Search results for deep learning
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Books on Graph-Powered Machine Learning, Graph Databases, Deep Learning for Search – 50% off
These 3 books will help you make the most from graph-powered databases. For a limited time, get 50% off any of them with the code kdngraph.https://www.kdnuggets.com/2019/05/manning-books-graph-machine-learning-databases.html
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Which Deep Learning Framework is Growing Fastest?
In September 2018, I compared all the major deep learning frameworks in terms of demand, usage, and popularity. TensorFlow was the champion of deep learning frameworks and PyTorch was the youngest framework. How has the landscape changed?https://www.kdnuggets.com/2019/05/which-deep-learning-framework-growing-fastest.html
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People Tracking using Deep Learning
Read this overview of people tracking and how deep learning-powered computer vision has allowed for phenomenal performance.https://www.kdnuggets.com/2019/03/people-tracking-using-deep-learning.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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NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing">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.https://www.kdnuggets.com/2019/01/nlp-overview-modern-deep-learning-techniques.html
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Deep learning in Satellite imagery
This article outlines possible sources of satellite imagery, what its properties are and how this data can be utilised using R.https://www.kdnuggets.com/2018/12/deep-learning-satellite-imagery.html
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Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning">Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning
Here are the top 15 Python libraries across Data Science, Data Visualization. Deep Learning, and Machine Learning.https://www.kdnuggets.com/2018/12/top-python-libraries-2018.html
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How to do Deep Learning with SAS
Build a deep learning model using SAS. This paper offers a how-to guide so that you can get up and running.https://www.kdnuggets.com/2018/12/sas-deep-learning.html
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State of Deep Learning and Major Advances: H2 2018 Review
In this post we summarise some of the key developments in deep learning in the second half of 2018, before briefly discussing the road ahead for the deep learning community.https://www.kdnuggets.com/2018/12/deep-learning-major-advances-review.html
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Handling Imbalanced Datasets in Deep Learning
It’s important to understand why we should do it so that we can be sure it’s a valuable investment. Class balancing techniques are only really necessary when we actually care about the minority classes.https://www.kdnuggets.com/2018/12/handling-imbalanced-datasets-deep-learning.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">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.https://www.kdnuggets.com/2018/11/deep-learning-cheat-sheets.html
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Best Deals in Deep Learning Cloud Providers: From CPU to GPU to TPU
A detailed comparison of the best places to train your deep learning model for the lowest cost and hassle, including AWS, Google, Paperspace, vast.ai, and more.https://www.kdnuggets.com/2018/11/deep-learning-cloud-providers-cpu-gpu-tpu.html
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Deep Learning Performance Cheat Sheet
We outline a variety of simple and complex tricks that can help you boost your deep learning models accuracy, from basic optimization, to open source labeling software.https://www.kdnuggets.com/2018/11/deep-learning-performance-cheat-sheet.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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Mastering the Learning Rate to Speed Up Deep Learning
Figuring out the optimal set of hyperparameters can be one of the most time consuming portions of creating a machine learning model, and that’s particularly true in deep learning.https://www.kdnuggets.com/2018/11/mastering-learning-rate-speed-up-deep-learning.html
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Top 13 Python Deep Learning Libraries">Top 13 Python Deep Learning Libraries
Part 2 of a new series investigating the top Python Libraries across Machine Learning, AI, Deep Learning and Data Science.https://www.kdnuggets.com/2018/11/top-python-deep-learning-libraries.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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Preprocessing for Deep Learning: From covariance matrix to image whitening
The goal of this post/notebook is to go from the basics of data preprocessing to modern techniques used in deep learning. My point is that we can use code (Python/Numpy etc.) to better understand abstract mathematical notions!https://www.kdnuggets.com/2018/10/preprocessing-deep-learning-covariance-matrix-image-whitening.html
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Top 3 Trends in Deep Learning
We investigate the intermediate stage of deep learning, and the trends that are emerging in response to the challenges at this stage, including Interoperability and the multi-deployment options.https://www.kdnuggets.com/2018/10/mathworks-top-3-trends-deep-learning.html
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Recent Advances for a Better Understanding of Deep Learning">Recent Advances for a Better Understanding of Deep Learning
A summary of the newest deep learning trends, including Non Convex Optimization, Overparametrization and Generalization, Generative Models, Stochastic Gradient Descent (SGD) and more.https://www.kdnuggets.com/2018/10/recent-advances-deep-learning.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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Power Laws in Deep Learning 2: Universality
It is amazing that Deep Neural Networks display this Universality in their weight matrices, and this suggests some deeper reason for Why Deep Learning Works.https://www.kdnuggets.com/2018/09/power-laws-deep-learning-2-universality.html
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Deep Learning Framework Power Scores 2018
Who’s on top in usage, interest, and popularity?https://www.kdnuggets.com/2018/09/deep-learning-framework-power-scores-2018.html
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Data Capture – the Deep Learning Way
An overview of how an information extraction pipeline built from scratch on top of deep learning inspired by computer vision can shakeup the established field of OCR and data capture.https://www.kdnuggets.com/2018/09/data-capture-deep-learning-way.html
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Power Laws in Deep Learning
In pretrained, production quality DNNs, the weight matrices for the Fully Connected (FC ) layers display Fat Tailed Power Law behavior.https://www.kdnuggets.com/2018/09/power-laws-deep-learning.html
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Deep Learning on the Edge
Detailed analysis into utilizing deep learning on the edge, covering both advantages and disadvantages and comparing this against more traditional cloud computing methods.https://www.kdnuggets.com/2018/09/deep-learning-edge.html
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Neural Networks and Deep Learning: A Textbook">Neural Networks and Deep Learning: A Textbook
This book covers both classical and modern models in deep learning. The book is intended to be a textbook for universities, and it covers the theoretical and algorithmic aspects of deep learning.https://www.kdnuggets.com/2018/09/aggarwal-neural-networks-textbook.html
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Deep Learning for NLP: An Overview of Recent Trends">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.https://www.kdnuggets.com/2018/09/deep-learning-nlp-overview-recent-trends.html
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Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code">Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code
Auto-Keras is an open source software library for automated machine learning. Auto-Keras provides functions to automatically search for architecture and hyperparameters of deep learning models.https://www.kdnuggets.com/2018/08/auto-keras-create-deep-learning-model-4-lines-code.html
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fast.ai Deep Learning Part 2 Complete Course Notes
This posts is a collection of a set of fantastic notes on the fast.ai deep learning part 2 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-2-notes.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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30 Free Resources for Machine Learning, Deep Learning, NLP & AI">30 Free Resources for Machine Learning, Deep Learning, NLP & AI
Check out this collection of 30 ML, DL, NLP & AI resources for beginners, starting from zero and slowly progressing to the point that readers should have an idea of where to go next.https://www.kdnuggets.com/2018/06/30-free-resources-machine-learning-deep-learning-nlp-ai.html
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How To Create Natural Language Semantic Search For Arbitrary Objects With Deep Learning
An end-to-end example of how to build a system that can search objects semantically.https://www.kdnuggets.com/2018/06/natural-language-semantic-search-arbitrary-objects-deep-learning.html
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DIY Deep Learning Projects">DIY Deep Learning Projects
Inspired by the great work of Akshay Bahadur in this article you will see some projects applying Computer Vision and Deep Learning, with implementations and details so you can reproduce them on your computer.https://www.kdnuggets.com/2018/06/diy-deep-learning-projects.html
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Descriptive analytics, machine learning, and deep learning viewed via the lens of CRISP-DM
CRISP-DM methodology is a must teach to explain analytics project steps. This article purpose it to complement it with specific chart flow that explain as simply as possible how it is more likely used in descriptive analytics, classic machine learning or deep learning.https://www.kdnuggets.com/2018/05/descriptive-analytics-machine-learning-deep-learning-crisp-dm.html
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An Introduction to Deep Learning for Tabular Data
This post will discuss a technique that many people don’t even realize is possible: the use of deep learning for tabular data, and in particular, the creation of embeddings for categorical variables.https://www.kdnuggets.com/2018/05/introduction-deep-learning-tabular-data.html
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Deep learning scaling is predictable, empirically
This study starts with a simple question: “how can we improve the state of the art in deep learning?”https://www.kdnuggets.com/2018/05/deep-learning-scaling-predictable-empirically.html
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Data Augmentation: How to use Deep Learning when you have Limited Data
This article is a comprehensive review of Data Augmentation techniques for Deep Learning, specific to images.https://www.kdnuggets.com/2018/05/data-augmentation-deep-learning-limited-data.html
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Detecting Breast Cancer with Deep Learning
Breast cancer is the most common invasive cancer in women, and the second main cause of cancer death in women, after lung cancer. In this article I will build a WideResNet based neural network to categorize slide images into two classes, one that contains breast cancer and other that doesn’t using Deep Learning Studio.https://www.kdnuggets.com/2018/05/detecting-breast-cancer-deep-learning.html
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Implementing Deep Learning Methods and Feature Engineering for Text Data: FastText
Overall, FastText is a framework for learning word representations and also performing robust, fast and accurate text classification. The framework is open-sourced by Facebook on GitHub.https://www.kdnuggets.com/2018/05/implementing-deep-learning-methods-feature-engineering-text-data-fasttext.html
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Implementing Deep Learning Methods and Feature Engineering for Text Data: The GloVe Model
The GloVe model stands for Global Vectors which is an unsupervised learning model which can be used to obtain dense word vectors similar to Word2Vec.https://www.kdnuggets.com/2018/04/implementing-deep-learning-methods-feature-engineering-text-data-glove.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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Why Deep Learning is perfect for NLP (Natural Language Processing)">Why Deep Learning is perfect for NLP (Natural Language Processing)
Deep learning brings multiple benefits in learning multiple levels of representation of natural language. Here we will cover the motivation of using deep learning and distributed representation for NLP, word embeddings and several methods to perform word embeddings, and applications.https://www.kdnuggets.com/2018/04/why-deep-learning-perfect-nlp-natural-language-processing.html
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Deep Learning With Apache Spark: Part 1
First part on a full discussion on how to do Distributed Deep Learning with Apache Spark. This part: What is Spark, basics on Spark+DL and a little more.https://www.kdnuggets.com/2018/04/deep-learning-apache-spark-part-1.html
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Top 8 Free Must-Read Books on Deep Learning">Top 8 Free Must-Read Books on Deep Learning
Deep Learning is the newest trend coming out of Machine Learning, but what exactly is it? And how do I learn more? With that in mind, here's a list of 8 free books on deep learning.https://www.kdnuggets.com/2018/04/top-free-books-deep-learning.html
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Implementing Deep Learning Methods and Feature Engineering for Text Data: The Skip-gram Model
Just like we discussed in the CBOW model, we need to model this Skip-gram architecture now as a deep learning classification model such that we take in the target word as our input and try to predict the context words.https://www.kdnuggets.com/2018/04/implementing-deep-learning-methods-feature-engineering-text-data-skip-gram.html
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Top 20 Deep Learning Papers, 2018 Edition">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.https://www.kdnuggets.com/2018/03/top-20-deep-learning-papers-2018.html
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Implementing Deep Learning Methods and Feature Engineering for Text Data: The Continuous Bag of Words (CBOW)
The CBOW model architecture tries to predict the current target word (the center word) based on the source context words (surrounding words).https://www.kdnuggets.com/2018/04/implementing-deep-learning-methods-feature-engineering-text-data-cbow.html
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A “Weird” Introduction to Deep Learning">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.https://www.kdnuggets.com/2018/03/weird-introduction-deep-learning.html
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Understanding Feature Engineering: Deep Learning Methods for Text Data
Newer, advanced strategies for taming unstructured, textual data: In this article, we will be looking at more advanced feature engineering strategies which often leverage deep learning models.https://www.kdnuggets.com/2018/03/understanding-feature-engineering-deep-learning-methods-text-data.html
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Comparing Deep Learning Frameworks: A Rosetta Stone Approach
A Rosetta Stone of deep-learning frameworks has been created to allow data-scientists to easily leverage their expertise from one framework to another.https://www.kdnuggets.com/2018/03/deep-learning-frameworks.html
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Top Stories, Feb 19-25: Top 20 Python AI and Machine Learning Open Source Projects; Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch
Also: Want a Job in Data? Learn This; A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018; 5 Fantastic Practical Natural Language Processing Resources; Neural network AI is simplehttps://www.kdnuggets.com/2018/02/top-news-week-0219-0225.html
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Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch">Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch
Now you can develop deep learning applications with Google Colaboratory - on the free Tesla K80 GPU - using Keras, Tensorflow and PyTorch.https://www.kdnuggets.com/2018/02/google-colab-free-gpu-tutorial-tensorflow-keras-pytorch.html
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Upcoming Meetings in AI, Analytics, Big Data, Data Science, Deep Learning, Machine Learning: February and Beyond
Coming soon: TDWI Las Vegas, BI + Analytics Huntington Beach, Strata San Jose, IBM Think Las Vegas, Big Data & Analytics Singapore, KNIME Berlin, Nvidia GPU, and more.https://www.kdnuggets.com/2018/02/upcoming-meetings.html
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The AGI/Deep Learning Connection
Also, deep learning would definitely prove to be an essential component to create truly intelligent machines but probably not enough alone.https://www.kdnuggets.com/2018/02/agi-deep-learning-connection.html
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Understanding Learning Rates and How It Improves Performance in Deep Learning
Furthermore, the learning rate affects how quickly our model can converge to a local minima (aka arrive at the best accuracy). Thus getting it right from the get go would mean lesser time for us to train the model.https://www.kdnuggets.com/2018/02/understanding-learning-rates-improves-performance-deep-learning.html
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My Journey into Deep Learning
In this post I’ll share how I’ve been studying Deep Learning and using it to solve data science problems. It’s an informal post but with interesting content (I hope).https://www.kdnuggets.com/2018/01/journey-into-deep-learning.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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Democratizing Artificial Intelligence, Deep Learning, Machine Learning with Dell EMC Ready Solutions
Democratization is defined as the action/development of making something accessible to everyone, to the “common masses.” AI | ML | DL technology stacks are complicated systems to tune and maintain, expertise is limited, and one minimal change of the stack can lead to failure.https://www.kdnuggets.com/2018/01/democratizing-ai-deep-learning-machine-learning-dell-emc.html
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Deep Learning Made Easy with Deep Cognition
So normally we do Deep Learning programming, and learning new APIs, some harder than others, some are really easy an expressive like Keras, but how about a visual API to create and deploy Deep Learning solutions with the click of a button? This is the promise of Deep Cognition.https://www.kdnuggets.com/2017/12/deep-learning-made-easy-deep-cognition.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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Using Deep Learning to Solve Real World Problems">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.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">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!https://www.kdnuggets.com/2017/11/top-10-videos-deep-learning-python.html
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Want to know how Deep Learning works? Here’s a quick guide for everyone">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.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">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.https://www.kdnuggets.com/2017/10/seven-steps-deep-learning-keras.html
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Neural Networks, Step 1: Where to Begin with Neural Nets & Deep Learning
This is a short post for beginners learning neural networks, covering several essential neural networks concepts.https://www.kdnuggets.com/2017/10/neural-networks-step-1.html
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Ranking Popular Deep Learning Libraries for Data Science">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.https://www.kdnuggets.com/2017/10/ranking-popular-deep-learning-libraries-data-science.html
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5 Free Resources for Furthering Your Understanding of Deep Learning
This post includes 5 specific video-based options for furthering your understanding of neural networks and deep learning, collectively consisting of many, many hours of insights.https://www.kdnuggets.com/2017/10/5-free-resources-furthering-understanding-deep-learning.html
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An Overview of 3 Popular Courses on Deep Learning">An Overview of 3 Popular Courses on Deep Learning
After completing the 3 most popular MOOCS in deep learning from Fast.ai, deeplearning.ai/Coursera (which is not completely released) and Udacity, I believe a post about what you can expect from these 3 courses will be useful for future Deep learning enthusiasts.https://www.kdnuggets.com/2017/10/3-popular-courses-deep-learning.html
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30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets">30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets
This collection of data science cheat sheets is not a cheat sheet dump, but a curated list of reference materials spanning a number of disciplines and tools.https://www.kdnuggets.com/2017/09/essential-data-science-machine-learning-deep-learning-cheat-sheets.html
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Detecting Facial Features Using Deep Learning
A challenging task in the past was detection of faces and their features like eyes, nose, mouth and even deriving emotions from their shapes. This task can be now “magically” solved by deep learning and any talented teenager can do it in a few hours.https://www.kdnuggets.com/2017/09/detecting-facial-features-deep-learning.html
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Top Stories, Aug 21-27: 42 Steps to Mastering Data Science; Deep Learning is not the AI future
Also: 37 Reasons why your Neural Network is not working; Machine Learning vs. Statistics: The Texas Death Match of Data Science; Understanding overfitting: an inaccurate meme in Machine Learning; Recommendation System Algorithms: An Overview; The Ultimate Guide to Basic Data Cleaninghttps://www.kdnuggets.com/2017/08/top-news-week-0821-0827.html
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Deep Learning and Neural Networks Primer: Basic Concepts for Beginners
This is a collection of introductory posts which present a basic overview of neural networks and deep learning. Start by learning some key terminology and gaining an understanding through some curated resources. Then look at summarized important research in the field before looking at a pair of concise case studies.https://www.kdnuggets.com/2017/08/deep-learning-neural-networks-primer-basic-concepts-beginners.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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How I Used Deep Learning To Train A Chatbot To Talk Like Me">How I Used Deep Learning To Train A Chatbot To Talk Like Me
In this post, we’ll be looking at how we can use a deep learning model to train a chatbot on my past social media conversations in hope of getting the chatbot to respond to messages the way that I would.https://www.kdnuggets.com/2017/08/deep-learning-train-chatbot-talk-like-me.html
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Train your Deep Learning Faster: FreezeOut
We explain another novel method for much faster training of Deep Learning models by freezing the intermediate layers, and show that it has little or no effect on accuracy.https://www.kdnuggets.com/2017/08/train-deep-learning-faster-freezeout.html
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AI and Deep Learning, Explained Simply">AI and Deep Learning, Explained Simply
AI can now see, hear, and even bluff better than most people. We look into what is new and real about AI and Deep Learning, and what is hype or misinformation.
https://www.kdnuggets.com/2017/07/ai-deep-learning-explained-simply.html
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5 Free Resources for Getting Started with Deep Learning for Natural Language Processing">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.https://www.kdnuggets.com/2017/07/5-free-resources-getting-started-deep-learning-nlp.html
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Cartoon: The First Ever Self-Driving, Deep Learning Grill
New KDnuggets Cartoon looks at what happens when self-driving craze collides with the traditional summer pastime of grilling.https://www.kdnuggets.com/2017/07/cartoon-self-driving-grill.html
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The Strange Loop in Deep Learning
This ‘strange loop’ is in fact is the fundamental reason for what Yann LeCun describes as “the coolest idea in machine learning in the last twenty years.”https://www.kdnuggets.com/2017/07/strange-loop-deep-learning.html
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What Are Artificial Intelligence, Machine Learning, and Deep Learning?">What Are Artificial Intelligence, Machine Learning, and Deep Learning?
AI and Machine Learning have become mainstream, and people know shockingly little about it. Here is an explainer and useful references.https://www.kdnuggets.com/2017/07/rapidminer-ai-machine-learning-deep-learning.html
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Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners, part 2">Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners, part 2
Here are deep learning examples and demos you can just download and run, including Spotify Artist Search using Speech APIs, Symbolic AI Speech Recognition, and Algorithmia API Photo Colorizer.https://www.kdnuggets.com/2017/07/deep-learning-demos-code-beginners-part2.html
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Applying Deep Learning to Real-world Problems">Applying Deep Learning to Real-world Problems
In this blog post I shared three learnings that are important to us at Merantix when applying deep learning to real-world problems. I hope that these ideas are helpful for other people who plan to use deep learning in their business.https://www.kdnuggets.com/2017/06/applying-deep-learning-real-world-problems.html
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Deep Learning with R + Keras
Keras has grown in popularity and supported on a wide set of platforms including Tensorflow, CNTK, Apple’s CoreML, and Theano. It is becoming the de factor language for deep learning.https://www.kdnuggets.com/2017/06/deep-learning-r-keras.html
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Understanding Deep Learning Requires Re-thinking Generalization">Understanding Deep Learning Requires Re-thinking Generalization
What is it that distinguishes neural networks that generalize well from those that don’t? A satisfying answer to this question would not only help to make neural networks more interpretable, but it might also lead to more principled and reliable model architecture design.https://www.kdnuggets.com/2017/06/understanding-deep-learning-rethinking-generalization.html
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Deep Learning Papers Reading Roadmap">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.https://www.kdnuggets.com/2017/06/deep-learning-papers-reading-roadmap.html
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Deep Learning: TensorFlow Programming via XML and PMML
In this approach, problem dataset and its Neural network are specified in a PMML like XML file. Then it is used to populate the TensorFlow graph, which, in turn run to get the results.https://www.kdnuggets.com/2017/06/deep-learning-tensorflow-programming-xml-pmml.html
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Deep Learning 101: Demystifying Tensors">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.https://www.kdnuggets.com/2017/06/deep-learning-demystifying-tensors.html
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Why Does Deep Learning Not Have a Local Minimum?
"As I understand, the chance of having a derivative zero in each of the thousands of direction is low. Is there some other reason besides this?"https://www.kdnuggets.com/2017/06/deep-learning-local-minimum.html
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Data preprocessing for deep learning with nuts-ml
Nuts-ml is a new data pre-processing library in Python for GPU-based deep learning in vision. It provides common pre-processing functions as independent, reusable units. These so called ‘nuts’ can be freely arranged to build data flows that are efficient, easy to read and modify.https://www.kdnuggets.com/2017/05/data-pre-processing-deep-learning-nuts-ml.html
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The Two Phases of Gradient Descent in Deep Learning
In short, you reach different resting placing with different SGD algorithms. That is, different SGDs just give you differing convergence rates due to different strategies, but we do expect that they all end up at the same results!https://www.kdnuggets.com/2017/05/two-phases-gradient-descent-deep-learning.html
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Using Deep Learning To Extract Knowledge From Job Descriptions">Using Deep Learning To Extract Knowledge From Job Descriptions
We present a deep learning approach to extract knowledge from a large amount of data from the recruitment space. A learning to rank approach is followed to train a convolutional neural network to generate job title and job description embeddings.https://www.kdnuggets.com/2017/05/deep-learning-extract-knowledge-job-descriptions.html
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Deep Learning in Minutes with this Pre-configured Python VM Image">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.https://www.kdnuggets.com/2017/05/deep-learning-pre-configured-python-vm-image.html
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Deep Learning – Past, Present, and Future">Deep Learning – Past, Present, and Future
There is a lot of buzz around deep learning technology. First developed in the 1940s, deep learning was meant to simulate neural networks found in brains, but in the last decade 3 key developments have unleashed its potential.https://www.kdnuggets.com/2017/05/deep-learning-big-deal.html
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One Deep Learning Virtual Machine to Rule Them All
The frontend code of programming languages only needs to parse and translate source code to an intermediate representation (IR). Deep Learning frameworks will eventually need their own “IR.”https://www.kdnuggets.com/2017/04/deep-learning-virtual-machine-rule-all.html
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Awesome Deep Learning: Most Cited Deep Learning Papers">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.https://www.kdnuggets.com/2017/04/awesome-deep-learning-most-cited-papers.html
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More Deep Learning “Magic”: Paintings to photos, horses to zebras, and more amazing image-to-image translation
This is an introduction to recent research which presents an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples.https://www.kdnuggets.com/2017/04/unpaired-image-translation-cycle-gan.html
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Top 20 Recent Research Papers on Machine Learning and Deep Learning">Top 20 Recent Research Papers on Machine Learning and Deep Learning
Machine learning and Deep Learning research advances are transforming our technology. Here are the 20 most important (most-cited) scientific papers that have been published since 2014, starting with "Dropout: a simple way to prevent neural networks from overfitting".https://www.kdnuggets.com/2017/04/top-20-papers-machine-learning.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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Homebrewed Deep Learning and Do-It-Yourself Robotics
Learn how to experiment with embodied robotic cognition with IBM Project Intu, a platform that extends Deep Learning and other cognitive services to new devices with minimum coding.https://www.kdnuggets.com/2017/03/ibm-homebrewed-deep-learning-robotics.html
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Greed, Fear, Game Theory and Deep Learning
The most advanced kind of Deep Learning system will involve multiple neural networks that either cooperate or compete to solve problems. The core problem of a multi-agent approach is how to control its behavior.https://www.kdnuggets.com/2017/03/greed-fear-game-theory-deep-learning.html
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An Overview of Python Deep Learning Frameworks">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.https://www.kdnuggets.com/2017/02/python-deep-learning-frameworks-overview.html
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The Anatomy of Deep Learning Frameworks">The Anatomy of Deep Learning Frameworks
This post sketches out some common principles which would help you better understand deep learning frameworks, and provides a guide on how to implement your own deep learning framework as well.
https://www.kdnuggets.com/2017/02/anatomy-deep-learning-frameworks.html
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Deep Learning, Artificial Intuition and the Quest for AGI
Deep Learning systems exhibit behavior that appears biological despite not being based on biological material. It so happens that humanity has luckily stumbled upon Artificial Intuition in the form of Deep Learning.https://www.kdnuggets.com/2017/02/deep-learning-artificial-intelligence-quest-agi.html
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Is Deep Learning the Silver Bullet?
With nearly every every smart young computer scientist planning to work on deep learning, are there really still artificial intelligence researchers working on other techniques? Is deep learning the AI silver bullet?https://www.kdnuggets.com/2017/02/deep-learning-silver-bullet.html
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Deep Learning Research Review: Natural Language Processing">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.https://www.kdnuggets.com/2017/01/deep-learning-review-natural-language-processing.html
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Deep Learning Can be Applied to Natural Language Processing">Deep Learning Can be Applied to Natural Language Processing
This post is a rebuttal to a recent article suggesting that neural networks cannot be applied to natural language given that language is not a produced as a result of continuous function. The post delves into some additional points on deep learning as well.https://www.kdnuggets.com/2017/01/deep-learning-applied-natural-language-processing.html
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Game Theory Reveals the Future of Deep Learning">Game Theory Reveals the Future of Deep Learning
This post covers the emergence of Game Theoretic concepts in the design of newer deep learning architectures. Deep learning systems need to be adaptive to imperfect knowledge and coordinating systems, 2 areas with which game theory can help.https://www.kdnuggets.com/2016/12/game-theory-reveals-future-deep-learning.html
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The Five Capability Levels of Deep Learning Intelligence
Deep learning writer Carlos Perez gives his own classification for deep learning-based AI, which is aimed at practitioners. This classification gives us a sense of where we currently are and where we might be heading.https://www.kdnuggets.com/2016/12/5-capability-levels-deep-learning-intelligence.html
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Why Deep Learning is Radically Different From Machine Learning">Why Deep Learning is Radically Different From Machine Learning
There is a lot of confusion these days about Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL), yet the distinction is very clear to practitioners in these fields. Are you able to articulate the difference?https://www.kdnuggets.com/2016/12/deep-learning-radically-different-machine-learning.html
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The hard thing about deep learning">The hard thing about deep learning
It’s easy to optimize simple neural networks, let’s say single layer perceptron. But, as network becomes deeper, the optmization problem becomes crucial. This article discusses about such optimization problems with deep neural networks.https://www.kdnuggets.com/2016/12/hard-thing-about-deep-learning.html
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Deep Learning Research Review: Reinforcement Learning
This edition of Deep Learning Research Review explains recent research papers in Reinforcement Learning (RL). If you don't have the time to read the top papers yourself, or need an overview of RL in general, this post has you covered.https://www.kdnuggets.com/2016/11/deep-learning-research-review-reinforcement-learning.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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Deep Learning cleans podcast episodes from ‘ahem’ sounds
“3.5 mm audio jack… Ahem!!” where did you hear that? ;) Well, this post is not about Google Pixel vs iPhone 7, but how to remove ugly “Ahem” sound from a speech using deep convolutional neural network. I must say, very interesting read.https://www.kdnuggets.com/2016/11/deep-learning-cleans-podcast-ahem-sounds.html
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Artificial Intelligence, Deep Learning, and Neural Networks, Explained">Artificial Intelligence, Deep Learning, and Neural Networks, Explained
This article is meant to explain the concepts of AI, deep learning, and neural networks at a level that can be understood by most non-practitioners, and can also serve as a reference or review for technical folks as well.https://www.kdnuggets.com/2016/10/artificial-intelligence-deep-learning-neural-networks-explained.html
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Top /r/MachineLearning Posts, September: Open Images Dataset; Whopping Deep Learning Grant; Advanced ML Courseware
Google Research announces the Open Images dataset; Canadian Government Deep Learning Research grant; DeepMind: WaveNet - A Generative Model for Raw Audio; Machine Learning in a Year - From total noob to using it at work; Phd-level machine learning courses; xkcd: Linear Regressionhttps://www.kdnuggets.com/2016/10/top-reddit-machine-learning-september.html
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Deep Learning Reading Group: SqueezeNet
This paper introduces a small CNN architecture called “SqueezeNet” that achieves AlexNet-level accuracy on ImageNet with 50x fewer parameters.https://www.kdnuggets.com/2016/09/deep-learning-reading-group-squeezenet.html
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Deep Learning Reading Group: Deep Residual Learning for Image Recognition
Published in 2015, today's paper offers a new architecture for Convolution Networks, one which has since become a staple in neural network implementation. Read all about it here.https://www.kdnuggets.com/2016/09/deep-learning-reading-group-deep-residual-learning-image-recognition.html
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9 Key Deep Learning Papers, Explained">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.https://www.kdnuggets.com/2016/09/9-key-deep-learning-papers-explained.html
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Deep Learning Reading Group: Deep Networks with Stochastic Depth
An concise overview of a recent paper which introduces a new way to perturb networks during training in order to improve their performance, stochastic depth networks.https://www.kdnuggets.com/2016/09/deep-learning-reading-group-stochastic-depth-networks.html
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KDnuggets™ News 16:n32, Sep 7: Cartoon: Data Scientist was sexiest job until…; Up to Speed on Deep Learning
Cartoon: Data Scientist - the sexiest job of the 21st century until...; Up to Speed on Deep Learning: July Update; How Convolutional Neural Networks Work; Learning from Imbalanced Classes; What is the Role of the Activation Function in a Neural Network?https://www.kdnuggets.com/2016/n32.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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5 Deep Learning Projects You Can No Longer Overlook
There are a number of "mainstream" deep learning projects out there, but many more niche projects flying under the radar. Have a look at 5 such projects worth checking out.https://www.kdnuggets.com/2016/07/five-deep-learning-projects-cant-overlook.html
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What is the Difference Between Deep Learning and “Regular” Machine Learning?">What is the Difference Between Deep Learning and “Regular” Machine Learning?
Another concise explanation of a machine learning concept by Sebastian Raschka. This time, Sebastian explains the difference between Deep Learning and "regular" machine learning.https://www.kdnuggets.com/2016/06/difference-between-deep-learning-regular-machine-learning.html
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Deep Learning and Neuromorphic Chips
The 3 main ingredients to creating artificial intelligence are hardware, software, and data, and while we have focused historically on improving software and data, what if, instead, the hardware was drastically changed?https://www.kdnuggets.com/2016/05/deep-learning-neuromorphic-chips.html
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When Does Deep Learning Work Better Than SVMs or Random Forests®?">When Does Deep Learning Work Better Than SVMs or Random Forests®?
Some advice on when a deep neural network may or may not outperform Support Vector Machines or Random Forests.https://www.kdnuggets.com/2016/04/deep-learning-vs-svm-random-forest.html
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Deep Learning for Chatbots, Part 1 – Introduction
The first in a series of tutorial posts on using Deep Learning for chatbots, this covers some of the techniques being used to build conversational agents, and goes from the current state of affairs through to what is and is not possible.https://www.kdnuggets.com/2016/04/deep-learning-chatbots-part-1.html