 Free Top Notch Natural Language Processing Courses
https://www.kdnuggets.com/2019/10/10-free-top-notch-courses-natural-language-processing.html
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Multi-Task Learning – ERNIE 2.0: State-of-the-Art NLP Architecture Intuitively Explained
The tech giant Baidu unveiled its state-of-the-art NLP architecture ERNIE 2.0 earlier this year, which scored significantly higher than XLNet and BERT on all tasks in the GLUE benchmark. This major breakthrough in NLP takes advantage of a new innovation called “Continual Incremental Multi-Task Learning”.https://www.kdnuggets.com/2019/10/multi-task-learning-ernie-sota-nlp-architecture.html
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How AI will transform healthcare (and can it fix the US healthcare system?)">
This thorough review focuses on the impact of AI, 5G, and edge computing on the healthcare sector in the 2020s as well as a look at quantum computing's potential impact on AI, healthcare, and financial services.
How AI will transform healthcare (and can it fix the US healthcare system?)
https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html
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A 2019 Guide for Automatic Speech Recognition
In this article, we’ll look at a couple of papers aimed at solving the problem of automated speech recognition with machine and deep learning.https://www.kdnuggets.com/2019/09/2019-guide-automatic-speech-recognition.html
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A 2019 Guide to Speech Synthesis with Deep Learning
In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.https://www.kdnuggets.com/2019/09/2019-guide-speech-synthesis-deep-learning.html
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TensorFlow vs PyTorch vs Keras for NLP">
These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.
TensorFlow vs PyTorch vs Keras for NLP
https://www.kdnuggets.com/2019/09/tensorflow-pytorch-keras-nlp.html
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TensorFlow 2.0: Dynamic, Readable, and Highly Extended
With substantial changes coming with TensorFlow 2.0, and the release candidate version now available, learn more in this guide about the major updates and how to get started on the machine learning platform.https://www.kdnuggets.com/2019/08/tensorflow-20.html
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As a data scientist, you are in high demand. So, how can you increase your marketability even more? Check out these current trends in skills most desired by employers in 2019.
How to Become More Marketable as a Data Scientist">
How to Become More Marketable as a Data Scientist
https://www.kdnuggets.com/2019/08/marketable-data-scientist.html
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A Gentle Guide to Starting Your NLP Project with AllenNLP
For those who aren’t familiar with AllenNLP, I will give a brief overview of the library and let you know the advantages of integrating it to your project.https://www.kdnuggets.com/2019/07/gentle-guide-starting-nlp-project-allennlp.html
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How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls">
We outline some of the common pitfalls of machine learning for time series forecasting, with a look at time delayed predictions, autocorrelations, stationarity, accuracy metrics, and more.
How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls
https://www.kdnuggets.com/2019/05/machine-learning-time-series-forecasting.html
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Top Data Science and Machine Learning Methods Used in 2018, 2019">
Once again, the most used methods are Regression, Clustering, Visualization, Decision Trees/Rules, and Random Forests. The greatest relative increases this year are overwhelmingly Deep Learning techniques, while SVD, SVMs and Association Rules show the greatest decline.
Top Data Science and Machine Learning Methods Used in 2018, 2019
https://www.kdnuggets.com/2019/04/top-data-science-machine-learning-methods-2018-2019.html
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An introduction to explainable AI, and why we need it
We introduce explainable AI, why it is needed, and present the Reversed Time Attention Model, Local Interpretable Model-Agnostic Explanation and Layer-wise Relevance Propagation.https://www.kdnuggets.com/2019/04/introduction-explainable-ai.html
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Spatio-Temporal Statistics: A Primer
Marketing scientist Kevin Gray asks University of Missouri Professor Chris Wikle about Spatio-Temporal Statistics and how it can be used in science and business.https://www.kdnuggets.com/2019/04/spatio-temporal-statistics-primer.html
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Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.
Another 10 Free Must-See Courses for Machine Learning and Data Science">
Another 10 Free Must-See Courses for Machine Learning and Data Science
https://www.kdnuggets.com/2019/04/another-10-free-must-see-courses-machine-learning-data-science.html
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Getting started with NLP using the PyTorch framework
We discuss the classes that PyTorch provides for helping with Natural Language Processing (NLP) and how they can be used for related tasks using recurrent layers.https://www.kdnuggets.com/2019/04/nlp-pytorch.html
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My favorite mind-blowing Machine Learning/AI breakthroughs">
We present some of our favorite breakthroughs in Machine Learning and AI in recent times, complete with papers, video links and brief summaries for each.
My favorite mind-blowing Machine Learning/AI breakthroughs
https://www.kdnuggets.com/2019/03/favorite-ml-ai-breakthroughs.html
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Deconstructing BERT, Part 2: Visualizing the Inner Workings of Attention
In this post, the author shows how BERT can mimic a Bag-of-Words model. The visualization tool from Part 1 is extended to probe deeper into the mind of BERT, to expose the neurons that give BERT its shape-shifting superpowers.https://www.kdnuggets.com/2019/03/deconstructing-bert-part-2-visualizing-inner-workings-attention.html
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Trending Deep Learning Github Repositories
Check these pair of resources for trending and top GitHub deep learning repositories for some new ideas on what to be looking out for.https://www.kdnuggets.com/2019/02/trending-top-deep-learning-github-repositories.html
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Top 10 Books on NLP and Text Analysis">
When it comes to choosing the right book, you become immediately overwhelmed with the abundance of possibilities. In this review, we have collected our Top 10 NLP and Text Analysis Books of all time, ranging from beginners to experts.
Top 10 Books on NLP and Text Analysis
https://www.kdnuggets.com/2019/01/top-10-books-nlp-text-analysis.html
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NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing">
Trying to keep up with advancements at the overlap of neural networks and natural language processing can be troublesome. That's where the today's spotlighted resource comes in.
NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing
https://www.kdnuggets.com/2019/01/nlp-overview-modern-deep-learning-techniques.html
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Deep Learning for the Masses (… and The Semantic Layer)
Deep learning is everywhere right now, in your watch, in your television, your phone, and in someway the platform you are using to read this article. Here I’ll talk about how can you start changing your business using Deep Learning in a very simple way. But first, you need to know about the Semantic Layer.https://www.kdnuggets.com/2018/11/deep-learning-masses-semantic-layer.html
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Deep Learning Cheat Sheets">
Check out this collection of high-quality deep learning cheat sheets, filled with valuable, concise information on a variety of neural network-related topics.
Deep Learning Cheat Sheets
https://www.kdnuggets.com/2018/11/deep-learning-cheat-sheets.html
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An Introduction to AI">
We provide an introduction to AI key terminologies and methodologies, covering both Machine Learning and Deep Learning, with an extensive list including Narrow AI, Super Intelligence, Classic Artificial Intelligence, and more.
An Introduction to AI
https://www.kdnuggets.com/2018/11/an-introduction-ai.html
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Introduction to PyTorch for Deep Learning
In this tutorial, you’ll get an introduction to deep learning using the PyTorch framework, and by its conclusion, you’ll be comfortable applying it to your deep learning models.https://www.kdnuggets.com/2018/11/introduction-pytorch-deep-learning.html
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Introduction to Deep Learning with Keras
In this article, we’ll build a simple neural network using Keras. Now let’s proceed to solve a real business problem: an insurance company wants you to develop a model to help them predict which claims look fraudulent.https://www.kdnuggets.com/2018/10/introduction-deep-learning-keras.html
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The Main Approaches to Natural Language Processing Tasks">
Let's have a look at the main approaches to NLP tasks that we have at our disposal. We will then have a look at the concrete NLP tasks we can tackle with said approaches.
The Main Approaches to Natural Language Processing Tasks
https://www.kdnuggets.com/2018/10/main-approaches-natural-language-processing-tasks.html
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Introduction to Deep Learning
I decided to begin to put some structure in my understanding of Neural Networks through this series of articles.https://www.kdnuggets.com/2018/09/introduction-deep-learning.html
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Deep Learning for NLP: An Overview of Recent Trends">
A new paper discusses some of the recent trends in deep learning based natural language processing (NLP) systems and applications. The focus is on the review and comparison of models and methods that have achieved state-of-the-art (SOTA) results on various NLP tasks and some of the current best practices for applying deep learning in NLP.
Deep Learning for NLP: An Overview of Recent Trends
https://www.kdnuggets.com/2018/09/deep-learning-nlp-overview-recent-trends.html
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fast.ai Deep Learning Part 1 Complete Course Notes
This posts is a collection of a set of fantastic notes on the fast.ai deep learning part 1 MOOC freely available online, as written and shared by a student. These notes are a valuable learning resource either as a supplement to the courseware or on their own.https://www.kdnuggets.com/2018/07/fast-ai-deep-learning-part-1-notes.html
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Overview and benchmark of traditional and deep learning models in text classification
In this post, traditional and deep learning models in text classification will be thoroughly investigated, including a discussion into both Recurrent and Convolutional neural networks.https://www.kdnuggets.com/2018/07/overview-benchmark-deep-learning-models-text-classification.html
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Deep Quantile Regression
Most Deep Learning frameworks currently focus on giving a best estimate as defined by a loss function. Occasionally something beyond a point estimate is required to make a decision. This is where a distribution would be useful. This article will purely focus on inferring quantiles.https://www.kdnuggets.com/2018/07/deep-quantile-regression.html
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Taming LSTMs: Variable-sized mini-batches and why PyTorch is good for your health
After reading this, you’ll be back to fantasies of you + PyTorch eloping into the sunset while your Recurrent Networks achieve new accuracies you’ve only read about on Arxiv.https://www.kdnuggets.com/2018/06/taming-lstms-variable-sized-mini-batches-pytorch.html
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The Keras 4 Step Workflow">
In his book "Deep Learning with Python," Francois Chollet outlines a process for developing neural networks with Keras in 4 steps. Let's take a look at this process with a simple example.
The Keras 4 Step Workflow
https://www.kdnuggets.com/2018/06/keras-4-step-workflow.html
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Top 16 Open Source Deep Learning Libraries and Platforms
We bring to you the top 16 open source deep learning libraries and platforms. TensorFlow is out in front as the undisputed number one, with Keras and Caffe completing the top three.https://www.kdnuggets.com/2018/04/top-16-open-source-deep-learning-libraries.html
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Ten Machine Learning Algorithms You Should Know to Become a Data Scientist">
It's important for data scientists to have a broad range of knowledge, keeping themselves updated with the latest trends. With that being said, we take a look at the top 10 machine learning algorithms every data scientist should know.
Ten Machine Learning Algorithms You Should Know to Become a Data Scientist
https://www.kdnuggets.com/2018/04/10-machine-learning-algorithms-data-scientist.html
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Machine Learning for Text
This book covers machine learning techniques from text using both bag-of-words and sequence-centric methods. The scope of coverage is vast, and it includes traditional information retrieval methods and also recent methods from neural networks and deep learning.https://www.kdnuggets.com/2018/04/machine-learning-text.html
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Top 20 Deep Learning Papers, 2018 Edition">
Deep Learning is constantly evolving at a fast pace. New techniques, tools and implementations are changing the field of Machine Learning and bringing excellent results.
Top 20 Deep Learning Papers, 2018 Edition
https://www.kdnuggets.com/2018/03/top-20-deep-learning-papers-2018.html
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A “Weird” Introduction to Deep Learning">
There are amazing introductions, courses and blog posts on Deep Learning. But this is a different kind of introduction.
A “Weird” Introduction to Deep Learning
https://www.kdnuggets.com/2018/03/weird-introduction-deep-learning.html
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How StockTwits Applies Social and Sentiment Data Science
StockTwits is a social network for investors and traders, giving them a platform to share assertions and perceptions, analyses and predictions.https://www.kdnuggets.com/2018/03/stocktwits-social-sentiment-data-science.html
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Great Data Scientists Don’t Just Think Outside the Box, They Redefine the Box
The best data scientists have strong imaginative skills for not just “thinking outside the box” – but actually redefining the box – in trying to find variables and metrics that might be better predictors of performance.https://www.kdnuggets.com/2018/03/great-data-scientists-think-outside-redefine-box.html
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Top 20 Python AI and Machine Learning Open Source Projects">
We update the top AI and Machine Learning projects in Python. Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.
Top 20 Python AI and Machine Learning Open Source Projects
https://www.kdnuggets.com/2018/02/top-20-python-ai-machine-learning-open-source-projects.html
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5 Things You Need To Know About Data Science
Here are 5 useful things to know about Data Science, including its relationship to BI, Data Mining, Predictive Analytics, and Machine Learning; Data Scientist job prospects; where to learn Data Science; and which algorithms/methods are used by Data Scientistshttps://www.kdnuggets.com/2018/02/5-things-about-data-science.html
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Resurgence of AI During 1983-2010
We discuss supervised learning, unsupervised learning and reinforcement learning, neural networks, and 6 reasons that helped AI Research and Development to move ahead.https://www.kdnuggets.com/2018/02/resurgence-ai-1983-2010.html
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The Birth of AI and The First AI Hype Cycle
A dazzling review of AI History, from Alan Turing and Turing Test, to Simon and Newell and Logic Theorist, to Marvin Minsky and Perceptron, birth of Rule-based systems and Machine Learning, Eliza - first chatbot, Robotics, and the bust which led to first AI Winter.https://www.kdnuggets.com/2018/02/birth-ai-first-hype-cycle.html
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Managing Machine Learning Workflows with Scikit-learn Pipelines Part 3: Multiple Models, Pipelines, and Grid Searches
In this post, we will be using grid search to optimize models built from a number of different types estimators, which we will then compare and properly evaluate the best hyperparameters that each model has to offer.https://www.kdnuggets.com/2018/01/managing-machine-learning-workflows-scikit-learn-pipelines-part-3.html
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Deep Learning in H2O using R
This article is about implementing Deep Learning (DL) using the H2O package in R. We start with a background on DL, followed by some features of H2O's DL framework, followed by an implementation using R.https://www.kdnuggets.com/2018/01/deep-learning-h2o-using-r.html
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A Day in the Life of an AI Developer">
This is the narrative of a typical AI Sunday, where I decided to look at building a sequence to sequence (seq2seq) model based chatbot using some already available sample code and data from the Cornell movie database.
A Day in the Life of an AI Developer
https://www.kdnuggets.com/2018/01/day-life-ai-developer.html
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Custom Optimizer in TensorFlow
How to customize the optimizers to speed-up and improve the process of finding a (local) minimum of the loss function using TensorFlow.https://www.kdnuggets.com/2018/01/custom-optimizer-tensorflow.html
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A Guide for Customer Retention Analysis with SQL
Customer retention curves are essential to any business looking to understand its clients, and will go a long way towards explaining other things like sales figures or the impact of marketing initiatives. They are an easy way to visualize a key interaction between customers and the business.https://www.kdnuggets.com/2017/12/guide-customer-retention-analysis-sql.html
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The 10 Deep Learning Methods AI Practitioners Need to Apply
Deep learning emerged from that decade’s explosive computational growth as a serious contender in the field, winning many important machine learning competitions. The interest has not cooled as of 2017; today, we see deep learning mentioned in every corner of machine learning.https://www.kdnuggets.com/2017/12/10-deep-learning-methods-ai-practitioners-need-apply.html
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Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018">
The leading experts in the field on the main Data Science, Machine Learning, Predictive Analytics developments in 2017 and key trends in 2018.
Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018
https://www.kdnuggets.com/2017/12/data-science-machine-learning-main-developments-trends.html
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TensorFlow for Short-Term Stocks Prediction
In this post you will see an application of Convolutional Neural Networks to stock market prediction, using a combination of stock prices with sentiment analysis.https://www.kdnuggets.com/2017/12/tensorflow-short-term-stocks-prediction.html
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Using Deep Learning to Solve Real World Problems">
Do you assume that deep learning is only being used for toy problems and in self-learning scenarios? This post includes several firsthand accounts of organizations using deep neural networks to solve real world problems.
Using Deep Learning to Solve Real World Problems
https://www.kdnuggets.com/2017/12/using-deep-learning-solve-real-world-problems.html
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Top 10 Videos on Deep Learning in Python">
Playlists, individual tutorials (not part of a playlist) and online courses on Deep Learning (DL) in Python using the Keras, Theano, TensorFlow and PyTorch libraries. Assumes no prior knowledge. These videos cover all skill levels and time constraints!
Top 10 Videos on Deep Learning in Python
https://www.kdnuggets.com/2017/11/top-10-videos-deep-learning-python.html
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Machine Learning Algorithms: Which One to Choose for Your Problem">
This article will try to explain basic concepts and give some intuition of using different kinds of machine learning algorithms in different tasks. At the end of the article, you’ll find the structured overview of the main features of described algorithms.
Machine Learning Algorithms: Which One to Choose for Your Problem
https://www.kdnuggets.com/2017/11/machine-learning-algorithms-choose-your-problem.html
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Want to know how Deep Learning works? Here’s a quick guide for everyone">
Once you’ve read this article, you will understand the basics of AI and ML. More importantly, you will understand how Deep Learning, the most popular type of ML, works.
Want to know how Deep Learning works? Here’s a quick guide for everyone
https://www.kdnuggets.com/2017/11/deep-learning-works-quick-guide-everyone.html
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7 Steps to Mastering Deep Learning with Keras">
Are you interested in learning how to use Keras? Do you already have an understanding of how neural networks work? Check out this lean, fat-free 7 step plan for going from Keras newbie to master of its basics as quickly as is possible.
7 Steps to Mastering Deep Learning with Keras
https://www.kdnuggets.com/2017/10/seven-steps-deep-learning-keras.html
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Ranking Popular Deep Learning Libraries for Data Science">
We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.
Ranking Popular Deep Learning Libraries for Data Science
https://www.kdnuggets.com/2017/10/ranking-popular-deep-learning-libraries-data-science.html
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Understanding Machine Learning Algorithms">
Machine learning algorithms aren’t difficult to grasp if you understand the basic concepts. Here, a SAS data scientist describes the foundations for some of today’s popular algorithms.
Understanding Machine Learning Algorithms
https://www.kdnuggets.com/2017/10/understanding-machine-learning-algorithms.html
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Machine Learning Translation and the Google Translate Algorithm
Today, we’ve decided to explore machine translators and explain how the Google Translate algorithm works.https://www.kdnuggets.com/2017/09/machine-learning-translation-google-translate-algorithm.html
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New-Age Machine Learning Algorithms in Retail Lending">
We review the application of new age Machine Learning algorithms for better Customer Analytics in Lending and Credit Risk Assessment.
New-Age Machine Learning Algorithms in Retail Lending
https://www.kdnuggets.com/2017/09/machine-learning-algorithms-lending.html
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First Steps of Learning Deep Learning: Image Classification in Keras
Whether you want to start learning deep learning for you career, to have a nice adventure (e.g. with detecting huggable objects) or to get insight into machines before they take over, this post is for you!https://www.kdnuggets.com/2017/08/first-steps-learning-deep-learning-image-classification-keras.html
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5 Free Resources for Getting Started with Deep Learning for Natural Language Processing">
This is a collection of 5 deep learning for natural language processing resources for the uninitiated, intended to open eyes to what is possible and to the current state of the art at the intersection of NLP and deep learning. It should also provide some idea of where to go next.
5 Free Resources for Getting Started with Deep Learning for Natural Language Processing
https://www.kdnuggets.com/2017/07/5-free-resources-getting-started-deep-learning-nlp.html
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Deep Learning Papers Reading Roadmap">
The roadmap is constructed in accordance with the following four guidelines: from outline to detail; from old to state-of-the-art; from generic to specific areas; focus on state-of-the-art.
Deep Learning Papers Reading Roadmap
https://www.kdnuggets.com/2017/06/deep-learning-papers-reading-roadmap.html
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Deep Learning 101: Demystifying Tensors">
Many deep-learning systems available today are based on tensor algebra, but tensor algebra isn’t tied to deep-learning. It isn’t hard to get started with tensor abuse but can be hard to stop.
Deep Learning 101: Demystifying Tensors
https://www.kdnuggets.com/2017/06/deep-learning-demystifying-tensors.html
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Deep Learning in Minutes with this Pre-configured Python VM Image">
Check out this Python deep learning virtual machine image, built on top of Ubuntu, which includes a number of machine learning tools and libraries, along with several projects to get up and running with right away.
Deep Learning in Minutes with this Pre-configured Python VM Image
https://www.kdnuggets.com/2017/05/deep-learning-pre-configured-python-vm-image.html
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How Not To Program the TensorFlow Graph
Using TensorFlow from Python is like using Python to program another computer. Being thoughtful about the graphs you construct can help you avoid confusion and costly performance problems.https://www.kdnuggets.com/2017/05/how-not-program-tensorflow-graph.html
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The Guerrilla Guide to Machine Learning with Python">
Here is a bare bones take on learning machine learning with Python, a complete course for the quick study hacker with no time (or patience) to spare.
The Guerrilla Guide to Machine Learning with Python
https://www.kdnuggets.com/2017/05/guerrilla-guide-machine-learning-python.html
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Awesome Deep Learning: Most Cited Deep Learning Papers">
This post introduces a curated list of the most cited deep learning papers (since 2012), provides the inclusion criteria, shares a few entry examples, and points to the full listing for those interested in investigating further.
Awesome Deep Learning: Most Cited Deep Learning Papers
https://www.kdnuggets.com/2017/04/awesome-deep-learning-most-cited-papers.html
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5 Machine Learning Projects You Can No Longer Overlook, April">
It's about that time again... 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out. Find tools for data exploration, topic modeling, high-level APIs, and feature selection herein.
5 Machine Learning Projects You Can No Longer Overlook, April
https://www.kdnuggets.com/2017/04/five-machine-learning-projects-cant-overlook-april.html
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Getting Started with Deep Learning
This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.https://www.kdnuggets.com/2017/03/getting-started-deep-learning.html
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Open Source Toolkits for Speech Recognition
This article reviews the main options for free speech recognition toolkits that use traditional Hidden Markov Models and n-gram language models.https://www.kdnuggets.com/2017/03/open-source-toolkits-speech-recognition.html
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7 More Steps to Mastering Machine Learning With Python">
This post is a follow-up to last year's introductory Python machine learning post, which includes a series of tutorials for extending your knowledge beyond the original.
7 More Steps to Mastering Machine Learning With Python
https://www.kdnuggets.com/2017/03/seven-more-steps-machine-learning-python.html
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An Overview of Python Deep Learning Frameworks">
Read this concise overview of leading Python deep learning frameworks, including Theano, Lasagne, Blocks, TensorFlow, Keras, MXNet, and PyTorch.
An Overview of Python Deep Learning Frameworks
https://www.kdnuggets.com/2017/02/python-deep-learning-frameworks-overview.html
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Learning to Learn by Gradient Descent by Gradient Descent
What if instead of hand designing an optimising algorithm (function) we learn it instead? That way, by training on the class of problems we’re interested in solving, we can learn an optimum optimiser for the class!https://www.kdnuggets.com/2017/02/learning-learn-gradient-descent.html
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Deep Learning Research Review: Natural Language Processing">
This edition of Deep Learning Research Review explains recent research papers in Natural Language Processing (NLP). If you don't have the time to read the top papers yourself, or need an overview of NLP with Deep Learning, this post is for you.
Deep Learning Research Review: Natural Language Processing
https://www.kdnuggets.com/2017/01/deep-learning-review-natural-language-processing.html
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6 areas of AI and Machine Learning to watch closely">
Artificial Intelligence is a generic term and many fields of science overlaps when comes to make an AI application. Here is an explanation of AI and its 6 major areas to be focused, going forward.
6 areas of AI and Machine Learning to watch closely
https://www.kdnuggets.com/2017/01/6-areas-ai-machine-learning.html
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Top 20 Python Machine Learning Open Source Projects, updated">
Open Source is the heart of innovation and rapid evolution of technologies, these days. This article presents you Top 20 Python Machine Learning Open Source Projects of 2016 along with very interesting insights and trends found during the analysis.
Top 20 Python Machine Learning Open Source Projects, updated
https://www.kdnuggets.com/2016/11/top-20-python-machine-learning-open-source-updated.html
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Deep Learning Reading Group: Skip-Thought Vectors
Skip-thought vectors take inspiration from Word2Vec skip-gram and attempt to extend it to sentences, and are created using an encoder-decoder model. Read on for an overview of the paper.https://www.kdnuggets.com/2016/11/deep-learning-group-skip-thought-vectors.html
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9 Key Deep Learning Papers, Explained">
If you are interested in understanding the current state of deep learning, this post outlines and thoroughly summarizes 9 of the most influential contemporary papers in the field.
9 Key Deep Learning Papers, Explained
https://www.kdnuggets.com/2016/09/9-key-deep-learning-papers-explained.html
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The Human Vector: Incorporate Speaker Embeddings to Make Your Bot More Powerful
One of the many ways in which bots can fail is by their (lack of) persona. Learn how speaker embeddings can help with this problem, and can help improve the persona of your bot.https://www.kdnuggets.com/2016/09/human-vector-incorporate-speaker-embedding-powerful-bot.html
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Contest Winner: Winning the AutoML Challenge with Auto-sklearn
This post is the first place prize recipient in the recent KDnuggets blog contest. Auto-sklearn is an open-source Python tool that automatically determines effective machine learning pipelines for classification and regression datasets. It is built around the successful scikit-learn library and won the recent AutoML challenge.https://www.kdnuggets.com/2016/08/winning-automl-challenge-auto-sklearn.html
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In Deep Learning, Architecture Engineering is the New Feature Engineering
A discussion of architecture engineering in deep neural networks, and its relationship with feature engineering.https://www.kdnuggets.com/2016/07/deep-learning-architecture-engineering-feature-engineering.html
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How to Start Learning Deep Learning
Want to get started learning deep learning? Sure you do! Check out this great overview, advice, and list of resources.https://www.kdnuggets.com/2016/07/start-learning-deep-learning.html
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Machine Learning for Artists – Video lectures and notes
Art has always been deep for those who appreciate it... but now, more than ever, deep learning is making a real impact on the art world. Check out this graduate course, and its freely-available resources, focusing on this very topic.https://www.kdnuggets.com/2016/04/machine-learning-artists-video-lectures-notes.html
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Top 15 Frameworks for Machine Learning Experts
Either you are a researcher, start-up or big organization who wants to use machine learning, you will need the right tools to make it happen. Here is a list of the most popular frameworks for machine learning.https://www.kdnuggets.com/2016/04/top-15-frameworks-machine-learning-experts.html
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The ICLR Experiment: Deep Learning Pioneers Take on Scientific Publishing
Deep learning pioneers Yann LeCun and Yoshua Bengio have undertaken a grand experiment in academic publishing. Embracing a radical level of transparency and unprecedented public participation, they've created an opportunity not only to find and vet the best papers, but also to gather data about the publication process itself.https://www.kdnuggets.com/2016/02/iclr-deep-learning-scientific-publishing-experiment.html
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Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn">
Scikit Learn is a new easy-to-use interface for TensorFlow from Google based on the Scikit-learn fit/predict model. Does it succeed in making deep learning more accessible?
Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn
https://www.kdnuggets.com/2016/02/scikit-flow-easy-deep-learning-tensorflow-scikit-learn.html
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Google Launches Deep Learning with TensorFlow MOOC
Google and Udacity have partnered for a new self-paced course on deep learning and TensorFlow, starting immediately.https://www.kdnuggets.com/2016/01/google-deep-learning-tensorflow-course.html
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Research Leaders on Data Mining, Data Science and Big Data key advances, top trends
Research Leaders in Data Science and Big Data reflect on the most important research advances in 2015 and the key trends expected to dominate throughout 2016.https://www.kdnuggets.com/2016/01/research-leaders-data-science-big-data-top-trends.html
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Attention and Memory in Deep Learning and NLP
An overview of attention mechanisms and memory in deep neural networks and why they work, including some specific applications in natural language processing and beyond.https://www.kdnuggets.com/2016/01/attention-memory-deep-learning-nlp.html
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7 Steps to Understanding Deep Learning
There are many deep learning resources freely available online, but it can be confusing knowing where to begin. Go from vague understanding of deep neural networks to knowledgeable practitioner in 7 steps!https://www.kdnuggets.com/2016/01/seven-steps-deep-learning.html
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50 Deep Learning Software Tools and Platforms, Updated
We present the popular software & toolkit resources for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch. Explore the new list!https://www.kdnuggets.com/2015/12/deep-learning-tools.html
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Deep Learning Transcends the Bag of Words
Generative RNNs are now widely popular, many modeling text at the character level and typically using unsupervised approach. Here we show how to generate contextually relevant sentences and explain recent work that does it successfully.https://www.kdnuggets.com/2015/12/deep-learning-outgrows-bag-words-recurrent-neural-networks.html
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Deep Learning for Visual Question Answering
Here we discuss about the Visual Question Answering problem, and I’ll also present neural network based approaches for same.https://www.kdnuggets.com/2015/11/deep-learning-visual-question-answering.html
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Deep Learning and the Triumph of Empiricism
Theoretical guarantees are clearly desirable. And yet many of today's best-performing supervised learning algorithms offer none. What explains the gap between theoretical soundness and empirical success?https://www.kdnuggets.com/2015/07/deep-learning-triumph-empiricism-over-theoretical-mathematical-guarantees.html
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Top 20 R packages by popularity
Wondering which are the most popular R packages? Here's an analysis based on most downloaded R packages from Jan to May 2015 to identify the top trending packages in the R world!https://www.kdnuggets.com/2015/06/top-20-r-packages.html
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10 Essential Python Libraries for Data Science in 2024
The richness of Python’s ecosystem has one downside: it makes it difficult to decide which libraries are the best for your needs. This article is an attempt to amend this by suggesting ten (and some more, as a bonus) libraries that are an absolute must in data science.https://www.kdnuggets.com/10-essential-python-libraries-for-data-science-in-2024
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10 GitHub Repositories for Deep Learning Enthusiasts
Learn deep learning through a variety of free resources, including books, courses, tutorials, model implementations, visualizations, and deployment, and Google Colab code examples.https://www.kdnuggets.com/10-github-repositories-for-deep-learning-enthusiasts
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History and Future of LLMs
Check out this concise history and future of large language models.https://www.kdnuggets.com/history-and-future-of-llms
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30 Years of Data Science: A Review From a Data Science Practitioner
A review from a data science practitioner.https://www.kdnuggets.com/30-years-of-data-science-a-review-from-a-data-science-practitioner
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38 Free Courses on Coursera for Data Science">
There are so many online resources for learning data science, and a great deal of it can be used at no cost. This collection of free courses hosted by Coursera will help you enhance your data science and machine learning skills, no matter your current level of expertise.
38 Free Courses on Coursera for Data Science
https://www.kdnuggets.com/2021/10/38-free-courses-coursera-datascience.html
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Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?">
Ever larger models churning on increasingly faster machines suggest a potential path toward smarter AI, such as with the massive GPT-3 language model. However, new, more lean, approaches are being conceived and explored that may rival these super-models, which could lead to a future with more efficient implementations of advanced AI-driven systems.
Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?
https://www.kdnuggets.com/2021/10/trillion-parameters-gpt-3-switch-transformers-path-agi.html
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7 Open Source Libraries for Deep Learning Graphs
In this article we’ll go through 7 up-and-coming open source libraries for graph deep learning, ranked in order of increasing popularity.https://www.kdnuggets.com/2021/07/7-open-source-libraries-deep-learning-graphs.html
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The Essential Guide to Transformers, the Key to Modern SOTA AI
You likely know Transformers from their recent spate of success stories in natural language processing, computer vision, and other areas of artificial intelligence, but are familiar with all of the X-formers? More importantly, do you know the differences, and why you might use one over another?https://www.kdnuggets.com/2021/06/essential-guide-transformers-key-modern-sota-ai.html
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Reducing the High Cost of Training NLP Models With SRU++
The increasing computation time and costs of training natural language models (NLP) highlight the importance of inventing computationally efficient models that retain top modeling power with reduced or accelerated computation. A single experiment training a top-performing language model on the 'Billion Word' benchmark would take 384 GPU days and as much as $36,000 using AWS on-demand instances.https://www.kdnuggets.com/2021/03/reducing-high-cost-training-nlp-models-sru.html
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My machine learning model does not learn. What should I do?
This article presents 7 hints on how to get out of the quicksand.https://www.kdnuggets.com/2021/02/machine-learning-model-not-learn.html
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Backcasting: Building an Accurate Forecasting Model for Your Business
This article will shed some light on processes happening under the roof of ML-based solutions on the example of the business case where the future success directly depends on the ability to predict unknown values from the past.https://www.kdnuggets.com/2021/02/backcasting-building-accurate-forecasting-model-business.html
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Vision Transformers: Natural Language Processing (NLP) Increases Efficiency and Model Generality
Why do we hear so little about transformer models applied to computer vision tasks? What about attention in computer vision networks?https://www.kdnuggets.com/2021/02/vision-transformers-nlp-efficiency-model-generality.html
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Unsupervised Learning for Predictive Maintenance using Auto-Encoders
This article outlines a machine learning approach to detect and diagnose anomalies in the context of machine maintenance, along with a number of introductory concepts, including: Introduction to machine maintenance; What is predictive maintenance?; Approaches for machine diagnosis; Machine diagnosis using machine learninghttps://www.kdnuggets.com/2021/01/unsupervised-learning-predictive-maintenance-auto-encoders.html
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Attention mechanism in Deep Learning, Explained
Attention is a powerful mechanism developed to enhance the performance of the Encoder-Decoder architecture on neural network-based machine translation tasks. Learn more about how this process works and how to implement the approach into your work.https://www.kdnuggets.com/2021/01/attention-mechanism-deep-learning-explained.html
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Top 10 Computer Vision Papers 2020">
The top 10 computer vision papers in 2020 with video demos, articles, code, and paper reference.
Top 10 Computer Vision Papers 2020
https://www.kdnuggets.com/2021/01/top-10-computer-vision-papers-2020.html
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2020: A Year Full of Amazing AI Papers — A Review
So much happened in the world during 2020 that it may have been easy to miss the great progress in the world of AI. To catch you up quickly, check out this curated list of the latest breakthroughs in AI by release date, along with a video explanation, link to an in-depth article, and code.https://www.kdnuggets.com/2020/12/2020-amazing-ai-papers.html
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Compute Goes Brrr: Revisiting Sutton’s Bitter Lesson for AI
"It's just about having more compute." Wait, is that really all there is to AI? As Richard Sutton's 'bitter lesson' sinks in for more AI researchers, a debate has stirred that considers a potentially more subtle relationship between advancements in AI based on ever-more-clever algorithms and massively scaled computational power.https://www.kdnuggets.com/2020/11/revisiting-sutton-bitter-lesson-ai.html
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Roadmap to Computer Vision
Read this introduction to the main steps which compose a computer vision system, starting from how images are pre-processed, features extracted and predictions are made.https://www.kdnuggets.com/2020/10/roadmap-computer-vision.html
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Understanding Transformers, the Data Science Way
Read this accessible and conversational article about understanding transformers, the data science way — by asking a lot of questions that is.https://www.kdnuggets.com/2020/10/understanding-transformers-data-science-way.html
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A Deep Dive Into the Transformer Architecture – The Development of Transformer Models
Even though transformers for NLP were introduced only a few years ago, they have delivered major impacts to a variety of fields from reinforcement learning to chemistry. Now is the time to better understand the inner workings of transformer architectures to give you the intuition you need to effectively work with these powerful tools.https://www.kdnuggets.com/2020/08/transformer-architecture-development-transformer-models.html
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13 must-read papers from AI experts">
What research articles do top AI experts in the field recommend? Find out which ones and why, then be sure to add each to your reading to do list.
13 must-read papers from AI experts
https://www.kdnuggets.com/2020/05/13-must-read-papers-ai-experts.html
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I Designed My Own Machine Learning and AI Degree
With so many pioneering online resources for open education, check out this organized collection of courses you can follow to become a well-rounded machine learning and AI engineer.https://www.kdnuggets.com/2020/05/designed-machine-learning-ai-degree.html
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Customer Churn Prediction: A Global Performance Study
This article details an automated machine-learned approach to predict customer churn and its results across selected communication service providers around the globe.https://www.kdnuggets.com/2020/05/customer-churn-prediction-global-performance-study.html
The Book to Start You on Machine Learning
The 4 Hottest Trends in Data Science for 2020
10 Free Top Notch Machine Learning Courses
10 Free Top Notch Natural Language Processing Courses
How AI will transform healthcare (and can it fix the US healthcare system?)
How to Become More Marketable as a Data Scientist">
How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls
Top Data Science and Machine Learning Methods Used in 2018, 2019
Another 10 Free Must-See Courses for Machine Learning and Data Science">
My favorite mind-blowing Machine Learning/AI breakthroughs
Top 10 Books on NLP and Text Analysis
NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing
Deep Learning Cheat Sheets
An Introduction to AI
The Main Approaches to Natural Language Processing Tasks
Deep Learning for NLP: An Overview of Recent Trends
The Keras 4 Step Workflow
Ten Machine Learning Algorithms You Should Know to Become a Data Scientist
Top 20 Deep Learning Papers, 2018 Edition
A “Weird” Introduction to Deep Learning
Top 20 Python AI and Machine Learning Open Source Projects
A Day in the Life of an AI Developer
Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018
Top 10 Videos on Deep Learning in Python
Want to know how Deep Learning works? Here’s a quick guide for everyone
7 Steps to Mastering Deep Learning with Keras
Ranking Popular Deep Learning Libraries for Data Science
New-Age Machine Learning Algorithms in Retail Lending
5 Free Resources for Getting Started with Deep Learning for Natural Language Processing
Deep Learning Papers Reading Roadmap
Deep Learning 101: Demystifying Tensors
Deep Learning in Minutes with this Pre-configured Python VM Image
Awesome Deep Learning: Most Cited Deep Learning Papers
5 Machine Learning Projects You Can No Longer Overlook, April
7 More Steps to Mastering Machine Learning With Python
6 areas of AI and Machine Learning to watch closely
Top 20 Python Machine Learning Open Source Projects, updated
9 Key Deep Learning Papers, Explained
Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn
38 Free Courses on Coursera for Data Science
Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?
Top 10 Computer Vision Papers 2020
13 must-read papers from AI experts