Search results for deep learning

Found 2810 documents, 5922 searched:

• The Current State of Automated Machine Learning

  What is automated machine learning (AutoML)? Why do we need it? What are some of the AutoML tools that are available? What does its future hold? Read this article for answers to these and other AutoML questions.

  https://www.kdnuggets.com/2017/01/current-state-automated-machine-learning.html

• The Most Popular Language For Machine Learning and Data Science Is …">The Most Popular Language For Machine Learning and Data Science Is …

  When it comes to choosing programming language for Data Analytics projects or job prospects, people have different opinions depending on their career backgrounds and domains they worked in. Here is the analysis of data from indeed.com with respect to choice of programming language for machine learning and data science.

  https://www.kdnuggets.com/2017/01/most-popular-language-machine-learning-data-science.html

• Cartoon: When Self-Driving Car + Machine Learning takes you too far …

  What can happen in the not too distant future when advanced technologies like a Self-Driving car and Machine Learning Recommendations Engine are combined ...

  https://www.kdnuggets.com/2017/01/cartoon-self-driving-car-machine-learning-recommendations.html

• How To Stay Competitive In Machine Learning Business

  To stay competitive in machine learning business, you have to be superior than your rivals and not the best possible – says one of the leading machine learning expert. Simple rules are defined here to make that happen. Let’s see how.

  https://www.kdnuggets.com/2017/01/stay-competitive-machine-learning-business.html

• Generative Adversarial Networks – Hot Topic in Machine Learning

  What is Generative Adversarial Networks (GAN) ? A very illustrative explanation of GAN is presented here with simple examples like predicting next frame in video sequence or predicting next word while typing in google search.

  https://www.kdnuggets.com/2017/01/generative-adversarial-networks-hot-topic-machine-learning.html

• Ten Myths About Machine Learning, by Pedro Domingos

  Myths on artificial intelligence and machine learning abound. Noted expert Pedro Domingos identifies and refutes a number of these myths, of both the pessimistic and optimistic variety.

  https://www.kdnuggets.com/2017/01/domingos-ten-myths-machine-learning.html

• Machine Learning and Cyber Security Resources">Machine Learning and Cyber Security Resources

  An overview of useful resources about applications of machine learning and data mining in cyber security, including important websites, papers, books, tutorials, courses, and more.
   
   

  https://www.kdnuggets.com/2017/01/machine-learning-cyber-security.html

• 5 Machine Learning Projects You Can No Longer Overlook, January">5 Machine Learning Projects You Can No Longer Overlook, January

  There are a lot of popular machine learning projects out there, but many more that are not. Which of these are actively developed and worth checking out? Here is an offering of 5 such projects, the most recent in an ongoing series.
   
   

  https://www.kdnuggets.com/2017/01/five-machine-learning-projects-cant-overlook-january.html

• Academic, Research Positions in Big Data, Data Mining, Data Science, Machine Learning

    To add here a short entry for an academic or research position related to AI, Big Data, Data Science, or Machine Learning, email 5 Read more »

  https://www.kdnuggets.com/academic/index.html

• Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017">Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017

  As 2016 comes to a close and we prepare for a new year, check out the final instalment in our "Main Developments in 2016 and Key Trends in 2017" series, where experts weigh in with their opinions.

  https://www.kdnuggets.com/2016/12/machine-learning-artificial-intelligence-main-developments-2016-key-trends-2017.html

• Top 2016 KDnuggets Stories: Must-Know Data Science Interview Q&A, 10 Algorithms Machine Learning Engineers Need to Know

  Also 20 Questions to Detect Fake Data Scientists; Software used for Analytics, Data Science, Machine Learning projects; Top Algorithms and Methods Used by Data Scientists

  https://www.kdnuggets.com/2016/12/top-2016-kdnuggets-stories.html

• 50+ Data Science, Machine Learning Cheat Sheets, updated">50+ Data Science, Machine Learning Cheat Sheets, updated

  Gear up to speed and have concepts and commands handy in Data Science, Data Mining, and Machine learning algorithms with these cheat sheets covering R, Python, Django, MySQL, SQL, Hadoop, Apache Spark, Matlab, and Java.

  https://www.kdnuggets.com/2016/12/data-science-machine-learning-cheat-sheets-updated.html

• Top 10 Amazon Books in Artificial Intelligence & Machine Learning, 2016 Edition

  Given the ongoing explosion in interest for all things Data Science, Artificial Intelligence, Machine Learning, etc., we have updated our Amazon top books lists from last year. Here are the 10 most popular titles in the AI & Machine Learning category.

  https://www.kdnuggets.com/2016/11/top-10-amazon-books-ai-machine-learning.html

• Introduction to Machine Learning for Developers

  Whether you are integrating a recommendation system into your app or building a chat bot, this guide will help you get started in understanding the basics of machine learning.

  https://www.kdnuggets.com/2016/11/intro-machine-learning-developers.html

• Continuous improvement for IoT through AI / Continuous learning">Continuous improvement for IoT through AI / Continuous learning

  In reality, especially for IoT, it is not like once an analytics model is built, it will give the results with same accuracy till the end of time. Data pattern changes over the time which makes it absolutely important to learn from new data and improve/recalibrate the models to get correct result. Below article explain this phenomenon of continuous improvement in analytics for IoT.

  https://www.kdnuggets.com/2016/11/continuous-improvement-iot-ai-learning.html

• Top 10 Facebook Groups for Big Data, Data Science, and Machine Learning

  Social media now not only shares friendship connections or photos of “selfies” but also spreads from political media to science information. Social network members are tending to more eagerly learn about big data, data science and machine learning through groups. We review the ten largest Facebook groups in this area.

  https://www.kdnuggets.com/2016/11/top-facebook-groups-big-data-science-machine-learning.html

• Top 20 Python Machine Learning Open Source Projects, updated">Top 20 Python Machine Learning Open Source Projects, updated

  Open Source is the heart of innovation and rapid evolution of technologies, these days. This article presents you Top 20 Python Machine Learning Open Source Projects of 2016 along with very interesting insights and trends found during the analysis.

  https://www.kdnuggets.com/2016/11/top-20-python-machine-learning-open-source-updated.html

• Questions To Ask When Moving Machine Learning From Practice to Production

  An overview of applying machine learning techniques to solve problems in production. This articles covers some of the varied questions to ponder when incorporating machine learning into teams and processes.

  https://www.kdnuggets.com/2016/11/moving-machine-learning-practice-production.html

• Parallelism in Machine Learning: GPUs, CUDA, and Practical Applications

  The lack of parallel processing in machine learning tasks inhibits economy of performance, yet it may very well be worth the trouble. Read on for an introductory overview to GPU-based parallelism, the CUDA framework, and some thoughts on practical implementation.

  https://www.kdnuggets.com/2016/11/parallelism-machine-learning-gpu-cuda-threading.html

• Agilience Top Artificial Intelligence, Machine Learning Authorities

  Agilience developed a new way to find authorities in social media across many fields of interest. In previous post we reviewed the top authorities in Data Mining and Data science; in this post we review top authorities in Artificial Intelligence and Machine Learning which includes Vineet Vashishta, Kirk D. Borne, KDnuggets, James Kobielus, Kaggle and more.

  https://www.kdnuggets.com/2016/11/agilence-top-artificial-intelligence-machine-learning-authorities.html

• Top /r/MachineLearning Posts, October: NSFW Image Recognition, Differentiable Neural Computers, Hinton on Coursera

  NSFW Image Recognition, Differentiable Neural Computers, Hinton's Neural Networks for Machine Learning Coursera course; Introducing the AI Open Network; Making a Self-driving RC Car

  https://www.kdnuggets.com/2016/11/top-reddit-machine-learning-october.html

• Machine Learning: A Complete and Detailed Overview">Machine Learning: A Complete and Detailed Overview

  This is an overview (with links) to a 5-part series on introductory machine learning. The set of tutorials is comprehensive, yet succinct, covering many important topics in the field (and beyond).

  https://www.kdnuggets.com/2016/10/machine-learning-complete-detailed-overview.html

• 5 EBooks to Read Before Getting into A Machine Learning Career">5 EBooks to Read Before Getting into A Machine Learning Career

  A carefully-curated list of 5 free ebooks to help you better understand the various aspects of what machine learning, and skills necessary for a career in the field.

  https://www.kdnuggets.com/2016/10/5-free-ebooks-machine-learning-career.html

• MLDB: The Machine Learning Database

  MLDB is an open­source database designed for machine learning. Send it commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.

  https://www.kdnuggets.com/2016/10/mldb-machine-learning-database.html

• Automated Data Science & Machine Learning: An Interview with the Auto-sklearn Team">Automated Data Science & Machine Learning: An Interview with the Auto-sklearn Team

  This is an interview with the authors of the recent winning KDnuggets Automated Data Science and Machine Learning blog contest entry, which provided an overview of the Auto-sklearn project. Learn more about the authors, the project, and automated data science.

  https://www.kdnuggets.com/2016/10/interview-auto-sklearn-automated-data-science-machine-learning-team.html

• Top Machine Learning Projects for Julia

  Julia is gaining traction as a legitimate alternative programming language for analytics tasks. Learn more about these 5 machine learning related projects.

  https://www.kdnuggets.com/2016/08/top-machine-learning-projects-julia.html

• The 10 Algorithms Machine Learning Engineers Need to Know">The 10 Algorithms Machine Learning Engineers Need to Know

  Read this introductory list of contemporary machine learning algorithms of importance that every engineer should understand.

  https://www.kdnuggets.com/2016/08/10-algorithms-machine-learning-engineers.html

• Short course: Statistical Learning and Data Mining IV, Washington, DC, Oct 19-20

  This new two-day course gives a detailed and modern overview of statistical models used by data scientists for prediction and inference, including sparse models and deep learning.

  https://www.kdnuggets.com/2016/08/tibshirani-statistical-learning-data-mining-washington-dc-october.html

• Reinforcement Learning and the Internet of Things

  Gain an understanding of how reinforcement learning can be employed in the Internet of Things world.

  https://www.kdnuggets.com/2016/08/reinforcement-learning-internet-things.html

• Would You Survive the Titanic? A Guide to Machine Learning in Python Part 2

  This is part 2 of a 3 part introductory series on machine learning in Python, using the Titanic dataset.

  https://www.kdnuggets.com/2016/07/titanic-machine-learning-guide-part-2.html

• Would You Survive the Titanic? A Guide to Machine Learning in Python Part 1

  Check out the first of a 3 part introductory series on machine learning in Python, fueled by the Titanic dataset. This is a great place to start for a machine learning newcomer.

  https://www.kdnuggets.com/2016/07/titanic-machine-learning-guide-part-1.html

• Multi-Task Learning in Tensorflow: Part 1

  A discussion and step-by-step tutorial on how to use Tensorflow graphs for multi-task learning.

  https://www.kdnuggets.com/2016/07/multi-task-learning-tensorflow-part-1.html

• Bayesian Machine Learning, Explained">Bayesian Machine Learning, Explained

  Want to know about Bayesian machine learning? Sure you do! Get a great introductory explanation here, as well as suggestions where to go for further study.
   
   

  https://www.kdnuggets.com/2016/07/bayesian-machine-learning-explained.html

• Top Machine Learning MOOCs and Online Lectures: A Comprehensive Survey

  This post reviews Machine Learning MOOCs and online lectures for both the novice and expert audience.

  https://www.kdnuggets.com/2016/07/top-machine-learning-moocs-online-lectures.html

• Deep Residual Networks for Image Classification with Python + NumPy

  This post outlines the results of an innovative Deep Residual Network implementation for Image Classification using Python and NumPy.

  https://www.kdnuggets.com/2016/07/deep-residual-neworks-image-classification-python-numpy.html

• 5 More Machine Learning Projects You Can No Longer Overlook

  There are a lot of popular machine learning projects out there, but many more that are not. Which of these are actively developed and worth checking out? Here is an offering of 5 such projects.

  https://www.kdnuggets.com/2016/06/five-more-machine-learning-projects-cant-overlook.html

• Top Machine Learning Libraries for Javascript

  Javascript may not be the conventional choice for machine learning, but there is no reason it cannot be used for such tasks. Here are the top libraries to facilitate machine learning in Javascript.

  https://www.kdnuggets.com/2016/06/top-machine-learning-libraries-javascript.html

• Machine Learning Trends and the Future of Artificial Intelligence

  The confluence of data flywheels, the algorithm economy, and cloud-hosted intelligence means every company can now be a data company, every company can now access algorithmic intelligence, and every app can now be an intelligent app.

  https://www.kdnuggets.com/2016/06/machine-learning-trends-future-ai.html

• New Andrew Ng Machine Learning Book Under Construction, Free Draft Chapters

  Check out the details on Andrew Ng's new book on building machine learning systems, and find out how to get your free copy of draft chapters as they are written.

  https://www.kdnuggets.com/2016/06/free-machine-learning-book-draft-chapters.html

• Bootcamps in Analytics, Big Data, Data Science, Machine Learning

  BaseCamp, an innovative data science bootcamp from Knoyd. The first cohort will start in Vienna, Austria in January 2017. Data Science Dojo, an in-person or Read more »

  https://www.kdnuggets.com/education/bootcamps.html

• Where are the Opportunities for Machine Learning Startups?

  Machine learning has permeated data-driven businesses, which means almost all businesses. Here are a few areas where it’s possible that big corporations haven’t already eaten everybody’s lunch.

  https://www.kdnuggets.com/2016/06/opportunites-machine-learning-startups.html

• Ethics in Machine Learning – Summary

  Still worried about the AI apocalypse? Here we are discussion about the constraints and ethics for the machine learning algorithms to prevent it.

  https://www.kdnuggets.com/2016/06/ethics-machine-learning-mlconf.html

• How to Explain Machine Learning to a Software Engineer

  How do you explain what machine learning is to the uninitiated software engineer? Read on for one perspective on doing so.

  https://www.kdnuggets.com/2016/05/explain-machine-learning-software-engineer.html

• 5 Machine Learning Projects You Can No Longer Overlook

  We all know the big machine learning projects out there: Scikit-learn, TensorFlow, Theano, etc. But what about the smaller niche projects that are actively developed, providing useful services to users? Here are 5 such projects.

  https://www.kdnuggets.com/2016/05/five-machine-learning-projects-cant-overlook.html

• Are Deep Neural Networks Creative?

  Deep neural networks routinely generate images and synthesize text. But does this amount to creativity? Can we reasonably claim that deep learning produces art?

  https://www.kdnuggets.com/2016/05/deep-neural-networks-creative-deep-learning-art.html

• Why Implement Machine Learning Algorithms From Scratch?

  Even with machine learning libraries covering almost any algorithm implementation you could imagine, there are often still good reasons to write your own. Read on to find out what these reasons are.

  https://www.kdnuggets.com/2016/05/implement-machine-learning-algorithms-scratch.html

• Machine Learning for Artists – Video lectures and notes

  Art has always been deep for those who appreciate it... but now, more than ever, deep learning is making a real impact on the art world. Check out this graduate course, and its freely-available resources, focusing on this very topic.

  https://www.kdnuggets.com/2016/04/machine-learning-artists-video-lectures-notes.html

• Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

  A list of 10 useful Github repositories made up of IPython (Jupyter) notebooks, focused on teaching data science and machine learning. Python is the clear target here, but general principles are transferable.

  https://www.kdnuggets.com/2016/04/top-10-ipython-nb-tutorials.html

• Top 15 Frameworks for Machine Learning Experts

  Either you are a researcher, start-up or big organization who wants to use machine learning, you will need the right tools to make it happen. Here is a list of the most popular frameworks for machine learning.

  https://www.kdnuggets.com/2016/04/top-15-frameworks-machine-learning-experts.html

• What Developers Actually Need to Know About Machine Learning

  Some guidance on what, exactly, it is that developers need to know to get up to speed with machine learning.

  https://www.kdnuggets.com/2016/04/developers-need-know-about-machine-learning.html

• 100 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning

  Stay on top of your data science skills game! Here’s a list of about 100 most active and interesting blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.

  https://www.kdnuggets.com/2016/03/100-active-blogs-analytics-big-data-science-machine-learning.html

• AI and Machine Learning: Top Influencers and Brands

  Onalytica gives us a new list of the top 100 Artifical Intelligence and Machine Learning influencers and brands, and provides some insight into the relationships between them.

  https://www.kdnuggets.com/2016/03/onalytica-ai-machine-learning-top-influencers-brands.html

• AutoML: Automated Data Science and Machine Learning

  For recent posts and more recent lists of AutoML and Automated Data Science, see Tag: AutoML. ABM: Automatic Business Modeler, automatically builds accurate and interpretable Read more »

  https://www.kdnuggets.com/software/automated-data-science.html

• AI Supercomputers: Microsoft Oxford, IBM Watson, Google DeepMind, Baidu Minwa

  In the world of AI, this is the equivalent of the US and USSR competing to put their guy on the moon first. Here is a profile of some of the giants locked into the AI space race.

  https://www.kdnuggets.com/2016/02/ai-supercomputers-microsoft-ibm-watson-google-deepmind-baidu.html

• Top 2015 KDnuggets Stories on Analytics, Big Data, Data Science, Data Mining, Machine Learning, updated

  R vs Python for Data Science: The Winner is ...; 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning; Top 20 Python Machine Learning Open Source Projects; 50+ Data Science and Machine Learning Cheat Sheets.

  https://www.kdnuggets.com/2016/01/top-2015-kdnuggets-stories-updated.html

• Lessons from 2 Million Machine Learning Models on Kaggle

  Lessons from Kaggle competitions, including why XG Boosting is the top method for structured problems, Neural Networks and deep learning dominate unstructured problems (visuals, text, sound), and 2 types of problems for which Kaggle is suitable.

  https://www.kdnuggets.com/2015/12/harasymiv-lessons-kaggle-machine-learning.html

• Top stories for Dec 13-19: Top 10 Machine Learning Projects on Github; Importance of Data Science for IoT business

  Top 10 Machine Learning Projects on Github; Using Python and R together: main approaches; Importance of Data Science for IoT business; Top 10 Deep Learning Tips, Tricks.

  https://www.kdnuggets.com/2015/12/top-news-week-dec-13.html

• 50 Useful Machine Learning & Prediction APIs

  We present a list of 50 APIs selected from areas like machine learning, prediction, text analytics & classification, face recognition, language translation etc. Start consuming APIs!

  https://www.kdnuggets.com/2015/12/machine-learning-data-science-apis.html

• 5 Tribes of Machine Learning – Questions and Answers

  Leading researcher Pedro Domingos answers questions on 5 tribes of Machine Learning, Master Algorithm, No Free Lunch Theorem, Unsupervised Learning, Ensemble methods, 360-degree recommender, and more.

  https://www.kdnuggets.com/2015/11/domingos-5-tribes-machine-learning-questions-answers.html

• 7 Steps to Mastering Machine Learning With Python

  There are many Python machine learning resources freely available online. Where to begin? How to proceed? Go from zero to Python machine learning hero in 7 steps!

  https://www.kdnuggets.com/2015/11/seven-steps-machine-learning-python.html

• The Best Advice From Quora on ‘How to Learn Machine Learning’

  Top machine learning writers on Quora give their advice on learning machine learning, including specific resources, quotes, and personal insights, along with some extra nuggets of information.

  https://www.kdnuggets.com/2015/10/learning-machine-learning-quora.html

• Top /r/MachineLearning Posts, September: Implement a neural network from scratch in C++

  Neural network in C++ for beginners, Chinese character handwriting recognition beats humans, a handy machine learning algorithm cheat sheet, neural nets versus functional programming, and a neural nets paper repository.

  https://www.kdnuggets.com/2015/10/top-reddit-machine-learning-september.html

• Top 10 Quora Machine Learning Writers and Their Best Advice

  Top Quora machine learning writers give their advice on pursuing a career in the field, academic research, and selecting and using appropriate technologies.

  https://www.kdnuggets.com/2015/09/top-machine-learning-writers-quora.html

• 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more

  Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science.

  https://www.kdnuggets.com/2015/09/free-data-science-books.html

• Top June stories: Top 20 Python Machine Learning Projects; Which Big Data, Data Mining Tools go together?

  Top 20 Python Machine Learning Open Source Projects; Which Big Data, Data Mining, and Data Science Tools go together?; Popular Deep Learning Tools - a review; Why Does Deep Learning Work?

  https://www.kdnuggets.com/2015/07/top-news-2015-jun.html

• 50+ Data Science and Machine Learning Cheat Sheets

  Gear up to speed and have Data Science & Data Mining concepts and commands handy with these cheatsheets covering R, Python, Django, MySQL, SQL, Hadoop, Apache Spark and Machine learning algorithms.

  https://www.kdnuggets.com/2015/07/good-data-science-machine-learning-cheat-sheets.html

• Excellent Tutorial on Sequence Learning using Recurrent Neural Networks

  Excellent tutorial explaining Recurrent Neural Networks (RNNs) which hold great promise for learning general sequences, and have applications for text analysis, handwriting recognition and even machine translation.

  https://www.kdnuggets.com/2015/06/rnn-tutorial-sequence-learning-recurrent-neural-networks.html

• Top 10 Machine Learning Videos on YouTube

  The top machine learning videos on YouTube include lecture series from Stanford and Caltech, Google Tech Talks on deep learning, using machine learning to play Mario and Hearthstone, and detecting NHL goals from live streams.

  https://www.kdnuggets.com/2015/06/top-10-machine-learning-videos-youtube.html

• In Machine Learning, What is Better: More Data or better Algorithms

  Gross over-generalization of “more data gives better results” is misguiding. Here we explain, in which scenario more data or more features are helpful and which are not. Also, how the choice of the algorithm affects the end result.

  https://www.kdnuggets.com/2015/06/machine-learning-more-data-better-algorithms.html

• Top 20 Python Machine Learning Open Source Projects

  We examine top Python Machine learning open source projects on Github, both in terms of contributors and commits, and identify most popular and most active ones.

  https://www.kdnuggets.com/2015/06/top-20-python-machine-learning-open-source-projects.html

• Machine Learning Table of Elements Decoded

  Machine learning packages for Python, Java, Big Data, Lua/JS/Clojure, Scala, C/C++, CV/NLP, and R/Julia are represented using a cute but ill-fitting metaphor of a periodic table. We extract the useful links.

  https://www.kdnuggets.com/2015/03/machine-learning-table-elements.html

• MetaMind Competes with IBM Watson Analytics and Microsoft Azure Machine Learning

  While Microsoft and IBM rush to bring data science and visualization to the masses, MetaMind follows another path, offering deep learning as a service.

  https://www.kdnuggets.com/2015/01/metamind-ibm-watson-analytics-microsoft-azure-machine-learning.html

• IBM Watson Analytics vs. Microsoft Azure Machine Learning (Part 1)

  IBM Watson Analytics prototype seeks to abstract away data science, taking ordinary natural language queries and answering them based on the content of uploaded datasets. Microsoft Azure Machine Learning goes the opposite route, streamlining existing data mining methodology for fast results and integration with MS's other cloud services.

  https://www.kdnuggets.com/2014/12/ibm-watson-analytics-microsoft-azure-machine-learning-p1.html

• Geoff Hinton AMA: Neural Networks, the Brain, and Machine Learning

  In a wide-ranging Q&A, Geoff Hinton addresses the future of deep learning, its biological inspirations, and his research philosophy.

  https://www.kdnuggets.com/2014/12/geoff-hinton-ama-neural-networks-brain-machine-learning.html

• R and Hadoop make Machine Learning Possible for Everyone

  R and Hadoop make machine learning approachable enough for inexperienced users to begin analyzing and visualizing interesting data to start down the path in this lucrative field.

  https://www.kdnuggets.com/2014/11/r-hadoop-make-machine-learning-possible-everyone.html

• Most Viewed Machine Learning Talks at Videolectures

  Discover lectures from a variety of summer schools and conference tutorials on machine learning in this list of the top lectures on the subject from videolectures.net.

  https://www.kdnuggets.com/2014/09/most-viewed-machine-learning-talks-videolectures.html

• Sibyl: Google’s system for Large Scale Machine Learning

  A review of 2014 keynote talk about Sibyl, Google system for large scale machine learning. Parallel Boosting algorithm and several design principles are introduced.

  https://www.kdnuggets.com/2014/08/sibyl-google-system-large-scale-machine-learning.html

• OpenML: Share, Discover and Do Machine Learning

  OpenML is designed to share, organize and reuse data, code and experiments, so that scientists can make discoveries more efficiently. It is an interesting idea to build a network of machine learning.

  https://www.kdnuggets.com/2014/08/openml-share-discover-do-machine-learning.html

• When Watson Meets Machine Learning

  Our report on a recent Cognitive Systems meetup co-sponsored by IBM Watson and NYU Center for Data Science, IBM Watson Ecosystem, and machine learning applications, from healthcare to cognitive toys. You will want Fang!

  https://www.kdnuggets.com/2014/07/watson-meets-machine-learning.html

• Vowpal Wabbit: Fast Learning on Big Data

  Vowpal Wabbit is a fast out-of-core machine learning system, which can learn from huge, terascale datasets faster than any other current algorithm. We also explain the cute name.

  https://www.kdnuggets.com/2014/05/vowpal-wabbit-fast-learning-on-big-data.html

• Blogs on AI, Analytics, Data Science, Machine Learning

  Here are some of the most interesting and regularly-updated blogs on Analytics, Big Data, Data Science, Data Mining, and Machine Learning, in alphabetical order. Blog Read more »

  https://www.kdnuggets.com/websites/blogs.html

• US/Canada Degree Programs in Data Science, Machine Learning, AI & Analytics

  Certificates | Courses | Online Masters | Europe Degrees | US/Canada Degrees United States of America   Northeast Connecticut: Central Connecticut State University (CCSU), exploring Read more »

  https://www.kdnuggets.com/education/usa-canada.html

• Certificates & Certifications in AI, Analytics, Data Science, Machine Learning

  Education | Certificates | Courses | Online Masters   Certificates Brandeis Graduate Certificate in Learning Analytics: 15-credit, five-course program to be completed in 1.5 years Read more »

  https://www.kdnuggets.com/education/analytics-data-mining-certificates.html

• Software Suites/Platforms for Analytics, Data Mining, Data Science, and Machine Learning

  commercial | free/open source A B C D E F G H I J K L M N O PQ R S T U V Read more »

  https://www.kdnuggets.com/software/suites.html

• Companies with Analytics, Data Mining, Data Science, and Machine Learning Products

  A B C D E F G H I J K L M N O P Q R S T U V W XYZ Advanced Read more »

  https://www.kdnuggets.com/companies/products.html

• Consulting Companies in AI, Analytics, Data Science, and Machine Learning

  A B C D E F G H I J K L M N O P Q R S T U V W XYZ 4i, Read more »

  https://www.kdnuggets.com/companies/consulting.html

• 3 Generations of Machine Learning and Data Mining Tools

  Three different paradigms available for implementing Machine Learning (ML) algorithms both from the literature and from the open source community.

  https://www.kdnuggets.com/2013/02/3-generations-machine-learning-data-mining-tools.html

• Ultimate Collection of 50 Free Courses for Mastering Data Science

  The collection includes free courses on Python, SQL, Data Analytics, Business Intelligence, Data Engineering, Machine Learning, Deep Learning, Generative AI, and MLOps.

  https://www.kdnuggets.com/ultimate-collection-of-50-free-courses-for-mastering-data-science

• WTF is Regularization and What is it For?

  This article explains the concept of regularization and its significance in machine learning and deep learning. We have discussed how regularization can be used to enhance the performance of linear models, as well as how it can be applied to improve the performance of deep learning models.

  https://www.kdnuggets.com/wtf-is-regularization-and-what-is-it-for

• KDnuggets News, December 13: 5 Super Cheat Sheets to Master Data Science • Using Google’s NotebookLM for Data Science: A Comprehensive Guide

  This week on KDnuggets: A collection of super cheat sheets that covers basic concepts of data science, probability & statistics, SQL, machine learning, and deep learning • An exploration of NotebookLM, its functionality, limitations, and advanced features essential for researchers and scientists • And much, much more!

  https://www.kdnuggets.com/newsletter-n45-2023-12-13

• 5 Super Cheat Sheets to Master Data Science

  The collection of super cheat sheets covers basic concepts of data science, probability & statistics, SQL, machine learning, and deep learning.

  https://www.kdnuggets.com/5-super-cheat-sheets-to-master-data-science

• Building a GPU Machine vs. Using the GPU Cloud

  The article examines the pros and cons of building an on-premise GPU machine versus using a GPU cloud service for projects involving deep learning and artificial intelligence, analyzing factors like cost, performance, operations, and scalability.

  https://www.kdnuggets.com/building-a-gpu-machine-vs-using-the-gpu-cloud

• Why Prompt Engineering is a Fad

  Various media outlets have been talking about prompt engineering with much fanfare, making it seem like it’s the ideal job — you don’t need to learn how to code, nor do you have to be knowledgeable about ML concepts like deep learning, datasets, etc. You’d agree that it seems too good to be true, right?

  https://www.kdnuggets.com/why-prompt-engineering-is-a-fad

• KDnuggets News, October 27: 5 Free Books to Master Data Science • 7 Steps to Mastering LLMs

  This week on KDnuggets: Go from learning what large language models are to building and deploying LLM apps in 7 steps • Check this list of free books for learning Python, statistics, linear algebra, machine learning and deep learning • And much, much more!

  https://www.kdnuggets.com/2023/n38.html

• 5 Free Books to Master Data Science

  Want to break into data science? Check this list of free books for learning Python, statistics, linear algebra, machine learning and deep learning.

  https://www.kdnuggets.com/5-free-books-to-master-data-science

• KDnuggets News, September 27: ChatGPT Projects Cheat Sheet • Introduction to PyTorch & Lightning AI

  10 ChatGPT Projects Cheat Sheet • Introduction to Deep Learning Libraries: PyTorch and Lightning AI • Top 5 Free Alternatives to GPT-4 • Machine Learning Evaluation Metrics: Theory and Overview • Kick Ass Midjourney Prompts with Poe

  https://www.kdnuggets.com/2023/n35.html

• KDnuggets 30th Anniversary Interview with Founder Gregory Piatetsky-Shapiro

  Gregory Piatetsky-Shapiro founded KDnuggets 30 years ago, after organizing early workshops on knowledge discovery. In this retrospective interview, he reflects on KDnuggets' growth, key innovations like deep learning, and concerns about AI's societal impact.

  https://www.kdnuggets.com/30th-anniversary-interview-with-founder-gregory-piatetsky-shapiro

• Keras 3.0: Everything You Need To Know

  Unlock the power of AI collaboration with Keras 3.0! Seamlessly switch between TensorFlow, JAX, and PyTorch, revolutionizing your deep learning projects. Read now and stay ahead in the world of AI.

  https://www.kdnuggets.com/2023/07/keras-30-everything-need-know.html

• Exploring the Latest Trends in AI/DL: From Metaverse to Quantum Computing

  The author discusses several emerging trends in Artificial Intelligence and Deep Learning such as Metaverse and Quantum Computing.

  https://www.kdnuggets.com/2023/07/exploring-latest-trends-aidl-metaverse-quantum-computing.html

• Introduction to Safetensors

  Introducing a new tool that offers speed, efficiency, cross-platform compatibility, user-friendliness, and security for deep learning applications.

  https://www.kdnuggets.com/2023/07/introduction-safetensors.html

• A Complete Collection of Data Science Free Courses – Part 2

  The second part covers the list of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Engineering, and MLOps.

  https://www.kdnuggets.com/2023/03/complete-collection-data-science-free-courses-part-2.html

• 5 Free Data Science Books You Must Read in 2023

  Get your hands on these gems to learn Python, data analytics, machine learning, and deep learning.

  https://www.kdnuggets.com/2023/01/5-free-data-science-books-must-read-2023.html

• Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science

  Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.

  https://www.kdnuggets.com/2020/10/data-science-minimum-10-essential-skills.html

• A Guide to Train an Image Classification Model Using Tensorflow

  Classify images at scale and with very high accuracy with the advent of machine learning and deep learning algorithms.

  https://www.kdnuggets.com/2022/12/guide-train-image-classification-model-tensorflow.html

• 5 Python Projects for Data Science Portfolio

  Get more experience by working on web scraping, data analytics, time-series forecasting, machine learning, and deep learning projects.

  https://www.kdnuggets.com/2022/12/5-python-projects-data-science-portfolio.html

• KDnuggets Top Posts for October 2022: 10 Cheat Sheets You Need To Ace Data Science Interview

  10 Cheat Sheets You Need To Ace Data Science Interview • 7 Free Platforms for Building a Strong Data Science Portfolio • The Complete Free PyTorch Course for Deep Learning • 3 Valuable Skills That Have Doubled My Income as a Data Scientist • 25 Advanced SQL Interview Questions for Data Scientists • A Data Science Portfolio That Will Land You The Job in 2022 • Top Free Git GUI Clients for Beginners • Essential Books You Need to Become a Data Engineer

  https://www.kdnuggets.com/2022/11/top-posts-october-2022.html

• 10 Cheat Sheets You Need To Ace Data Science Interview

  The only cheat you need for a job interview and data professional life. It includes SQL, web scraping, statistics, data wrangling and visualization, business intelligence, machine learning, deep learning, NLP, and super cheat sheets.

  https://www.kdnuggets.com/2022/10/10-cheat-sheets-need-ace-data-science-interview.html

• The Complete Collection of Data Science Projects – Part 2

  The second part covers the list of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Engineering, and MLOps.

  https://www.kdnuggets.com/2022/08/complete-collection-data-science-projects-part-2.html

• Online Training and Workshops with Nvidia

  Learn about the Nvidia Self-Paced Online Training from their Deep Learning Institute.

  https://www.kdnuggets.com/2022/07/online-training-workshops-nvidia.html

• The Complete Collection of Data Science Interviews – Part 2

  The second part covers the list of Data Management, Data Engineering, Machine Learning, Deep Learning, Natural Language Processing, MLOps, Cloud Computing, and AI Manager interview questions.

  https://www.kdnuggets.com/2022/06/complete-collection-data-science-interviews-part-2.html

• The Complete Collection of Data Science Books – Part 2

  Read the best books on Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, MLOps, Robotics, IoT, AI Products Management, and Data Science for Executives.

  https://www.kdnuggets.com/2022/05/complete-collection-data-science-books-part-2.html

• Understanding Agent Environment in AI

  The role of the agent is always very important in artificial intelligence, machine learning, and deep learning. Learn more about agents here.

  https://www.kdnuggets.com/2022/05/understanding-agent-environment-ai.html

• From Google Colab to a Ploomber Pipeline: ML at Scale with GPUs

  In this short blog, we’ll review the process of taking a POC data science pipeline (ML/Deep learning/NLP) that was conducted on Google Colab, and transforming it into a pipeline that can run parallel at scale and works with Git so the team can collaborate on.

  https://www.kdnuggets.com/2022/03/google-colab-ploomber-pipeline-ml-scale-gpus.html

• The Complete Collection of Data Science Cheat Sheets – Part 2

  A collection of cheat sheets that will help you prepare for a technical interview on Data Structures & Algorithms, Machine learning, Deep Learning, Natural Language Processing, Data Engineering, Web Frameworks.

  https://www.kdnuggets.com/2022/02/complete-collection-data-science-cheat-sheets-part-2.html

• Advanced PyTorch Lightning with TorchMetrics and Lightning Flash

  In this tutorial we will be diving deeper into two additional tools you should be using: TorchMetrics and Lightning Flash. TorchMetrics unsurprisingly provides a modular approach to define and track useful metrics across batches and devices, while Lightning Flash offers a suite of functionality facilitating more efficient transfer learning and data handling, and a recipe book of state-of-the-art approaches to typical deep learning problems.

  https://www.kdnuggets.com/2021/11/advanced-pytorch-lightning-torchmetrics-lightning-flash.html

• Learn To Reproduce Papers: Beginner’s Guide">Learn To Reproduce Papers: Beginner’s Guide

  Step-by-step instructions on how to understand Deep Learning papers and implement the described approaches.

  https://www.kdnuggets.com/2021/10/learn-reproduce-papers-beginners-guide.html

• How our Obsession with Algorithms Broke Computer Vision: And how Synthetic Computer Vision can fix it

  Deep Learning radically improved Machine Learning as a whole. The Data-Centric revolution is about to do the same. In this post, we’ll take a look at the pitfalls of mainstream Computer Vision (CV) and discuss why Synthetic Computer Vision (SCV) is the future.

  https://www.kdnuggets.com/2021/10/obsession-algorithms-broke-computer-vision.html

• Computer Vision in Agriculture

  Deep learning isn’t just for placing ads or identifying cats anymore. Instead, a slew of young startups have started to incorporate the advances in computer vision made possible through larger and larger neural networks to real working robots in the fields.

  https://www.kdnuggets.com/2021/09/computer-vision-agriculture.html

• Top Stories, Jul 12-18: Top 6 Data Science Online Courses in 2021; Become an Analytics Engineer in 90 Days

  Also: Data Scientists and ML Engineers Are Luxury Employees; Geometric foundations of Deep Learning; How Can You Distinguish Yourself from Hundreds of Other Data Science Candidates?; A Learning Path To Becoming a Data Scientist

  https://www.kdnuggets.com/2021/07/top-news-week-0712-0718.html

• Beginners Guide to Debugging TensorFlow Models

  If you are new to working with a deep learning framework, such as TensorFlow, there are a variety of typical errors beginners face when building and training models. Here, we explore and solve some of the most common errors to help you develop a better intuition for debugging in TensorFlow.

  https://www.kdnuggets.com/2021/06/beginners-guide-debugging-tensorflow-models.html

• Best Python Books for Beginners and Advanced Programmers

  Let's take a look at nine of the best Python books for both beginners and advanced programmers, covering topics such as data science, machine learning, deep learning, NLP, and more.

  https://www.kdnuggets.com/2021/05/best-python-books-beginner-advanced.html

• Applying Natural Language Processing in Healthcare

  New advances in natural language processing (NLP) based on deep learning and transfer learning have made a whole set of software use cases in healthcare viable. The Healthcare NLP Summit is a free online conference on April 6th and 7th, bringing together 30+ technical sessions from across the community that works to apply these advances in the real world.

  https://www.kdnuggets.com/2021/03/formulated-natural-language-processing-healthcare.html

• Six Times Bigger than GPT-3: Inside Google’s TRILLION Parameter Switch Transformer Model

  Google’s Switch Transformer model could be the next breakthrough in this area of deep learning.

  https://www.kdnuggets.com/2021/01/google-trillion-parameter-switch-transformer-model.html

• Mastering TensorFlow Variables in 5 Easy Steps

  Learn how to use TensorFlow Variables, their differences from plain Tensor objects, and when they are preferred over these Tensor objects | Deep Learning with TensorFlow 2.x.

  https://www.kdnuggets.com/2021/01/mastering-tensorflow-variables-5-easy-steps.html

• Covid or just a Cough? AI for detecting COVID-19 from Cough Sounds

  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.

  https://www.kdnuggets.com/2020/12/covid-cough-ai-detecting-sounds.html

• Building AI Models for High-Frequency Streaming Data – Part Two

  Many data scientists have implemented machine or deep learning algorithms on static data or in batch, but what considerations must you make when building models for a streaming environment? In this post, we will discuss these considerations.

  https://www.kdnuggets.com/2020/12/mathworks-pt2-ai-models-streaming-data.html

• Computer Vision at Scale With Dask And PyTorch

  A tutorial on conducting image classification inference using the Resnet50 deep learning model at scale with using GPU clusters on Saturn Cloud. The results were: 40x faster computer vision that made a 3+ hour PyTorch model run in just 5 minutes.

  https://www.kdnuggets.com/2020/11/computer-vision-scale-dask-pytorch.html

• An Introduction to AI, updated">An Introduction to AI, updated

  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.

  https://www.kdnuggets.com/2020/10/introduction-ai-updated.html

• The Most Complete Guide to PyTorch for Data Scientists

  All the PyTorch functionality you will ever need while doing Deep Learning. From an Experimentation/Research Perspective.

  https://www.kdnuggets.com/2020/09/most-complete-guide-pytorch-data-scientists.html

• Artificial Intelligence for Precision Medicine and Better Healthcare

  In this article, we will focus on various machine learning, deep learning models, and applications of AI which can pave the way for a new data-centric era of discovery in healthcare.

  https://www.kdnuggets.com/2020/09/artificial-intelligence-precision-medicine-better-healthcare.html