Search results for Convolutional Neural Networks
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2011: DanNet triggers deep CNN revolution
In 2021, we are celebrating the 10-year anniversary of DanNet, which, in 2011, was the first pure deep convolutional neural network (CNN) to win computer vision contests. Read about its history here.https://www.kdnuggets.com/2021/02/dannet-triggers-deep-cnn-revolution.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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Deep Learning Pioneer Geoff Hinton on his Latest Research and the Future of AI
Geoff Hinton has lived at the outer reaches of machine learning research since an aborted attempt at a carpentry career a half century ago. He spoke to Craig Smith about his work In 2020 and what he sees on the horizon for AI.https://www.kdnuggets.com/2021/01/deep-learning-pioneer-geoff-hinton-research-future-ai.html
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Mastering TensorFlow Variables in 5 Easy Steps
Learn how to use TensorFlow Variables, their differences from plain Tensor objects, and when they are preferred over these Tensor objects | Deep Learning with TensorFlow 2.x.https://www.kdnuggets.com/2021/01/mastering-tensorflow-variables-5-easy-steps.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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State of Data Science and Machine Learning 2020: 3 Key Findings">State of Data Science and Machine Learning 2020: 3 Key Findings
Kaggle recently released its State of Data Science and Machine Learning report for 2020, based on compiled results of its annual survey. Read about 3 key findings in the report here.https://www.kdnuggets.com/2020/12/kaggle-survey-2020-data-science-machine-learning.html
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Mastering TensorFlow Tensors in 5 Easy Steps
Discover how the building blocks of TensorFlow works at the lower level and learn how to make the most of Tensor objects.https://www.kdnuggets.com/2020/11/mastering-tensorflow-tensors-5-easy-steps.html
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My Data Science Online Learning Journey on Coursera
Check out the author's informative list of courses and specializations on Coursera taken to get started on their data science and machine learning journey.https://www.kdnuggets.com/2020/11/data-science-online-learning-journey-coursera.html
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Interpretability, Explainability, and Machine Learning – What Data Scientists Need to Know
The terms “interpretability,” “explainability” and “black box” are tossed about a lot in the context of machine learning, but what do they really mean, and why do they matter?https://www.kdnuggets.com/2020/11/interpretability-explainability-machine-learning.html
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Explaining the Explainable AI: A 2-Stage Approach
Understanding how to build AI models is one thing. Understanding why AI models provide the results they provide is another. Even more so, explaining any type of understanding of AI models to humans is yet another challenging layer that must be addressed if we are to develop a complete approach to Explainable AI.https://www.kdnuggets.com/2020/10/explaining-explainable-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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Behavior Analysis with Machine Learning and R: The free eBook
Check out this new free ebook to learn how to leverage the power of machine learning to analyze behavioral patterns from sensor data and electronic records using R.https://www.kdnuggets.com/2020/10/behavior-analysis-machine-learning-r-free-ebook.html
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MathWorks Deep learning workflow: tips, tricks, and often forgotten steps
Getting started in deep learning – and adopting an organized, sustainable, and reproducible workflow – can be challenging. This blog post will share some tips and tricks to help you develop a systematic, effective, attainable, and scalable deep learning workflow as you experiment with different deep learning models, datasets, and applications.https://www.kdnuggets.com/2020/09/mathworks-deep-learning-workflow.html
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Deep Learning’s Most Important Ideas">Deep Learning’s Most Important Ideas
In the field of deep learning, there continues to be a deluge of research and new papers published daily. Many well-adopted ideas that have stood the test of time provide the foundation for much of this new work. To better understand modern deep learning, these techniques cover the basic necessary knowledge, especially as a starting point if you are new to the field.https://www.kdnuggets.com/2020/09/deep-learnings-most-important-ideas.html
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AI Papers to Read in 2020
Reading suggestions to keep you up-to-date with the latest and classic breakthroughs in AI and Data Science.https://www.kdnuggets.com/2020/09/ai-papers-read-2020.html
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8 AI/Machine Learning Projects To Make Your Portfolio Stand Out">8 AI/Machine Learning Projects To Make Your Portfolio Stand Out
If you are just starting down a path toward a career in Data Science, or you are already a seasoned practitioner, then keeping active to advance your experience through side projects is invaluable to take you to the next professional level. These eight interesting project ideas with source code and reference articles will jump start you to thinking outside of the box.https://www.kdnuggets.com/2020/09/8-ml-ai-projects-stand-out.html
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Accelerated Computer Vision: A Free Course From Amazon
Amazon's Machine Learning University is making its online courses available to the public, and this time we look at its Accelerated Computer Vision offering.https://www.kdnuggets.com/2020/08/accelerated-computer-vision-free-course-amazon.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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3D Human Pose Estimation Experiments and Analysis
In this article, we explore how 3D human pose estimation works based on our research and experiments, which were part of the analysis of applying human pose estimation in AI fitness coach applications.https://www.kdnuggets.com/2020/08/3d-human-pose-estimation-experiments-analysis.html
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Metrics to Use to Evaluate Deep Learning Object Detectors
It's important to understand which metric should be used to evaluate trained object detectors and which one is more important. Is mAP alone enough to evaluate the objector models? Can the same metric be used to evaluate object detectors on validation set and test set?https://www.kdnuggets.com/2020/08/metrics-evaluate-deep-learning-object-detectors.html
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Awesome Machine Learning and AI Courses">Awesome Machine Learning and AI Courses
Check out this list of awesome, free machine learning and artificial intelligence courses with video lectures.https://www.kdnuggets.com/2020/07/awesome-machine-learning-ai-courses.html
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5 Fantastic Natural Language Processing Books
This curated collection of 5 natural language processing books attempts to cover a number of different aspects of the field, balancing the practical and the theoretical. Check out these 5 fantastic selections now in order to improve your NLP skills.https://www.kdnuggets.com/2020/07/5-fantastic-nlp-books.html
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Graph Machine Learning in Genomic Prediction
This work explores how genetic relationships can be exploited alongside genomic information to predict genetic traits with the aid of graph machine learning algorithms.https://www.kdnuggets.com/2020/06/graph-machine-learning-genomic-prediction.html
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Best Machine Learning Youtube Videos Under 10 Minutes
The Youtube videos on this list cover concepts such as what machine learning is, the basics of natural language processing, how computer vision works, and machine learning in video games.https://www.kdnuggets.com/2020/06/best-machine-learning-youtube-videos-under-10-minutes.html
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Deep Learning for Coders with fastai and PyTorch: The Free eBook">Deep Learning for Coders with fastai and PyTorch: The Free eBook
If you are interested in a top-down, example-driven book on deep learning, check out the draft of the upcoming Deep Learning for Coders with fastai & PyTorch from fast.ai team.https://www.kdnuggets.com/2020/06/fastai-book-free-ebook.html
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5 Machine Learning Papers on Face Recognition
This article will highlight some of that research and introduce five machine learning papers on face recognition.https://www.kdnuggets.com/2020/05/5-machine-learning-papers-face-recognition.html
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13 must-read papers from AI experts">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.https://www.kdnuggets.com/2020/05/13-must-read-papers-ai-experts.html
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Start Your Machine Learning Career in Quarantine">Start Your Machine Learning Career in Quarantine
While this quarantine can last two months, make the most of it by starting your career in Machine Learning with this 60-day learning plan.https://www.kdnuggets.com/2020/05/machine-learning-career-quarantine.html
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Beginners Learning Path for Machine Learning">Beginners Learning Path for Machine Learning
So, you are interested in machine learning? Here is your complete learning path to start your career in the field.https://www.kdnuggets.com/2020/05/beginners-learning-path-machine-learning.html
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5 Papers on CNNs Every Data Scientist Should Read">5 Papers on CNNs Every Data Scientist Should Read
In this article, we introduce 5 papers on CNNs that represent both novel approaches and baselines in the field.https://www.kdnuggets.com/2020/04/5-papers-cnns-data-scientist.html
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Dive Into Deep Learning: The Free eBook
This freely available text on deep learning is fully interactive and incredibly thorough. Check out "Dive Into Deep Learning" now and increase your neural networks theoretical understanding and practical implementation skills.https://www.kdnuggets.com/2020/04/dive-deep-learning-book.html
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How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals">How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals
The goal of this essay is to discuss meaningful machine learning progress in the real-world application of drug discovery. There’s even a solid chance of the deep learning approach to drug discovery changing lives for the better doing meaningful good in the world.https://www.kdnuggets.com/2020/04/deep-learning-accelerating-drug-discovery-pharmaceuticals.html
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10 Must-read Machine Learning Articles (March 2020)">10 Must-read Machine Learning Articles (March 2020)
This list will feature some of the recent work and discoveries happening in machine learning, as well as guides and resources for both beginner and intermediate data scientists.https://www.kdnuggets.com/2020/04/10-must-read-machine-learning-articles-march-2020.html
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Brain Tumor Detection using Mask R-CNN
Mask R-CNN has been the new state of the art in terms of instance segmentation. Here I want to share some simple understanding of it to give you a first look and then we can move ahead and build our model.https://www.kdnuggets.com/2020/03/brain-tumor-detection-mask-r-cnn.html
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Few-Shot Image Classification with Meta-Learning
Here is how you can teach your model to learn quickly from a few examples.https://www.kdnuggets.com/2020/03/few-shot-image-classification-meta-learning.html
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21 Machine Learning Projects – Datasets Included
Upgrading your machine learning, AI, and Data Science skills requires practice. To practice, you need to develop models with a large amount of data. Finding good datasets to work with can be challenging, so this article discusses more than 20 great datasets along with machine learning project ideas for you to tackle today.https://www.kdnuggets.com/2020/03/20-machine-learning-datasets-project-ideas.html
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Hands on Hyperparameter Tuning with Keras Tuner
Or how hyperparameter tuning with Keras Tuner can boost your object classification network's accuracy by 10%.https://www.kdnuggets.com/2020/02/hyperparameter-tuning-keras-tuner.html
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Audio Data Analysis Using Deep Learning with Python (Part 2)
This is a followup to the first article in this series. Once you are comfortable with the concepts explained in that article, you can come back and continue with this.https://www.kdnuggets.com/2020/02/audio-data-analysis-deep-learning-python-part-2.html
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Audio Data Analysis Using Deep Learning with Python (Part 1)">Audio Data Analysis Using Deep Learning with Python (Part 1)
A brief introduction to audio data processing and genre classification using Neural Networks and python.https://www.kdnuggets.com/2020/02/audio-data-analysis-deep-learning-python-part-1.html
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20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)">20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)
2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.https://www.kdnuggets.com/2020/02/ai-data-science-machine-learning-key-terms-2020.html
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Fourier Transformation for a Data Scientist">Fourier Transformation for a Data Scientist
The article contains a brief intro into Fourier transformation mathematically and its applications in AI.https://www.kdnuggets.com/2020/02/fourier-transformation-data-scientist.html
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Easy Image Dataset Augmentation with TensorFlow
What can we do when we don't have a substantial amount of varied training data? This is a quick intro to using data augmentation in TensorFlow to perform in-memory image transformations during model training to help overcome this data impediment.https://www.kdnuggets.com/2020/02/easy-image-dataset-augmentation-tensorflow.html
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Top 10 AI, Machine Learning Research Articles to know">Top 10 AI, Machine Learning Research Articles to know
We’ve seen many predictions for what new advances are expected in the field of AI and machine learning. Here, we review a “data set” based on what researchers were apparently studying at the turn of the decade to take a fresh glimpse into what might come to pass in 2020.https://www.kdnuggets.com/2020/01/top-10-ai-ml-articles-to-know.html
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NLP Year in Review — 2019
In this blog post, I want to highlight some of the most important stories related to machine learning and NLP that I came across in 2019.https://www.kdnuggets.com/2020/01/nlp-year-review-2019.html
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The Book to Start You on Machine Learning">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.https://www.kdnuggets.com/2020/01/book-start-machine-learning.html
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10 Free Top Notch Machine Learning Courses">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.https://www.kdnuggets.com/2019/12/10-free-top-notch-courses-machine-learning.html
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Data Science Curriculum Roadmap">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.https://www.kdnuggets.com/2019/12/data-science-curriculum-roadmap.html
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Pro Tips: How to deal with Class Imbalance and Missing Labels
Your spectacularly-performing machine learning model could be subject to the common culprits of class imbalance and missing labels. Learn how to handle these challenges with techniques that remain open areas of new research for addressing real-world machine learning problems.https://www.kdnuggets.com/2019/11/tips-class-imbalance-missing-labels.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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Research Guide for Video Frame Interpolation with Deep Learning
In this research guide, we’ll look at deep learning papers aimed at synthesizing video frames within an existing video.https://www.kdnuggets.com/2019/10/research-guide-video-frame-interpolation-deep-learning.html
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Beyond Word Embedding: Key Ideas in Document Embedding
This literature review on document embedding techniques thoroughly covers the many ways practitioners develop rich vector representations of text -- from single sentences to entire books.https://www.kdnuggets.com/2019/10/beyond-word-embedding-document-embedding.html
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How AI will transform healthcare (and can it fix the US healthcare system?)">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.https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html
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12 Deep Learning Researchers and Leaders">12 Deep Learning Researchers and Leaders
Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.https://www.kdnuggets.com/2019/09/12-deep-learning-research-leaders.html
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A Single Function to Streamline Image Classification with Keras
We show, step-by-step, how to construct a single, generalized, utility function to pull images automatically from a directory and train a convolutional neural net model.https://www.kdnuggets.com/2019/09/single-function-streamline-image-classification-keras.html
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Beyond Neurons: Five Cognitive Functions of the Human Brain that we are Trying to Recreate with Artificial Intelligence
The quest for recreating cognitive capabilities of the brain in deep neural networks remains one of the elusive goals of AI. Let’s explore some human cognitive skills that are serving as inspiration to a new generation of AI techniques.https://www.kdnuggets.com/2019/09/beyond-neurons-five-cognitive-functions-human-brain-recreate-artificial-intelligence.html
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A 2019 Guide to Human Pose Estimation
Human pose estimation refers to the process of inferring poses in an image. Essentially, it entails predicting the positions of a person’s joints in an image or video. This problem is also sometimes referred to as the localization of human joints.https://www.kdnuggets.com/2019/08/2019-guide-human-pose-estimation.html
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Artificial Intelligence vs. Machine Learning vs. Deep Learning: What is the Difference?
Over the past few years, artificial intelligence continues to be one of the hottest topics. And in order to work effectively with it, you need to understand its constituent parts.https://www.kdnuggets.com/2019/08/artificial-intelligence-vs-machine-learning-vs-deep-learning-difference.html
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A 2019 Guide to Semantic Segmentation
Semantic segmentation refers to the process of linking each pixel in an image to a class label. These labels could include a person, car, flower, piece of furniture, etc., just to mention a few. We’ll now look at a number of research papers on covering state-of-the-art approaches to building semantic segmentation models.https://www.kdnuggets.com/2019/08/2019-guide-semantic-segmentation.html
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Keras Callbacks Explained In Three Minutes
A gentle introduction to callbacks in Keras. Learn about EarlyStopping, ModelCheckpoint, and other callback functions with code examples.https://www.kdnuggets.com/2019/08/keras-callbacks-explained-three-minutes.html
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Knowing Your Neighbours: Machine Learning on Graphs">Knowing Your Neighbours: Machine Learning on Graphs
Graph Machine Learning uses the network structure of the underlying data to improve predictive outcomes. Learn how to use this modern machine learning method to solve challenges with connected data.https://www.kdnuggets.com/2019/08/neighbours-machine-learning-graphs.html
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Pytorch Cheat Sheet for Beginners and Udacity Deep Learning Nanodegree
This cheatsheet should be easier to digest than the official documentation and should be a transitional tool to get students and beginners to get started reading documentations soon.https://www.kdnuggets.com/2019/08/pytorch-cheat-sheet-beginners.html
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A 2019 Guide to Object Detection
Object detection has been applied widely in video surveillance, self-driving cars, and object/people tracking. In this piece, we’ll look at the basics of object detection and review some of the most commonly-used algorithms and a few brand new approaches, as well.https://www.kdnuggets.com/2019/08/2019-guide-object-detection.html
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Adapters: A Compact and Extensible Transfer Learning Method for NLP
Adapters obtain comparable results to BERT on several NLP tasks while achieving parameter efficiency.https://www.kdnuggets.com/2019/07/adapters-compact-extensible-transfer-learning-method-nlp.html
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10 New Things I Learnt from fast.ai Course V3
Fastai offers some really good courses in machine learning and deep learning for programmers. I recently took their "Practical Deep Learning for Coders" course and found it really interesting. Here are my learnings from the course.https://www.kdnuggets.com/2019/06/things-learnt-fastai-course.html
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Building a Computer Vision Model: Approaches and datasets
How can we build a computer vision model using CNNs? What are existing datasets? And what are approaches to train the model? This article provides an answer to these essential questions when trying to understand the most important concepts of computer vision.https://www.kdnuggets.com/2019/05/computer-vision-model-approaches-datasets.html
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Top Data Science and Machine Learning Methods Used in 2018, 2019">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.https://www.kdnuggets.com/2019/04/top-data-science-machine-learning-methods-2018-2019.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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Another 10 Free Must-See Courses for Machine Learning and Data Science">Another 10 Free Must-See Courses for Machine Learning and Data Science
Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.https://www.kdnuggets.com/2019/04/another-10-free-must-see-courses-machine-learning-data-science.html
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Deep Compression: Optimization Techniques for Inference & Efficiency
We explain deep compression for improved inference efficiency, mobile applications, and regularization as technology cozies up to the physical limits of Moore's law.https://www.kdnuggets.com/2019/03/deep-compression-optimization-techniques-inference-efficiency.html
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How to do Everything in Computer Vision
The many standard tasks in computer vision all require special consideration: classification, detection, segmentation, pose estimation, enhancement and restoration, and action recognition. Let me show you how to do everything in Computer Vision with Deep Learning!https://www.kdnuggets.com/2019/02/everything-computer-vision.html
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State of the art in AI and Machine Learning – highlights of papers with code
We introduce papers with code, the free and open resource of state-of-the-art Machine Learning papers, code and evaluation tables.https://www.kdnuggets.com/2019/02/paperswithcode-ai-machine-learning-highlights.html
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A Quick Guide to Feature Engineering
Feature engineering plays a key role in machine learning, data mining, and data analytics. This article provides a general definition for feature engineering, together with an overview of the major issues, approaches, and challenges of the field.https://www.kdnuggets.com/2019/02/quick-guide-feature-engineering.html
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How to solve 90% of NLP problems: a step-by-step guide">How to solve 90% of NLP problems: a step-by-step guide
Read this insightful, step-by-step article on how to use machine learning to understand and leverage text.https://www.kdnuggets.com/2019/01/solve-90-nlp-problems-step-by-step-guide.html
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Top 10 Books on NLP and Text Analysis">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.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">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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Feature Engineering for Machine Learning: 10 Examples
A brief introduction to feature engineering, covering coordinate transformation, continuous data, categorical features, missing values, normalization, and more.https://www.kdnuggets.com/2018/12/feature-engineering-explained.html
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Solve any Image Classification Problem Quickly and Easily
This article teaches you how to use transfer learning to solve image classification problems. A practical example using Keras and its pre-trained models is given for demonstration purposes.https://www.kdnuggets.com/2018/12/solve-image-classification-problem-quickly-easily.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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An Introduction to AI">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.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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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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The Main Approaches to Natural Language Processing Tasks">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.https://www.kdnuggets.com/2018/10/main-approaches-natural-language-processing-tasks.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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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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Free resources to learn Natural Language Processing
An extensive list of free resources to help you learn Natural Language Processing, including explanations on Text Classification, Sequence Labeling, Machine Translation and more.https://www.kdnuggets.com/2018/09/free-resources-natural-language-processing.html
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Object Detection and Image Classification with YOLO
We explain object detection, how YOLO algorithm can help with image classification, and introduce the open source neural network framework Darknet.https://www.kdnuggets.com/2018/09/object-detection-image-classification-yolo.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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UX Design Guide for Data Scientists and AI Products
Realizing that there is a legitimate knowledge gap between UX Designers and Data Scientists, I have decided to attempt addressing the needs from the Data Scientist’s perspective.https://www.kdnuggets.com/2018/08/ux-design-guide-data-scientists-ai-products.html
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Text Classification & Embeddings Visualization Using LSTMs, CNNs, and Pre-trained Word Vectors
In this tutorial, I classify Yelp round-10 review datasets. After processing the review comments, I trained three model in three different ways and obtained three word embeddings.https://www.kdnuggets.com/2018/07/text-classification-lstm-cnn-pre-trained-word-vectors.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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How to Implement a YOLO (v3) Object Detector from Scratch in PyTorch: Part 1">How to Implement a YOLO (v3) Object Detector from Scratch in PyTorch: Part 1
The best way to go about learning object detection is to implement the algorithms by yourself, from scratch. This is exactly what we'll do in this tutorial.https://www.kdnuggets.com/2018/05/implement-yolo-v3-object-detector-pytorch-part-1.html
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Ten Machine Learning Algorithms You Should Know to Become a Data Scientist">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.https://www.kdnuggets.com/2018/04/10-machine-learning-algorithms-data-scientist.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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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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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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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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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">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.https://www.kdnuggets.com/2017/12/data-science-machine-learning-main-developments-trends.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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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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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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Understanding Machine Learning Algorithms">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.https://www.kdnuggets.com/2017/10/understanding-machine-learning-algorithms.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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Using AI to Super Compress Images
Neural Network algorithms are showing promising results for different complex problems. Here we discuss how these algorithms are used in image compression.https://www.kdnuggets.com/2017/08/ai-compress-images.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">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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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 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 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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The Guerrilla Guide to Machine Learning with Python">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.https://www.kdnuggets.com/2017/05/guerrilla-guide-machine-learning-python.html
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A Brief History of Artificial Intelligence">A Brief History of Artificial Intelligence
This post is a brief outline of what happened in artificial intelligence in the last 60 years. A great place to start or brush up on your history.
https://www.kdnuggets.com/2017/04/brief-history-artificial-intelligence.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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7 More Steps to Mastering Machine Learning With Python">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.
https://www.kdnuggets.com/2017/03/seven-more-steps-machine-learning-python.html
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Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017">Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017
As 2016 comes to a close and we prepare for a new year, check out the final instalment in our "Main Developments in 2016 and Key Trends in 2017" series, where experts weigh in with their opinions.https://www.kdnuggets.com/2016/12/machine-learning-artificial-intelligence-main-developments-2016-key-trends-2017.html
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ResNets, HighwayNets, and DenseNets, Oh My!
This post walks through the logic behind three recent deep learning architectures: ResNet, HighwayNet, and DenseNet. Each make it more possible to successfully trainable deep networks by overcoming the limitations of traditional network design.https://www.kdnuggets.com/2016/12/resnets-highwaynets-densenets-oh-my.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 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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Introduction to Trainspotting: Computer Vision, Caltrain, and Predictive Analytics
We previously analyzed delays using Caltrain’s real-time API to improve arrival predictions, and we have modeled the sounds of passing trains to tell them apart. In this post we’ll start looking at the nuts and bolts of making our Caltrain work possible.https://www.kdnuggets.com/2016/11/introduction-trainspotting.html
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Data Science Basics: 3 Insights for Beginners
For data science beginners, 3 elementary issues are given overview treatment: supervised vs. unsupervised learning, decision tree pruning, and training vs. testing datasets.https://www.kdnuggets.com/2016/09/data-science-basics-3-insights-beginners.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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7 Steps to Understanding Computer Vision
A starting point for Computer Vision and how to get going deeper. Dive into this post for some overview of the right resources and a little bit of advice.https://www.kdnuggets.com/2016/08/seven-steps-understanding-computer-vision.html
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Reinforcement Learning and the Internet of Things
Gain an understanding of how reinforcement learning can be employed in the Internet of Things world.https://www.kdnuggets.com/2016/08/reinforcement-learning-internet-things.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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Improving Nudity Detection and NSFW Image Recognition
This post discussed improvements made in a tricky machine learning classification problem: nude and/or NSFW, or not?https://www.kdnuggets.com/2016/06/algorithmia-improving-nudity-detection-nsfw-image-recognition.html
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Top Machine Learning Libraries for Javascript
Javascript may not be the conventional choice for machine learning, but there is no reason it cannot be used for such tasks. Here are the top libraries to facilitate machine learning in Javascript.https://www.kdnuggets.com/2016/06/top-machine-learning-libraries-javascript.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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Predicting Popularity of Online Content
A look at predicting what makes online content popular, with a particular focus on images, especially selfies.https://www.kdnuggets.com/2016/05/predicting-popularity-online-content.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