Tag: Deep Learning (1006)

• Deep Learning Recommendation Models (DLRM): A Deep Dive - Apr 9, 2021.
  
  The currency in the 21st century is no longer just data. It's the attention of people. This deep dive article presents the architecture and deployment issues experienced with the deep learning recommendation model, DLRM, which was open-sourced by Facebook in March 2019.

  Tags: Deep Learning, Recommendations, Recommender Systems

• How to deploy Machine Learning/Deep Learning models to the web - Apr 5, 2021.
  
  The full value of your deep learning models comes from enabling others to use them. Learn how to deploy your model to the web and access it as a REST API, and begin to share the power of your machine learning development with the world.

  Tags: Deep Learning, Deployment, Machine Learning, RESTful API

• Deep Learning Is Becoming Overused - Mar 29, 2021.
  
  Understanding the data is the first port of call.

  Tags: Classification, Deep Learning, Neural Networks, Regression, Time Series

• 10 Amazing Machine Learning Projects of 2020 - Mar 15, 2021.
  
  So much progress in AI and machine learning happened in 2020, especially in the areas of AI-generating creativity and low-to-no-code frameworks. Check out these trending and popular machine learning projects released last year, and let them inspire your work throughout 2021.

  Tags: Chatbot, Deep Learning, Image Processing, Machine Learning, Project, Trends

• Reducing the High Cost of Training NLP Models With SRU++ - Mar 4, 2021.
  
  The increasing computation time and costs of training natural language models (NLP) highlight the importance of inventing computationally efficient models that retain top modeling power with reduced or accelerated computation. A single experiment training a top-performing language model on the 'Billion Word' benchmark would take 384 GPU days and as much as $36,000 using AWS on-demand instances.

  Tags: Deep Learning, Machine Learning, Neural Networks, NLP

• KDnuggets™ News 21:n08, Feb 24: Powerful Exploratory Data Analysis in just two lines of code; Cartoon: Data Scientist vs Data Engineer - Feb 24, 2021.
  
  Powerful Exploratory Data Analysis in just two lines of code; Cartoon: Data Scientist vs Data Engineer; Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall; Feature Store as a Foundation for Machine Learning; Approaching (Almost) Any Machine Learning Problem

  Tags: Cartoon, Data Analysis, Data Engineering, Data Science, Deep Learning, Machine Learning, Metrics, Python

• Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall - Feb 19, 2021.
  
  This tutorial discusses the confusion matrix, and how the precision, recall and accuracy are calculated, and how they relate to evaluating deep learning models.

  Tags: Accuracy, Confusion Matrix, Deep Learning, Metrics, Precision, Recall

• Approaching (Almost) Any Machine Learning Problem - Feb 18, 2021.
  
  This freely-available book is a fantastic walkthrough of practical approaches to machine learning problems.

  Tags: Deep Learning, Free ebook, Machine Learning, Python

• Deep Learning-based Real-time Video Processing - Feb 17, 2021.
  
  In this article, we explore how to build a pipeline and process real-time video with Deep Learning to apply this approach to business use cases overviewed in our research.

  Tags: Computer Vision, Deep Learning, Neural Networks, Video recognition

• Hugging Face Transformers Package – What Is It and How To Use It - Feb 16, 2021.
  
  The rapid development of Transformers have brought a new wave of powerful tools to natural language processing. These models are large and very expensive to train, so pre-trained versions are shared and leveraged by researchers and practitioners. Hugging Face offers a wide variety of pre-trained transformers as open-source libraries, and you can incorporate these with only one line of code.

  Tags: Deep Learning, Hugging Face, Natural Language Generation, NLP, PyTorch, TensorFlow, Transformer, Zero-shot Learning

• KDnuggets™ News 21:n06, Feb 10: The Best Data Science Project to Have in Your Portfolio; Deep learning doesn’t need to be a black box - Feb 10, 2021.
  
  The Best Data Science Project to Have in Your Portfolio; Deep learning doesn’t need to be a black box; Build Your First Data Science Application; How to create stunning visualizations using python from scratch; How to Get Your First Job in Data Science without Any Work Experience

  Tags: Career Advice, Data Science, Data Visualization, Deep Learning, Explainability, Portfolio, Python

• Deep learning doesn’t need to be a black box - Feb 5, 2021.
  
  The cultural perception of AI is often suspect because of the described challenges in knowing why a deep neural network makes its predictions. So, researchers try to crack open this "black box" after a network is trained to correlate results with inputs. But, what if the goal of explainability could be designed into the network's architecture -- before the model is trained and without reducing its predictive power? Maybe the box could stay open from the beginning.

  Tags: Convolutional Neural Networks, Deep Learning, Explainability, Explainable AI, Image Recognition

• Saving and loading models in TensorFlow — why it is important and how to do it - Feb 3, 2021.
  
  So much time and effort can go into training your machine learning models. But, shut down the notebook or system, and all those trained weights and more vanish with the memory flush. Saving your models to maximize reusability is key for efficient productivity.

  Tags: Deep Learning, Machine Learning, TensorFlow

• KDnuggets™ News 21:n04, Jan 27: The Ultimate Scikit-Learn Machine Learning Cheatsheet; Building a Deep Learning Based Reverse Image Search - Jan 27, 2021.
  
  The Ultimate Scikit-Learn Machine Learning Cheatsheet; Building a Deep Learning Based Reverse Image Search; Data Engineering — the Cousin of Data Science, is Troublesome; Going Beyond the Repo: GitHub for Career Growth in AI & Machine Learning; Popular Machine Learning Interview Questions

  Tags: Cheat Sheet, Data Engineering, Data Science, Deep Learning, GitHub, Image Recognition, Machine Learning, scikit-learn, Search

• Deep Learning Pioneer Geoff Hinton on his Latest Research and the Future of AI - Jan 26, 2021.
  
  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.

  Tags: AI, Capsule Networks, Deep Learning, Geoff Hinton, Neural Networks, Research

• Building a Deep Learning Based Reverse Image Search - Jan 22, 2021.
  
  Following the journey from unstructured data to content based image retrieval.

  Tags: Deep Learning, Image Recognition, Search

• Attention mechanism in Deep Learning, Explained - Jan 11, 2021.
  
  Attention is a powerful mechanism developed to enhance the performance of the Encoder-Decoder architecture on neural network-based machine translation tasks. Learn more about how this process works and how to implement the approach into your work.

  Tags: Attention, Deep Learning, Explained, LSTM, Machine Translation

• DeepMind’s MuZero is One of the Most Important Deep Learning Systems Ever Created - Jan 4, 2021.
  
  MuZero takes a unique approach to solve the problem of planning in deep learning models.

  Tags: AlphaZero, Deep Learning, DeepMind, MuZero, Reinforcement Learning

• 15 Free Data Science, Machine Learning & Statistics eBooks for 2021 - Dec 31, 2020.
  
  We present a curated list of 15 free eBooks compiled in a single location to close out the year.

  Tags: Automated Machine Learning, Data Science, Deep Learning, Free ebook, Machine Learning, NLP, Python, R, Statistics

• Covid or just a Cough? AI for detecting COVID-19 from Cough Sounds - Dec 15, 2020.
  
  Increased capabilities in screening and early testing for a disease can significantly support quelling its spread and impact. Recent progress in developing deep learning AI models to classify cough sounds as a prescreening tool for COVID-19 has demonstrated promising early success. Cough-based diagnosis is non-invasive, cost-effective, scalable, and, if approved, could be a potential game-changer in our fight against COVID-19.

  Tags: AI, Audio, COVID-19, Deep Learning, Healthcare

• How to Create Custom Real-time Plots in Deep Learning - Dec 14, 2020.
  
  How to generate real-time visualizations of custom metrics while training a deep learning model using Keras callbacks.

  Tags: Data Visualization, Deep Learning, Keras, Metrics, Neural Networks, Python

• Deep Learning Design Patterns! - Dec 9, 2020.
  
  New book, "Deep Learning Design Patterns" presents deep learning models in a unique-but-familiar new way: as extendable design patterns you can easily plug-and-play into your software projects. Use code kdmath50 to save 50% off.

  Tags: Book, Deep Learning, Manning

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 - Dec 3, 2020.
  
  2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.

  Tags: 2021 Predictions, AI, Ajit Jaokar, Analytics, Brandon Rohrer, Daniel Tunkelang, Data Science, Deep Learning, Machine Learning, Pedro Domingos, Predictions, Research, Rosaria Silipo

• KDnuggets™ News 20:n45, Dec 2: TabPy: Combining Python and Tableau; Learn Deep Learning with this Free Course from Yann LeCun - Dec 2, 2020.
  
  Combine Python and Tableau with TabPy; Learn Deep Learning with this Free Course from Yann LeCun; Find 15 Exciting AI Project Ideas for Beginners; Read about the Rise of the Machine Learning Engineer; See How to Incorporate Tabular Data with HuggingFace Transformers

  Tags: AI, Courses, Deep Learning, Hugging Face, Machine Learning Engineer, Python, Tableau, Transformer, Yann LeCun

• Learn Deep Learning with this Free Course from Yann LeCun - Nov 27, 2020.
  
  Here is a freely-available NYU course on deep learning to check out from Yann LeCun and Alfredo Canziani, including videos, slides, and other helpful resources.

  Tags: Courses, Deep Learning, NYU, Yann LeCun

• How to Incorporate Tabular Data with HuggingFace Transformers - Nov 25, 2020.
  
  In real-world scenarios, we often encounter data that includes text and tabular features. Leveraging the latest advances for transformers, effectively handling situations with both data structures can increase performance in your models.

  Tags: Data Preparation, Deep Learning, Machine Learning, NLP, Python, Transformer

• Adversarial Examples in Deep Learning – A Primer - Nov 20, 2020.
  
  Bigger compute has led to increasingly impressive deep learning computer vision model SOTA results. However most of these SOTA deep learning models are brought down to their knees when making predictions on adversarial images. Read on to find out more.

  Tags: Adversarial, Computer Vision, Deep Learning

• Primer on TensorFlow and how PerceptiLabs Makes it Easier - Nov 18, 2020.
  
  With PerceptiLabs, beginners can get started building a model more quickly, and those with more experience can still dive into the code. Given that PerceptiLabs runs TensorFlow behind the scenes, we thought we'd walk through the framework so you can understand its basics, and how it is utilized by PerceptiLabs.

  Tags: AutoML, Deep Learning, Machine Learning, MLOps, PerceptiLabs, TensorFlow

• Facebook Open Sourced New Frameworks to Advance Deep Learning Research - Nov 17, 2020.
  
  Polygames, PyTorch3D and HiPlot are the new additions to Facebook’s open source deep learning stack.

  Tags: Deep Learning, Facebook, Open Source, PyTorch, Research

• Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision - Nov 16, 2020.
  
  This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.

  Tags: Computer Vision, Data Science, Deep Learning, Machine Learning, Neural Networks, NLP, Python

• How to Acquire the Most Wanted Data Science Skills - Nov 13, 2020.
  
  We recently surveyed KDnuggets readers to determine the "most wanted" data science skills. Since they seem to be those most in demand from practitioners, here is a collection of resources for getting started with this learning.

  Tags: Algorithms, Amazon, Apache Spark, AWS, Computer Vision, Data Science, Data Science Skills, Deep Learning, Docker, NLP, NoSQL, PyTorch, Reinforcement Learning, TensorFlow

• Deep Learning Design Patterns. - Nov 11, 2020.
  
  New book, "Deep Learning Design Patterns" presents deep learning models in a unique-but-familiar new way: as extendable design patterns you can easily plug-and-play into your software projects. Use code kdmath50 to save 50% off.

  Tags: Book, Deep Learning, Manning

• Mastering TensorFlow Tensors in 5 Easy Steps - Nov 11, 2020.
  
  Discover how the building blocks of TensorFlow works at the lower level and learn how to make the most of Tensor objects.

  Tags: Deep Learning, Python, Tensor, TensorFlow

• Top 5 Free Machine Learning and Deep Learning eBooks Everyone should read - Nov 5, 2020.
  
  There is always so much new to learn in machine learning, and keeping well grounded in the fundamentals will help you stay up-to-date with the latest advancements while acing your career in Data Science.

  Tags: Deep Learning, Free ebook, Machine Learning

• Building Deep Learning Projects with fastai — From Model Training to Deployment - Nov 4, 2020.
  
  A getting started guide to develop computer vision application with fastai.

  Tags: Deep Learning, Deployment, fast.ai, Modeling, Python, Training

• Microsoft and Google Open Sourced These Frameworks Based on Their Work Scaling Deep Learning Training - Nov 2, 2020.
  
  Google and Microsoft have recently released new frameworks for distributed deep learning training.

  Tags: Deep Learning, Google, Microsoft, Open Source, Scalability, Training

• How to Make Sense of the Reinforcement Learning Agents? - Oct 30, 2020.
  
  In this blog post, you’ll learn what to keep track of to inspect/debug your agent learning trajectory. I’ll assume you are already familiar with the Reinforcement Learning (RL) agent-environment setting and you’ve heard about at least some of the most common RL algorithms and environments.

  Tags: Agents, Deep Learning, Reinforcement Learning

• Building Neural Networks with PyTorch in Google Colab - Oct 30, 2020.
  
  Combining PyTorch and Google's cloud-based Colab notebook environment can be a good solution for building neural networks with free access to GPUs. This article demonstrates how to do just that.

  Tags: Deep Learning, Google Colab, Neural Networks, Python, PyTorch

• An Introduction to AI, updated - Oct 28, 2020.
  
  We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.

  Tags: AGI, AI, Beginners, Deep Learning, Machine Learning

• PerceptiLabs – A GUI and Visual API for TensorFlow - Oct 27, 2020.
  
  Recently released PerceptiLabs 0.11, is quickly becoming the GUI and visual API for TensorFlow. PerceptiLabs is built around a sophisticated visual ML modeling editor in which you drag and drop components and connect them together to form your model, automatically creating the underlying TensorFlow code. Try it now.

  Tags: API, Deep Learning, PerceptiLabs, TensorFlow

• Deep Learning for Virtual Try On Clothes – Challenges and Opportunities - Oct 16, 2020.
  
  Learn about the experiments by MobiDev for transferring 2D clothing items onto the image of a person. As part of their efforts to bring AR and AI technologies into virtual fitting room development, they review the deep learning algorithms and architecture under development and the current state of results.

  Tags: Computer Vision, Deep Learning, Fashion, Generative Adversarial Network, Generative Models, Humans, Image Generation

• Deep Learning Design Patterns - Oct 14, 2020.
  
  New book, "Deep Learning Design Patterns" presents deep learning models in a unique-but-familiar new way: as extendable design patterns you can easily plug-and-play into your software projects. Use code kdmath50 to save 50% off.

  Tags: Book, Deep Learning, Manning

• 10 Best Machine Learning Courses in 2020 - Oct 6, 2020.
  
  If you are ready to take your career in machine learning to the next level, then these top 10 Machine Learning Courses covering both practical and theoretical work will help you excel.

  Tags: Courses, DataCamp, Deep Learning, fast.ai, Machine Learning, Online Education, Python, Stanford

• 10 Days With “Deep Learning for Coders” - Oct 1, 2020.
  
  Read about the author's experience with the course and the book from fast.ai.

  Tags: Courses, Deep Learning, fast.ai, MOOC

• How AI is Driving Innovation in Astronomy - Sep 29, 2020.
  
  In this blog, we look at a disruptive AI program - Morpheus - developed by Researchers at UC Santa Cruz that can analyze astronomical image data and classify galaxies and stars with surgical precision. If you're reading this with "starry" eyes, we bet we've got you hooked.

  Tags: AI, Deep Learning, Innovation, Science

• KDnuggets™ News 20:n36, Sep 23: New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project - Sep 23, 2020.
  
  New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project; Autograd: The Best Machine Learning Library You're Not Using?; Implementing a Deep Learning Library from Scratch in Python; Online Certificates/Courses in AI, Data Science, Machine Learning; Can Neural Networks Show Imagination?

  Tags: Automation, Certificate, Courses, Data Science, Deep Learning, DeepMind, Machine Learning, Neural Networks, Python

• MathWorks Deep learning workflow: tips, tricks, and often forgotten steps - Sep 22, 2020.
  
  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.

  Tags: Deep Learning, MathWorks, MATLAB, Tips

• The Insiders’ Guide to Generative and Discriminative Machine Learning Models - Sep 18, 2020.
  
  In this article, we will look at the difference between generative and discriminative models, how they contrast, and one another.

  Tags: Deep Learning, GANs, Generative Adversarial Network, Modeling

• Implementing a Deep Learning Library from Scratch in Python - Sep 17, 2020.
  
  A beginner’s guide to understanding the fundamental building blocks of deep learning platforms.

  Tags: Deep Learning, Neural Networks, Python

• Autograd: The Best Machine Learning Library You’re Not Using? - Sep 16, 2020.
  
  If there is a Python library that is emblematic of the simplicity, flexibility, and utility of differentiable programming it has to be Autograd.

  Tags: Deep Learning, Neural Networks, Python, PyTorch

• KDnuggets™ News 20:n35, Sep 16: Data Science Skills: Core, Emerging, and Most Wanted; Free From MIT: Intro to CS, Programming in Python - Sep 16, 2020.
  
  Check the analysis of latest KDnuggets Poll: which data science skills are core, which are emerging, and what is the most wanted skill readers want to learn; Free From MIT: Intro to CS and Programming in Python; 8 AI/Machine Learning Projects To Make Your Portfolio Stand Out; Statistics with Julia: The Free eBook; and more.

  Tags: Deep Learning, Julia, Kaggle, MIT, Python

• Deep Learning’s Most Important Ideas - Sep 14, 2020.
  
  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.

  Tags: Attention, Deep Learning, GANs, History, ImageNet, Reinforcement Learning, Transformer

• A Deep Learning Dream: Accuracy and Interpretability in a Single Model - Sep 7, 2020.
  
  IBM Research believes that you can improve the accuracy of interpretable models with knowledge learned in pre-trained models.

  Tags: Accuracy, Deep Learning, Interpretability

• KDnuggets™ News 20:n33, Aug 26: If I had to start learning Data Science again, how would I do it? Must-read NLP and Deep Learning articles for Data Scientists - Aug 26, 2020.
  
  If I had to start learning Data Science again, how would I do it? Must-read NLP and Deep Learning articles for Data Scientists; These Data Science Skills will be your Superpower; Accelerated Natural Language Processing: A Free Amazon Machine Learning University Course.

  Tags: Career, Career Advice, Data Science, Deep Learning, NLP, Research

• A Deep Dive Into the Transformer Architecture – The Development of Transformer Models - Aug 24, 2020.
  
  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.

  Tags: Attention, Deep Learning, Hugging Face, NLP, Transformer

• Must-read NLP and Deep Learning articles for Data Scientists - Aug 21, 2020.
  
  NLP and deep learning continue to advance, nearly on a daily basis. Check out these recent must-read guides, feature articles, and other resources to keep you on top of the latest advancements and ahead of the curve.

  Tags: Deep Learning, Google, GPT-3, NLP, OpenAI, Privacy, Research, Self-Driving, TensorFlow, Trends

• KDD-2020 (virtual), the leading conference on Data Science and Knowledge Discovery, Aug 23-27 – register now - Aug 18, 2020.
  
  Using an interactive VR platform, KDD-2020 brings you the latest research in AI, Data Science, Deep Learning, and Machine Learning with tutorials to improve your skills, keynotes from top experts, workshops on state-of-the-art topics and over 200 research presentations.

  Tags: ACM SIGKDD, COVID-19, Data Science, Deep Learning, KDD, KDD-2020, Machine Learning, Meetings, Research

• Top KDnuggets tweets, Aug 5-11: Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild - Aug 12, 2020.
  
  Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild; How to Evaluate the Performance of Your Machine Learning Model; Deep Learning Most Important Ideas - an excellent review

  Tags: Deep Learning, History, Model Performance, Photography, Top tweets

• Batch Normalization in Deep Neural Networks - Aug 7, 2020.
  
  Batch normalization is a technique for training very deep neural networks that normalizes the contributions to a layer for every mini batch.

  Tags: Deep Learning, Neural Networks, Normalization, Regularization

• Metrics to Use to Evaluate Deep Learning Object Detectors - Aug 6, 2020.
  
  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?

  Tags: Computer Vision, Deep Learning, Metrics, Object Detection

• I have a joke about … - Aug 1, 2020.
  
  I have a machine learning joke, but it is not performing as well on a new audience. We bring you a selection of the nerdy self-referential computer jokes that were popular on the web recently.

  Tags: Cartoon, Deep Learning, Humor

• Deep Learning for Signal Processing: What You Need to Know - Jul 27, 2020.
  
  Signal Processing is a branch of electrical engineering that models and analyzes data representations of physical events. It is at the core of the digital world. And now, signal processing is starting to make some waves in deep learning.

  Tags: Deep Learning, Neural Networks

• Is depth useful for self-attention? - Jul 27, 2020.
  
  Learn about recent research that is the first to explain a surprising phenomenon where in BERT/Transformer-like architectures, deepening the network does not seem to be better than widening (or, increasing the representation dimension). This empirical observation is in contrast to a fundamental premise in deep learning.

  Tags: Attention, BERT, Deep Learning, Research, Scalability, Transformer

• Labelling Data Using Snorkel - Jul 24, 2020.
  
  In this tutorial, we walk through the process of using Snorkel to generate labels for an unlabelled dataset. We will provide you examples of basic Snorkel components by guiding you through a real clinical application of Snorkel.

  Tags: Data Labeling, Data Science, Deep Learning, Machine Learning, NLP, Python

• Recurrent Neural Networks (RNN): Deep Learning for Sequential Data - Jul 20, 2020.
  
  Recurrent Neural Networks can be used for a number of ways such as detecting the next word/letter, forecasting financial asset prices in a temporal space, action modeling in sports, music composition, image generation, and more.

  Tags: Deep Learning, Python, Recurrent Neural Networks, Sequences, TensorFlow

• Math and Architectures of Deep Learning! - Jul 15, 2020.
  
  This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 50% with code kdarch50.

  Tags: Architecture, Deep Learning, Manning, Mathematics, PyTorch

• Auto Rotate Images Using Deep Learning - Jul 14, 2020.
  
  Follow these 5 simple steps to auto rotate images and get the right angle in human photos using computer vision.

  Tags: Computer Vision, Deep Learning, Face Detection, Image Processing

• Deep Learning in Finance: Is This The Future of the Financial Industry? - Jul 10, 2020.
  
  Get a handle on how deep learning is affecting the finance industry, and identify resources to further this understanding and increase your knowledge of the various aspects.

  Tags: Deep Learning, Finance

• Learn Python, ML, Deep Learning, Data Visualization and more in Italy with BIG DIVE - Jul 9, 2020.
  
  Do you want to learn or upgrade your data data proficiency and push your career forward? This year, under the umbrella of BIG DIVE, TOP-IX presents four full-time 1-week courses from beginner to advanced levels. Read more and register now.

  Tags: Courses, Deep Learning, Italy, Python

• Free MIT Courses on Calculus: The Key to Understanding Deep Learning - Jul 8, 2020.
  
  Calculus is the key to fully understanding how neural networks function. Go beyond a surface understanding of this mathematics discipline with these free course materials from MIT.

  Tags: Deep Learning, Free ebook, MIT, Neural Networks

• KDnuggets™ News 20:n26, Jul 8: Speed up Your Numpy and Pandas; A Layman’s Guide to Data Science; Getting Started with TensorFlow 2 - Jul 8, 2020.
  
  Speed up your Numpy and Pandas with NumExpr Package; A Layman's Guide to Data Science. Part 3: Data Science Workflow; Getting Started with TensorFlow 2; Feature Engineering in SQL and Python: A Hybrid Approach; Deploy Machine Learning Pipeline on AWS Fargate

  Tags: AWS, Data Science, Deep Learning, numpy, Pandas, Python, TensorFlow, Workflow

• PyTorch for Deep Learning: The Free eBook - Jul 7, 2020.
  
  For this week's free eBook, check out the newly released Deep Learning with PyTorch from Manning, made freely available via PyTorch's website for a limited time. Grab it now!

  Tags: Deep Learning, Free ebook, Neural Networks, PyTorch

• Generating cooking recipes using TensorFlow and LSTM Recurrent Neural Network: A step-by-step guide - Jul 3, 2020.
  
  A character-level LSTM (Long short-term memory) RNN (Recurrent Neural Network) is trained on ~100k recipes dataset using TensorFlow. The model suggested the recipes "Cream Soda with Onions", "Puff Pastry Strawberry Soup", "Zucchini flavor Tea", and "Salmon Mousse of Beef and Stilton Salad with Jalapenos". Yum!? Follow along this detailed guide with code to create your own recipe-generating chef.

  Tags: Cooking, Deep Learning, Humor, LSTM, Natural Language Generation, TensorFlow

• Getting Started with TensorFlow 2 - Jul 2, 2020.
  
  Learn about the latest version of TensorFlow with this hands-on walk-through of implementing a classification problem with deep learning, how to plot it, and how to improve its results.

  Tags: Advice, Beginners, Deep Learning, Python, Regularization, TensorFlow

• The Unreasonable Progress of Deep Neural Networks in Natural Language Processing (NLP) - Jun 29, 2020.
  
  Natural language processing has made incredible advances through advanced techniques in deep learning. Learn about these powerful models, and find how close (or far away) these approaches are to human-level understanding.

  Tags: Deep Learning, LSTM, NLP, Transfer Learning, Transformer, Trends

• Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron - Jun 25, 2020.
  
  DeepMind’s research shows how to understand the role of individual neurons in a neural network.

  Tags: Deep Learning, DeepMind, Learning, Neural Networks

• Tools to Spot Deepfakes and AI-Generated Text - Jun 23, 2020.
  
  The technologies that generate deepfake content is at the forefront of manipulating humans. While the research developing these algorithms is fascinating and will lead to powerful tools that enhance the way people create and work, in the wrong hands, these same tools drive misinformation at a scale we can't yet imagine. Stopping these bad actors using awesome tools is in your hands.

  Tags: AI, Deep Learning, Deepfakes, Natural Language Generation

• The Most Important Fundamentals of PyTorch you Should Know - Jun 18, 2020.
  
  PyTorch is a constantly developing deep learning framework with many exciting additions and features. We review its basic elements and show an example of building a simple Deep Neural Network (DNN) step-by-step.

  Tags: Deep Learning, Neural Networks, Python, PyTorch, Tensor

• Crop Disease Detection Using Machine Learning and Computer Vision - Jun 17, 2020.
  
  Computer vision has tremendous promise for improving crop monitoring at scale. We present our learnings from building such models for detecting stem and wheat rust in crops.

  Tags: Agriculture, Computer Vision, Deep Learning, fast.ai

• A Complete guide to Google Colab for Deep Learning - Jun 16, 2020.
  
  Google Colab is a widely popular cloud service for machine learning that features free access to GPU and TPU computing. Follow this detailed guide to help you get up and running fast to develop your next deep learning algorithms with Colab.

  Tags: Deep Learning, GitHub, Google Colab, GPU, Jupyter

• Math and Architectures of Deep Learning - Jun 11, 2020.
  
  This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 40% off Math and Architectures of Deep Learning with code nlkdarch40

  Tags: Deep Learning, Manning, Mathematics

• GPT-3, a giant step for Deep Learning and NLP? - Jun 9, 2020.
  
  Recently, OpenAI announced a new successor to their language model, GPT-3, that is now the largest model trained so far with 175 billion parameters. Training a language model this large has its merits and limitations, so this article covers some of its most interesting and important aspects.

  Tags: AI, Deep Learning, GPT-2, GPT-3, NLP, OpenAI

• Deep Learning for Detecting Pneumonia from X-ray Images - Jun 5, 2020.
  
  This article covers an end to end pipeline for pneumonia detection from X-ray images.

  Tags: Deep Learning, Healthcare, Image Recognition, Python

• Metis Webinar: Deep Learning Approaches to Forecasting - Jun 4, 2020.
  
  Metis Corporate Training is offering Deep Learning Approaches to Forecasting and Planning, a free webinar focusing on the intuition behind various deep learning approaches, and exploring how business leaders, data science managers, and decision makers can tackle highly complex models by asking the right questions, and evaluating the models with familiar tools.

  Tags: Deep Learning, Forecasting, Metis, Webinar

• KDnuggets™ News 20:n22, Jun 3: How to Think Like a Data Scientist; Six Ways For Data Scientists to Succeed at a Startup - Jun 3, 2020.
  
  Learn how to think like a Data Scientist; Read about 6 ways for a data scientist to succeed at a startup; Get a great and free new book on Deep Learning for Coders with fast.ai and PyTorch; check best GIS Courses in 2020; and more.

  Tags: Data Scientist, Deep Learning, fast.ai, GIS, PyTorch, Startups

• Deep Learning for Coders with fastai and PyTorch: The Free eBook - Jun 1, 2020.
  
  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.

  Tags: Deep Learning, fast.ai, Free ebook, Jeremy Howard, PyTorch

• Are Tera Operations Per Second (TOPS) Just hype? Or Dark AI Silicon in Disguise? - May 27, 2020.
  
  This article explains why TOPS isn’t as accurate a gauge as many people think, and discusses other criteria that should be considered when evaluating a solution to a real application.

  Tags: AI, Deep Learning, Hype, Neural Networks

• Deepmind’s Gaming Streak: The Rise of AI Dominance - May 27, 2020.
  
  There is still a long way to go before machine agents match overall human gaming prowess, but Deepmind’s gaming research focus has shown a clear progression of substantial progress.

  Tags: AI, AlphaGo, Deep Learning, DeepMind, Games, Reinforcement Learning

• KDnuggets™ News 20:n21, May 27: The Best NLP with Deep Learning Course is Free; Your First Machine Learning Web App - May 27, 2020.
  
  Also: Python For Everybody: The Free eBook; Complex logic at breakneck speed: Try Julia for data science; An easy guide to choose the right Machine Learning algorithm; Dataset Splitting Best Practices in Python; Appropriately Handling Missing Values for Statistical Modelling and Prediction

  Tags: Algorithms, Course, Deep Learning, Free ebook, Julia, Machine Learning, NLP, Python

• The Best NLP with Deep Learning Course is Free - May 22, 2020.
  
  Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.

  Tags: Course, Deep Learning, NLP, Stanford

• DeepMind’s Suggestions for Learning #AtHomeWithAI - May 13, 2020.
  
  DeepMind has been sharing resources for learning AI at home on their Twitter account. Check out a few of these suggestions here, and keep your eye on the #AtHomeWithAI hashtag for more.

  Tags: AI, Courses, Deep Learning, DeepMind, Neural Networks, Reinforcement Learning

• KDnuggets™ News 20:n19, May 13: Start Your Machine Learning Career in Quarantine; Will Machine Learning Engineers Exist in 10 Years? - May 13, 2020.
  
  Also: The Elements of Statistical Learning: The Free eBook; Explaining "Blackbox" Machine Learning Models: Practical Application of SHAP; What You Need to Know About Deep Reinforcement Learning; 5 Concepts You Should Know About Gradient Descent and Cost Function; Hyperparameter Optimization for Machine Learning Models

  Tags: Book, Career, Deep Learning, Explainability, Free ebook, Machine Learning, Machine Learning Engineer, Reinforcement Learning, SHAP

• What You Need to Know About Deep Reinforcement Learning - May 12, 2020.
  
  How does deep learning solve the challenges of scale and complexity in reinforcement learning? Learn how combining these approaches will make more progress toward the notion of Artificial General Intelligence.

  Tags: Deep Learning, Reinforcement Learning

• KDnuggets™ News 20:n18, May 6: Five Cool Python Libraries for Data Science; NLP Recipes: Best Practices - May 6, 2020.
  
  5 cool Python libraries for Data Science; NLP Recipes: Best Practices and Examples; Deep Learning: The Free eBook; Demystifying the AI Infrastructure Stack; and more.

  Tags: Deep Learning, GIS, NLP, Python

• Deep Learning: The Free eBook - May 4, 2020.
  
  "Deep Learning" is the quintessential book for understanding deep learning theory, and you can still read it freely online.

  Tags: Aaron Courville, Book, Deep Learning, Free ebook, Ian Goodfellow, Neural Networks, Yoshua Bengio

• LSTM for time series prediction - Apr 27, 2020.
  
  Learn how to develop a LSTM neural network with PyTorch on trading data to predict future prices by mimicking actual values of the time series data.

  Tags: Deep Learning, Forecasting, LSTM, Neural Networks, Recurrent Neural Networks, Time Series

• Fighting Coronavirus With AI: Improving Testing with Deep Learning and Computer Vision - Apr 22, 2020.
  
  This post will cover how testing is done for the coronavirus, why it's important in battling the pandemic, and how deep learning tools for medical imaging can help us improve the quality of COVID-19 testing.

  Tags: AI, Computer Vision, Coronavirus, COVID-19, Deep Learning, Healthcare

• Math and Architectures of Deep Learning - Apr 22, 2020.
  
  This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. You can save 40% off Math and Architectures of Deep Learning until May 13! Just enter the code nlkdarch40 at checkout when you buy from manning.com.

  Tags: Deep Learning, Manning, Mathematics

• KDnuggets™ News 20:n16, Apr 22: Scaling Pandas with Dask for Big Data; Dive Into Deep Learning: The Free eBook - Apr 22, 2020.
  
  4 Steps to ensure your AI/Machine Learning system survives COVID-19; State of the Machine Learning and AI Industry; A Key Missing Part of the Machine Learning Stack; 5 Papers on CNNs Every Data Scientist Should Read

  Tags: AI, Big Data, Coronavirus, COVID-19, Dask, Deep Learning, Free ebook, Machine Learning, Pandas

• Livestream Deep Learning World from your Home Office! - Apr 20, 2020.
  
  Livestream Deep Learning World Munich 2020 from the comfort and safety of your home on 11-12 May 2020.

  Tags: Deep Learning, PAW, Predictive Analytics World, Virtual Event

• The Double Descent Hypothesis: How Bigger Models and More Data Can Hurt Performance - Apr 20, 2020.
  
  OpenAI research shows a phenomenon that challenges both traditional statistical learning theory and conventional wisdom in machine learning practitioners.

  Tags: Deep Learning, Modeling, OpenAI

• Dive Into Deep Learning: The Free eBook - Apr 16, 2020.
  
  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.

  Tags: Book, Deep Learning, Free ebook, numpy

• How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals - Apr 13, 2020.
  
  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.

  Tags: Deep Learning, Drug Development, Pharma

• KDnuggets™ News 20:n13, Apr 1: Effective visualizations for pandemic storytelling; Machine learning for time series forecasting - Apr 1, 2020.
  
  This week, read about the power of effective visualizations for pandemic storytelling; see how (not) to use machine learning for time series forecasting; learn about a deep learning breakthrough: a sub-linear deep learning algorithm that does not need a GPU?; familiarize yourself with how to painlessly analyze your time series; check out what can we learn from the latest coronavirus trends; and... KDnuggets topics?!? Also, much more.

  Tags: Coronavirus, Data Visualization, Deep Learning, Distributed, Machine Learning, Python, Time Series

• Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU? - Mar 26, 2020.
  
  Deep Learning sits at the forefront of many important advances underway in machine learning. With backpropagation being a primary training method, its computational inefficiencies require sophisticated hardware, such as GPUs. Learn about this recent breakthrough algorithmic advancement with improvements to the backpropgation calculations on a CPU that outperforms large neural network training with a GPU.

  Tags: Algorithms, Deep Learning, GPU, Machine Learning

• The 4 Best Jupyter Notebook Environments for Deep Learning - Mar 19, 2020.
  
  Many cloud providers, and other third-party services, see the value of a Jupyter notebook environment which is why many companies now offer cloud hosted notebooks that are hosted on the cloud. Let's have a look at 3 such environments.

  Tags: Deep Learning, Google Colab, Jupyter, Python, Saturn Cloud

• Francois Chollet on the Future of Keras and Reinforce Conference - Feb 25, 2020.
  
  Ahead of Reinforce Conference in Budapest, we asked Francois Chollet, the creator of Keras, about Keras future, proposed developments, PyTorch, energy efficiency, and more. Listen to him in person in Budapest, April 6-7, and use code KDNuggets to save 15% on conference tickets.

  Tags: AutoKeras, Budapest, Climate Change, Deep Learning, Francois Chollet, Google, Keras, PyTorch, Reinforce, TensorFlow

• Audio Data Analysis Using Deep Learning with Python (Part 2) - Feb 25, 2020.
  
  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.

  Tags: Audio, Data Preprocessing, Deep Learning, Python

• Audio Data Analysis Using Deep Learning with Python (Part 1) - Feb 19, 2020.
  
  A brief introduction to audio data processing and genre classification using Neural Networks and python.

  Tags: Audio, Data Processing, Deep Learning, Python

• Deep Neural Networks - Feb 14, 2020.
  
  We examine the features and applications of a deep neural network.

  Tags: Applications, Deep Learning, Neural Networks, Robots

• Practical Hyperparameter Optimization - Feb 13, 2020.
  
  An introduction on how to fine-tune Machine and Deep Learning models using techniques such as: Random Search, Automated Hyperparameter Tuning and Artificial Neural Networks Tuning.

  Tags: Automated Machine Learning, AutoML, Deep Learning, Hyperparameter, Machine Learning, Optimization, Python, scikit-learn

• Top KDnuggets tweets, Feb 05-11: #SciPy 1.0: fundamental algorithms for scientific computing in #Python; Why is Data Science so popular? - Feb 12, 2020.
  
  Why is Data Science so Popular?; Visual Paper Summary: ALBERT (A Lite BERT); Uber Has Assembled One of the Most Impressive Open Source DL Stacks; Top #AI Influencers To Follow in 2020

  Tags: AI, Deep Learning, Influencers, SciPy, Top tweets, Uber

• Sharing your machine learning models through a common API - Feb 12, 2020.
  
  DEEPaaS API is a software component developed to expose machine learning models through a REST API. In this article we describe how to do it.

  Tags: API, Deep Learning, Machine Learning, Open Source, Python

• The Data Science Puzzle — 2020 Edition - Feb 7, 2020.
  
  The data science puzzle is once again re-examined through the relationship between several key concepts of the landscape, incorporating updates and observations since last time. Check out the results here.

  Tags: AI, Big Data, Data Mining, Data Science, Deep Learning, Machine Learning

• OpenAI is Adopting PyTorch… They Aren’t Alone - Jan 31, 2020.
  
  OpenAI is moving to PyTorch for the bulk of their research work. This might be a high-profile adoption, but it is far from the only such example.

  Tags: Adoption, AI, Deep Learning, OpenAI, PyTorch

• Amazon Gets Into the AutoML Race with AutoGluon: Some AutoML Architectures You Should Know About - Jan 30, 2020.
  
  Amazon, Microsoft, Salesforce, Waymo have produced some of the most innovative AutoML architectures in the market.

  Tags: Automated Machine Learning, AutoML, Deep Learning, Machine Learning

• Uber Has Been Quietly Assembling One of the Most Impressive Open Source Deep Learning Stacks in the Market - Jan 27, 2020.
  
  Many of the technologies used by Uber teams have been open sourced and received accolades from the machine learning community. Let’s look at some of my favorites.

  Tags: Deep Learning, Interpretability, NLP, Probability, Programming, Scalability, Uber

• Artificial Intelligence Books to Read in 2020 - Jan 21, 2020.
  
  Here are some AI-related books that I’ve read and recommend for you to add to your 2020 reading list!

  Tags: AI, Books, Deep Learning, Machine Learning

• Explaining Black Box Models: Ensemble and Deep Learning Using LIME and SHAP - Jan 21, 2020.
  
  This article will demonstrate explainability on the decisions made by LightGBM and Keras models in classifying a transaction for fraudulence, using two state of the art open source explainability techniques, LIME and SHAP.

  Tags: Deep Learning, Ensemble Methods, Explainability, LIME, SHAP

• Learn from Industry Leaders Facebook, Walmart, Lyft, eBay & More - Jan 20, 2020.
  
  The agenda for Deep Learning World 2020 in Las Vegas, May 31-Jun 4, has been released. Use code KDNUGGETS for a 15% discount on your ticket.

  Tags: Deep Learning, eBay, Facebook, Las Vegas, NV, PAW, Predictive Analytics World, Walmart

• Methods, challenges & applications of Deep Learning | Munich 11-12 May - Jan 16, 2020.
  
  Visit Deep Learning World, 11-12 May in Munich, to broaden your knowledge, deepen your understanding and discuss your questions with other Deep Learning experts!

  Tags: Deep Learning, Germany, Munich, PAW

• Disentangling disentanglement: Ideas from NeurIPS 2019 - Jan 15, 2020.
  
  This year’s NEURIPS-2019 Vancouver conference recently concluded and featured a dozen papers on disentanglement in deep learning. What is this idea and why is it so interesting in machine learning? This summary of these papers will give you initial insight in disentanglement as well as ideas on what you can explore next.

  Tags: AI, Deep Learning, Disentanglement, NeurIPS, Representation, Research

• Applying Occam’s razor to Deep Learning - Jan 10, 2020.
  
  Finding a deep learning model to perform well is an exciting feat. But, might there be other -- less complex -- models that perform just as well for your application? A simple complexity measure based on the statistical physics concept of Cascading Periodic Spectral Ergodicity (cPSE) can help us be computationally efficient by considering the least complex during model selection.

  Tags: Complexity, Deep Learning, Model Performance, Regularization

• Top 5 must-have Data Science skills for 2020 - Jan 8, 2020.
  
  The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.

  Tags: 2020 Predictions, Agile, Cloud Computing, Data Science Skills, Deep Learning, Deployment, GitHub, NLP

• Fighting Overfitting in Deep Learning - Dec 27, 2019.
  
  This post outlines an attack plan for fighting overfitting in neural networks.

  Tags: Deep Learning, Keras, Neural Networks, Overfitting, Python, Regularization, Transfer Learning

• 10 Best and Free Machine Learning Courses, Online - Dec 26, 2019.
  
  Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.

  Tags: Coursera, Data Science Education, Deep Learning, edX, Machine Learning, Online Education

• Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup - Dec 16, 2019.
  
  It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.

  Tags: 2020 Predictions, AI, Deep Learning, Healthcare, NLP, PyTorch, Reinforcement Learning, Review, Self-supervised Learning, TensorFlow, Xavier Amatriain

• What just happened in the world of AI? - Dec 12, 2019.
  
  The speed at which AI made advancements and news during 2019 makes it imperative now to step back and place these events into order and perspective. It's important to separate the interest that any one advancement initially attracts, from its actual gravity and its consequential influence on the field. This review unfolds the parallel threads of these AI stories over this year and isolates their significance.

  Tags: AI, AutoML, Bias, Deep Learning, DeepMind, GANs, GPT-2, NLP, OpenAI, Reinforcement Learning, Trends

• Scalable graph machine learning: a mountain we can climb? - Dec 10, 2019.
  
  Graph machine learning is a developing area of research that brings many complexities. One challenge that both fascinates and infuriates those working with graph algorithms is — scalability. We take a close look at scalability for graph machine learning methods covering what it is, what makes it difficult, and an example of a method that tackles it head-on.

  Tags: Deep Learning, Graph Analytics, Graph Databases, Machine Learning, Scalability

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020 - Dec 9, 2019.
  
  As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.

  Tags: 2020 Predictions, AI, Ajit Jaokar, Analytics, Andriy Burkov, Anima Anandkumar, Daniel Tunkelang, Data Science, Deep Learning, Machine Learning, Pedro Domingos, Research, Rosaria Silipo, Xavier Amatriain