Search results for deep learning

Found 2809 documents, 5920 searched:

• The Only Interview Prep Course You Need for Deep Learning

  Dive into the 50 most popular deep-learning questions to get you ready for your interview.

  https://www.kdnuggets.com/the-only-interview-prep-course-you-need-for-deep-learning

• Vector Database for LLMs, Generative AI, and Deep Learning

  Exploring the limitless possibilities of AI and making it context-aware.

  https://www.kdnuggets.com/vector-database-for-llms-generative-ai-and-deep-learning

• Free MIT Course: TinyML and Efficient Deep Learning Computing

  Curious about optimizing AI for everyday devices? Dive into the complete overview of MIT's TinyML and Efficient Deep Learning Computing course. Explore strategies to make AI smarter on small devices. Read the full article for an in-depth look!

  https://www.kdnuggets.com/free-mit-course-tinyml-and-efficient-deep-learning-computing

• Rust Burn Library for Deep Learning

  A new deep learning framework built entirely in Rust that aims to balance flexibility, performance, and ease of use for researchers, ML engineers, and developers.

  https://www.kdnuggets.com/rust-burn-library-for-deep-learning

• Introduction to Deep Learning Libraries: PyTorch and Lightning AI

  Simple explanation of PyTorch and Lightning AI.

  https://www.kdnuggets.com/introduction-to-deep-learning-libraries-pytorch-and-lightning-ai

• Neural Networks and Deep Learning: A Textbook (2nd Edition)

  The second edition of the book Neural Networks and Deep Learning is now available. This book covers both classical and modern models in deep learning. The book is intended to be a textbook for universities, and it covers the theoretical and algorithmic aspects of deep learning. The second edition is significantly expanded and covers many modern topics such as graph neural networks, adversarial learning, attention mechanisms, transformers, and large language models.

  https://www.kdnuggets.com/2023/07/aggarwal-neural-networks-deep-learning-textbook-2nd-edition.html

• Calculate Computational Efficiency of Deep Learning Models with FLOPs and MACs

  In this article we will learn about its definition, differences and how to calculate FLOPs and MACs using Python packages.

  https://www.kdnuggets.com/2023/06/calculate-computational-efficiency-deep-learning-models-flops-macs.html

• Deep Learning with R

  In this tutorial, learn how to perform a deep learning task in R.

  https://www.kdnuggets.com/2023/05/deep-learning-r.html

• Hydra Configs for Deep Learning Experiments

  This brief guide illustrates how to use the Hydra library for ML experiments, especially in the case of deep learning-related tasks, and why you need this tool to make your workflow easier.

  https://www.kdnuggets.com/2023/03/hydra-configs-deep-learning-experiments.html

• Multi-modal deep learning in less than 15 lines of code

  Learn how to easily build, iterate and deploy a state-of-the-art deep learning model to predict customer ratings with a declarative approach to machine learning.

  https://www.kdnuggets.com/2023/01/predibase-multi-modal-deep-learning-less-15-lines-code.html

• A Solid Plan for Learning Data Science, Machine Learning, and Deep Learning

  Check out this solid plan for learning Data Science, Machine Learning, and Deep Learning. The entire plan is currently available at no cost to KDnuggets readers.

  https://www.kdnuggets.com/2023/01/mwiti-solid-plan-learning-data-science-machine-learning-deep-learning.html

• 15 More Free Machine Learning and Deep Learning Books

  Check out this second list of 15 FREE ebooks for learning machine learning and deep learning.

  https://www.kdnuggets.com/2022/11/15-free-machine-learning-deep-learning-books.html

• Getting Deep Learning working in the wild: A Data-Centric Course

  Data-centric learning resources are somewhat scattered today, and that’s why we developed a new Data Centric Deep Learning course on the co:rise education platform. It is an introduction to a set of approaches and best practices, for people who are trying to do deep learning in the wild.

  https://www.kdnuggets.com/2022/11/corise-deep-learning-wild-data-centric-course.html

• KDnuggets News, November 2: The Current State of Data Science Careers • 15 Free Machine Learning and Deep Learning Books

  The Current State of Data Science Careers • 15 Free Machine Learning and Deep Learning Books • How to Make Python Code Run Incredibly Fast • Machine Learning on the Edge • Don't Become a Commoditized Data Scientist

  https://www.kdnuggets.com/2022/n43.html

• The Gap Between Deep Learning and Human Cognitive Abilities

  How do we bridge this gap between deep learning and human cognitive ability?

  https://www.kdnuggets.com/2022/10/gap-deep-learning-human-cognitive-abilities.html

• 15 Free Machine Learning and Deep Learning Books

  Check out this list of 15 FREE ebooks for learning machine learning and deep learning.

  https://www.kdnuggets.com/2022/10/15-free-machine-learning-deep-learning-books.html

• KDnuggets News, October 19: 3 Valuable Skills That Have Doubled My Income as a Data Scientist • The Complete Free PyTorch Course for Deep Learning

  3 Valuable Skills That Have Doubled My Income as a Data Scientist • The Complete Free PyTorch Course for Deep Learning • 7 Free Platforms for Building a Strong Data Science Portfolio • Mathematics for Machine Learning: The Free eBook • 25 Advanced SQL Interview Questions for Data Scientists

  https://www.kdnuggets.com/2022/n41.html

• The Complete Free PyTorch Course for Deep Learning

  Do you want to learn PyTorch for machine learning and deep learning? Check out this 24 hour long video course with accompanying notes and courseware for free. Did I mention it's free?

  https://www.kdnuggets.com/2022/10/complete-free-pytorch-course-deep-learning.html

• Put your deep learning skills with R into action!

  Sponsored Post     Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow Read more »

  https://www.kdnuggets.com/2022/08/manning-deep-learning-skills-r-action.html

• Practical Deep Learning from fast.ai is Back!

  Looking for a great course to go from machine learning zero to hero quickly? fast.ai has released the latest version of Practical Deep Learning For Coders. And it won't cost you a thing.

  https://www.kdnuggets.com/2022/07/practical-deep-learning-fastai-2022.html

• Free Artificial Intelligence And Deep Learning Crash Course

  Deep learning forms the backbone of modern day artificial intelligence. Learn more about the important aspects of this connection with this freely available course.

  https://www.kdnuggets.com/2022/07/free-artificial-intelligence-deep-learning-crash-course.html

• Bounding Box Deep Learning: The Future of Video Annotation

  Bounding box deep learning has several benefits that make it well-suited for video annotation.

  https://www.kdnuggets.com/2022/07/bounding-box-deep-learning-future-video-annotation.html

• Deep Learning Key Terms, Explained

  Gain a beginner's perspective on artificial neural networks and deep learning with this set of 14 straight-to-the-point related key concept definitions.

  https://www.kdnuggets.com/2016/10/deep-learning-key-terms-explained.html

• How Activation Functions Work in Deep Learning

  Check out a this article for a better understanding of activation functions.

  https://www.kdnuggets.com/2022/06/activation-functions-work-deep-learning.html

• Deep Learning For Compliance Checks: What’s New?

  By implementing the different NLP techniques into the production processes, compliance departments can maintain detailed checks and keep up with regulator demands.

  https://www.kdnuggets.com/2022/05/deep-learning-compliance-checks-new.html

• Getting Deep Learning working in the wild: A Data-Centric Course

  Data-centric learning resources are somewhat scattered today, and that’s why we developed a new Data Centric Deep Learning course on the co:rise education platform. It is an introduction to a set of approaches and best practices, for people who are trying to do deep learning in the wild.

  https://www.kdnuggets.com/2022/04/corise-deep-learning-wild-data-centric-course.html

• A New Way of Managing Deep Learning Datasets

  Create, version-control, query, and visualize image, audio, and video datasets using Hub 2.0 by Activeloop.

  https://www.kdnuggets.com/2022/03/new-way-managing-deep-learning-datasets.html

• Free MIT Courses on Calculus: The Key to Understanding Deep Learning

  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.

  https://www.kdnuggets.com/2020/07/free-mit-courses-calculus-key-deep-learning.html

• Deep Learning with Python: Second Edition by François Chollet

  Now in print! New edition of the bestselling original by François Chollet.

  https://www.kdnuggets.com/2022/01/manning-deep-learning-python-second-edition-francois-chollet.html

• Learn Deep Learning by Building 15 Neural Network Projects in 2022

  Here are 15 neural network projects you can take on in 2022 to build your skills, your know-how, and your portfolio.

  https://www.kdnuggets.com/2022/01/15-neural-network-projects-build-2022.html

• Tips & Tricks of Deploying Deep Learning Webapp on Heroku Cloud

  Learn model deployment issues and solutions on deploying a TensorFlow-based image classifier Streamlit app on a Heroku server.

  https://www.kdnuggets.com/2021/12/tips-tricks-deploying-dl-webapps-heroku.html

• Inside DeepMind’s New Efforts to Use Deep Learning to Advance Mathematics

  Using deep learning techniques can help mathematicians develop intuitions about the toughest problems in the field.

  https://www.kdnuggets.com/2021/12/inside-deepmind-new-efforts-deep-learning-advance-mathematics.html

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2021 and Key Trends for 2022

  2021 has almost come and gone. We saw some standout advancements in AI, Analytics, Machine Learning, Data Science, Deep Learning Research this past year, and the future, starting with 2022, looks bright. As per KDnuggets tradition, our collection of experts have contributed their insights on the matter. Read on to find out more.

  https://www.kdnuggets.com/2021/12/developments-predictions-ai-machine-learning-data-science-research.html

• Using Datawig, an AWS Deep Learning Library for Missing Value Imputation

  A lot of missing values in the dataset can affect the quality of prediction in the long run. Several methods can be used to fill the missing values and Datawig is one of the most efficient ones.

  https://www.kdnuggets.com/2021/12/datawig-aws-deep-learning-library-missing-value-imputation.html

• On-Device Deep Learning: PyTorch Mobile and TensorFlow Lite

  PyTorch and TensorFlow are the two leading AI/ML Frameworks. In this article, we take a look at their on-device counterparts PyTorch Mobile and TensorFlow Lite and examine them more deeply from the perspective of someone who wishes to develop and deploy models for use on mobile platforms.

  https://www.kdnuggets.com/2021/11/on-device-deep-learning-pytorch-mobile-tensorflow-lite.html

• Deep Learning on your phone: PyTorch C++ API for use on Mobile Platforms

  The PyTorch Deep Learning framework has a C++ API for use on mobile platforms. This article shows an end-to-end demo of how to write a simple C++ application with Deep Learning capabilities using the PyTorch C++ API such that the same code can be built for use on mobile platforms (both Android and iOS).

  https://www.kdnuggets.com/2021/11/deep-learning-mobile-phone-pytorch-c-api.html

• What Comes After HDF5? Seeking a Data Storage Format for Deep Learning

  In this article we are discussing that HDF5 is one of the most popular and reliable formats for non-tabular, numerical data. But this format is not optimized for deep learning work. This article suggests what kind of ML native data format should be to truly serve the needs of modern data scientists.

  https://www.kdnuggets.com/2021/11/after-hdf5-data-storage-format-deep-learning.html

• A Breakdown of Deep Learning Frameworks

  Deep Learning continues to evolve as one of the most powerful techniques in the AI toolbox. Many software packages exist today to support the development of models, and we highlight important options available with key qualities and differentiators to help you select the most appropriate for your needs.

  https://www.kdnuggets.com/2021/09/a-breakdown-deep-learning-frameworks.html

• KDnuggets™ News 21:n36, Sep 22: The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python

  The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python; Introduction to Automated Machine Learning; How to be a Data Scientist without a STEM degree; What Is The Real Difference Between Data Engineers and Data Scientists?

  https://www.kdnuggets.com/2021/n36.html

• The Machine & Deep Learning Compendium Open Book">The Machine & Deep Learning Compendium Open Book

  After years in the making, this extensive and comprehensive ebook resource is now available and open for data scientists and ML engineers. Learn from and contribute to this tome of valuable information to support all your work in data science from engineering to strategy to management.

  https://www.kdnuggets.com/2021/09/machine-deep-learning-open-book.html

• Text Preprocessing Methods for Deep Learning

  While the preprocessing pipeline we are focusing on in this post is mainly centered around Deep Learning, most of it will also be applicable to conventional machine learning models too.

  https://www.kdnuggets.com/2021/09/text-preprocessing-methods-deep-learning.html

• 8 Deep Learning Project Ideas for Beginners">8 Deep Learning Project Ideas for Beginners

  Have you studied Deep Learning techniques, but never worked on a useful project? Here, we highlight eight deep learning project ideas for beginners that will help you sharpen your skills and boost your resume.

  https://www.kdnuggets.com/2021/09/8-deep-learning-project-ideas-beginners.html

• GPU-Powered Data Science (NOT Deep Learning) with RAPIDS">GPU-Powered Data Science (NOT Deep Learning) with RAPIDS

  How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.

  https://www.kdnuggets.com/2021/08/gpu-powered-data-science-deep-learning-rapids.html

• Not Only for Deep Learning: How GPUs Accelerate Data Science & Data Analytics">Not Only for Deep Learning: How GPUs Accelerate Data Science & Data Analytics

  Modern AI/ML systems’ success has been critically dependent on their ability to process massive amounts of raw data in a parallel fashion using task-optimized hardware. Can we leverage the power of GPU and distributed computing for regular data processing jobs too?

  https://www.kdnuggets.com/2021/07/deep-learning-gpu-accelerate-data-science-data-analytics.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 5

  Training efficient deep learning models with any software tool is nothing without an infrastructure of robust and performant compute power. Here, current software and hardware ecosystems are reviewed that you might consider in your development when the highest performance possible is needed.

  https://www.kdnuggets.com/2021/07/high-performance-deep-learning-part5.html

• 7 Open Source Libraries for Deep Learning Graphs

  In this article we’ll go through 7 up-and-coming open source libraries for graph deep learning, ranked in order of increasing popularity.

  https://www.kdnuggets.com/2021/07/7-open-source-libraries-deep-learning-graphs.html

• Geometric foundations of Deep Learning">Geometric foundations of Deep Learning

  Geometric Deep Learning is an attempt for geometric unification of a broad class of machine learning problems from the perspectives of symmetry and invariance. These principles not only underlie the breakthrough performance of convolutional neural networks and the recent success of graph neural networks but also provide a principled way to construct new types of problem-specific inductive biases.

  https://www.kdnuggets.com/2021/07/geometric-foundations-deep-learning.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 4

  With the right software, hardware, and techniques at your fingertips, your capability to effectively develop high-performing models now hinges on leveraging automation to expedite the experimental process and building with the most efficient model architectures for your data.

  https://www.kdnuggets.com/2021/07/high-performance-deep-learning-part4.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 3

  Now that you are ready to efficiently build advanced deep learning models with the right software and hardware tools, the techniques involved in implementing such efforts must be explored to improve model quality and obtain the performance that your organization desires.

  https://www.kdnuggets.com/2021/07/high-performance-deep-learning-part3.html

• Computational Complexity of Deep Learning: Solution Approaches

  Why has deep learning been so successful? What is the fundamental reason that deep learning can learn from big data? Why cannot traditional ML learn from the large data sets that are now available for different tasks as efficiently as deep learning can?

  https://www.kdnuggets.com/2021/06/computational-complexity-deep-learning-solution-approaches.html

• High-Performance Deep Learning: How to train smaller, faster, and better models – Part 2

  As your organization begins to consider building advanced deep learning models with efficiency in mind to improve the power delivered through your solutions, the software and hardware tools required for these implementations are foundational to achieving high-performance.

  https://www.kdnuggets.com/2021/06/high-performance-deep-learning-part2.html

• High Performance Deep Learning, Part 1

  Advancing deep learning techniques continue to demonstrate incredible potential to deliver exciting new AI-enhanced software and systems. But, training the most powerful models is expensive--financially, computationally, and environmentally. Increasing the efficiency of such models will have profound impacts in many ways, so developing future models with this intension in mind will only help to further expand the reach, applicability, and value of what deep learning has to offer.

  https://www.kdnuggets.com/2021/06/efficiency-deep-learning-part1.html

• How to speed up a Deep Learning Language model by almost 50X at half the cost

  In this blog post, we show how to accelerate fine-tuning the ALBERT language model while also reducing costs by using Determined’s built-in support for distributed training with AWS spot instances.

  https://www.kdnuggets.com/2021/06/determined-ai-speed-up-deep-learning-language-model.html

• Deep Learning Recommendation Models (DLRM): A Deep Dive

  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.

  https://www.kdnuggets.com/2021/04/deep-learning-recommendation-models-dlrm-deep-dive.html

• How to deploy Machine Learning/Deep Learning models to the web">How to deploy Machine Learning/Deep Learning models to the web

  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.

  https://www.kdnuggets.com/2021/04/deploy-machine-learning-models-to-web.html

• Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall">Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall

  This tutorial discusses the confusion matrix, and how the precision, recall and accuracy are calculated, and how they relate to evaluating deep learning models.

  https://www.kdnuggets.com/2021/02/evaluating-deep-learning-models-confusion-matrix-accuracy-precision-recall.html

• Deep Learning-based Real-time Video Processing

  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.

  https://www.kdnuggets.com/2021/02/deep-learning-based-real-time-video-processing.html

• Deep learning doesn’t need to be a black box">Deep learning doesn’t need to be a black box

  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.

  https://www.kdnuggets.com/2021/02/deep-learning-not-black-box.html

• 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

• Building a Deep Learning Based Reverse Image Search">Building a Deep Learning Based Reverse Image Search

  Following the journey from unstructured data to content based image retrieval.

  https://www.kdnuggets.com/2021/01/deep-learning-based-reverse-image-search.html

• Attention mechanism in Deep Learning, Explained

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

  https://www.kdnuggets.com/2021/01/attention-mechanism-deep-learning-explained.html

• DeepMind’s MuZero is One of the Most Important Deep Learning Systems Ever Created">DeepMind’s MuZero is One of the Most Important Deep Learning Systems Ever Created

  MuZero takes a unique approach to solve the problem of planning in deep learning models.

  https://www.kdnuggets.com/2021/01/deepmind-muzero-important-deep-learning-systems.html

• How to Create Custom Real-time Plots in Deep Learning

  How to generate real-time visualizations of custom metrics while training a deep learning model using Keras callbacks.

  https://www.kdnuggets.com/2020/12/create-custom-real-time-plots-deep-learning.html

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021">AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021

  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.

  https://www.kdnuggets.com/2020/12/predictions-ai-machine-learning-data-science-research.html

• Learn Deep Learning with this Free Course from Yann LeCun">Learn Deep Learning with this Free Course from Yann LeCun

  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.

  https://www.kdnuggets.com/2020/11/learn-deep-learning-free-course-yann-lecun.html

• Adversarial Examples in Deep Learning – A Primer

  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.

  https://www.kdnuggets.com/2020/11/adversarial-examples-deep-learning-primer.html

• Facebook Open Sourced New Frameworks to Advance Deep Learning Research">Facebook Open Sourced New Frameworks to Advance Deep Learning Research

  Polygames, PyTorch3D and HiPlot are the new additions to Facebook’s open source deep learning stack.

  https://www.kdnuggets.com/2020/11/facebook-open-source-frameworks-advance-deep-learning-research.html

• Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision">Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision

  This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.

  https://www.kdnuggets.com/2020/11/top-python-libraries-deep-learning-natural-language-processing-computer-vision.html

• Top 5 Free Machine Learning and Deep Learning eBooks Everyone should read">Top 5 Free Machine Learning and Deep Learning eBooks Everyone should read

  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.

  https://www.kdnuggets.com/2020/11/top-5-free-machine-learning-deep-learning-ebooks.html

• Building Deep Learning Projects with fastai — From Model Training to Deployment

  A getting started guide to develop computer vision application with fastai.

  https://www.kdnuggets.com/2020/11/building-deep-learning-projects-fastai-model-training-deployment.html

• Microsoft and Google Open Sourced These Frameworks Based on Their Work Scaling Deep Learning Training

  Google and Microsoft have recently released new frameworks for distributed deep learning training.

  https://www.kdnuggets.com/2020/11/microsoft-google-open-sourced-frameworks-scaling-deep-learning-training.html

• Deep Learning for Virtual Try On Clothes – Challenges and Opportunities

  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.

  https://www.kdnuggets.com/2020/10/deep-learning-virtual-try-clothes.html

• 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

• Implementing a Deep Learning Library from Scratch in Python">Implementing a Deep Learning Library from Scratch in Python

  A beginner’s guide to understanding the fundamental building blocks of deep learning platforms.

  https://www.kdnuggets.com/2020/09/implementing-deep-learning-library-scratch-python.html

• 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

• A Deep Learning Dream: Accuracy and Interpretability in a Single Model

  IBM Research believes that you can improve the accuracy of interpretable models with knowledge learned in pre-trained models.

  https://www.kdnuggets.com/2020/09/deep-learning-dream-accuracy-interpretability-single-model.html

• Must-read NLP and Deep Learning articles for Data Scientists">Must-read NLP and Deep Learning articles for Data Scientists

  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.

  https://www.kdnuggets.com/2020/08/must-read-nlp-deep-learning-articles.html

• 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

• Deep Learning for Signal Processing: What You Need to Know

  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.

  https://www.kdnuggets.com/2020/07/deep-learning-signal-processing.html

• Recurrent Neural Networks (RNN): Deep Learning for Sequential Data

  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.

  https://www.kdnuggets.com/2020/07/rnn-deep-learning-sequential-data.html

• Math and Architectures of Deep Learning!

  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.

  https://www.kdnuggets.com/2020/07/manning-math-architectures-deep-learning.html

• Auto Rotate Images Using Deep Learning

  Follow these 5 simple steps to auto rotate images and get the right angle in human photos using computer vision.

  https://www.kdnuggets.com/2020/07/auto-rotate-images-deep-learning.html

• Deep Learning in Finance: Is This The Future of the Financial Industry?

  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.

  https://www.kdnuggets.com/2020/07/deep-learning-finance-future-financial-industry.html

• PyTorch for Deep Learning: The Free eBook

  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!

  https://www.kdnuggets.com/2020/07/pytorch-deep-learning-free-ebook.html

• A Complete guide to Google Colab for Deep Learning">A Complete guide to Google Colab for Deep Learning

  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.

  https://www.kdnuggets.com/2020/06/google-colab-deep-learning.html

• Math and Architectures of Deep Learning

  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

  https://www.kdnuggets.com/2020/06/manning-math-architectures-deep-learning.html

• Top May Stories: The Best NLP with Deep Learning Course is Free

  Also: How to Think Like a Data Scientist; Python For Everybody: The Free eBook; Automated Machine Learning: The Free eBook.

  https://www.kdnuggets.com/2020/06/top-stories-2020-may.html

• GPT-3, a giant step for Deep Learning and NLP?

  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.

  https://www.kdnuggets.com/2020/06/gpt-3-deep-learning-nlp.html

• Deep Learning for Detecting Pneumonia from X-ray Images">Deep Learning for Detecting Pneumonia from X-ray Images

  This article covers an end to end pipeline for pneumonia detection from X-ray images.

  https://www.kdnuggets.com/2020/06/deep-learning-detecting-pneumonia-x-ray-images.html

• 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

• Top Stories, May 18-24: The Best NLP with Deep Learning Course is Free

  Also: Automated Machine Learning: The Free eBook; Sparse Matrix Representation in Python; Build and deploy your first machine learning web app; Complex logic at breakneck speed: Try Julia for data science

  https://www.kdnuggets.com/2020/05/top-news-week-0518-0524.html

• The Best NLP with Deep Learning Course is Free">The Best NLP with Deep Learning Course is Free

  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.

  https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html

• Deep Learning: The Free eBook">Deep Learning: The Free eBook

  "Deep Learning" is the quintessential book for understanding deep learning theory, and you can still read it freely online.

  https://www.kdnuggets.com/2020/05/deep-learning-free-ebook.html

• Fighting Coronavirus With AI: Improving Testing with Deep Learning and Computer Vision

  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.

  https://www.kdnuggets.com/2020/04/fighting-coronavirus-ai-improving-testing-deep-learning-computer-vision.html

• Math and Architectures of Deep Learning

  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.

  https://www.kdnuggets.com/2020/04/manning-math-architectures-deep-learning.html

• 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

• 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

• 3 Reasons to Use Random Forest® Over a Neural Network: Comparing Machine Learning versus Deep Learning

  Both the random forest algorithm and Neural Networks are different techniques that learn differently but can be used in similar domains. Why would you use one over the other?

  https://www.kdnuggets.com/2020/04/3-reasons-random-forest-neural-network-comparison.html

• Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?

  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.

  https://www.kdnuggets.com/2020/03/deep-learning-breakthrough-sub-linear-algorithm-no-gpu.html

• The 4 Best Jupyter Notebook Environments for Deep Learning

  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.

  https://www.kdnuggets.com/2020/03/4-best-jupyter-notebook-environments-deep-learning.html

• Topic: Deep Learning

  This page features most recent and most popular posts on Deep Learning.

  https://www.kdnuggets.com/topic/deep-learning

• 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

• 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

• Uber Has Been Quietly Assembling One of the Most Impressive Open Source Deep Learning Stacks in the Market

  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.

  https://www.kdnuggets.com/2020/01/uber-quietly-assembling-impressive-open-source-deep-learning.html

• Explaining Black Box Models: Ensemble and Deep Learning Using LIME and SHAP

  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.

  https://www.kdnuggets.com/2020/01/explaining-black-box-models-ensemble-deep-learning-lime-shap.html

• Applying Occam’s razor to Deep Learning

  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.

  https://www.kdnuggets.com/2020/01/occams-razor-deep-learning.html

• Fighting Overfitting in Deep Learning

  This post outlines an attack plan for fighting overfitting in neural networks.

  https://www.kdnuggets.com/2019/12/fighting-overfitting-deep-learning.html

• AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020">AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020

  We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.

  https://www.kdnuggets.com/2019/12/predictions-ai-machine-learning-data-science-technology.html

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020">AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020

  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.

  https://www.kdnuggets.com/2019/12/predictions-ai-machine-learning-data-science-research.html

• Enabling the Deep Learning Revolution

  Deep learning models are revolutionizing the business and technology world with jaw-dropping performances in one application area after another. Read this post on some of the numerous composite technologies which allow deep learning its complex nonlinearity.

  https://www.kdnuggets.com/2019/12/enabling-deep-learning-revolution.html

• Deep Learning for Image Classification with Less Data

  In this blog I will be demonstrating how deep learning can be applied even if we don’t have enough data.

  https://www.kdnuggets.com/2019/11/deep-learning-image-classification-less-data.html

• Research Guide for Depth Estimation with Deep Learning

  In this guide, we’ll look at papers aimed at solving the problems of depth estimation using deep learning.

  https://www.kdnuggets.com/2019/11/research-guide-depth-estimation-deep-learning.html

• Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch">Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch

  The new release of PyTorch includes some impressive open source projects for deep learning researchers and developers.

  https://www.kdnuggets.com/2019/11/facebook-quietly-open-sourcing-amazing-deep-learning-capabilities-pytorch.html

• 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

• Activation maps for deep learning models in a few lines of code">Activation maps for deep learning models in a few lines of code

  We illustrate how to show the activation maps of various layers in a deep CNN model with just a couple of lines of code.

  https://www.kdnuggets.com/2019/10/activation-maps-deep-learning-models-lines-code.html

• 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

• 5 Step Guide to Scalable Deep Learning Pipelines with d6tflow

  How to turn a typical pytorch script into a scalable d6tflow DAG for faster research & development.

  https://www.kdnuggets.com/2019/09/5-step-guide-scalable-deep-learning-pipelines-d6tflow.html

• A 2019 Guide to Speech Synthesis with Deep Learning

  In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.

  https://www.kdnuggets.com/2019/09/2019-guide-speech-synthesis-deep-learning.html

• Deep Learning Next Step: Transformers and Attention Mechanism">Deep Learning Next Step: Transformers and Attention Mechanism

  With the pervasive importance of NLP in so many of today's applications of deep learning, find out how advanced translation techniques can be further enhanced by transformers and attention mechanisms.

  https://www.kdnuggets.com/2019/08/deep-learning-transformers-attention-mechanism.html

• 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

• Deep Learning for NLP: Creating a Chatbot with Keras!">Deep Learning for NLP: Creating a Chatbot with Keras!

  Learn how to use Keras to build a Recurrent Neural Network and create a Chatbot! Who doesn’t like a friendly-robotic personal assistant?

  https://www.kdnuggets.com/2019/08/deep-learning-nlp-creating-chatbot-keras.html

• Top KDnuggets tweets, Aug 07-13: Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners To Follow

  Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners & Innovators You Should Be Following; Knowing Your Neighbours: Machine Learning on Graphs.

  https://www.kdnuggets.com/2019/08/top-tweets-aug07-13.html

• Deep Learning for NLP: ANNs, RNNs and LSTMs explained!">Deep Learning for NLP: ANNs, RNNs and LSTMs explained!

  Learn about Artificial Neural Networks, Deep Learning, Recurrent Neural Networks and LSTMs like never before and use NLP to build a Chatbot!

  https://www.kdnuggets.com/2019/08/deep-learning-nlp-explained.html

• 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

• Easily Deploy Deep Learning Models in Production

  Getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail. This blog explores how to navigate these challenges.

  https://www.kdnuggets.com/2019/08/nvidia-deploy-deep-learning-models-production.html

• How a simple mix of object-oriented programming can sharpen your deep learning prototype

  By mixing simple concepts of object-oriented programming, like functionalization and class inheritance, you can add immense value to a deep learning prototyping code.

  https://www.kdnuggets.com/2019/08/simple-mix-object-oriented-programming-sharpen-deep-learning-prototype.html

• Bayesian deep learning and near-term quantum computers: A cautionary tale in quantum machine learning">Bayesian deep learning and near-term quantum computers: A cautionary tale in quantum machine learning

  This blog post is an overview of quantum machine learning written by the author of the paper Bayesian deep learning on a quantum computer. In it, we explore the application of machine learning in the quantum computing space. The authors of this paper hope that the results of the experiment help influence the future development of quantum machine learning.

  https://www.kdnuggets.com/2019/07/bayesian-deep-learning-near-term-quantum-computers.html

• Scaling a Massive State-of-the-art Deep Learning Model in Production

  A new NLP text writing app based on OpenAI's GPT-2 aims to write with you -- whenever you ask. Find out how the developers setup and deployed their model into production from an engineer working on the team.

  https://www.kdnuggets.com/2019/07/scaling-massive-deep-learning-model-production.html

• An Overview of Human Pose Estimation with Deep Learning

  Human Pose Estimation is one of the main research areas in computer vision. The reason for its importance is the abundance of applications that can benefit from such a technology. Here's an introduction to the different techniques used in Human Pose Estimation based on Deep Learning.

  https://www.kdnuggets.com/2019/06/human-pose-estimation-deep-learning.html

• PySyft and the Emergence of Private Deep Learning

  PySyft is an open-source framework that enables secured, private computations in deep learning, by combining federated learning and differential privacy in a single programming model integrated into different deep learning frameworks such as PyTorch, Keras or TensorFlow.

  https://www.kdnuggets.com/2019/06/pysyft-emergence-deep-learning.html