Search results for "deep learning"

3152 documents found out of 7188 total.

• How To Unit Test Machine Learning Code

  One of the main principles I learned during my time at Google Brain was that unit tests can make or break your algorithm and can save you weeks of debugging and training time.

  https://www.kdnuggets.com/2017/11/unit-test-machine-learning-code.html

• Machine Learning Algorithms: Which One to Choose for Your Problem">Machine Learning Algorithms: Which One to Choose for Your Problem

  This article will try to explain basic concepts and give some intuition of using different kinds of machine learning algorithms in different tasks. At the end of the article, you’ll find the structured overview of the main features of described algorithms.

  https://www.kdnuggets.com/2017/11/machine-learning-algorithms-choose-your-problem.html

• Interpreting Machine Learning Models: An Overview">Interpreting Machine Learning Models: An Overview

  This post summarizes the contents of a recent O'Reilly article outlining a number of methods for interpreting machine learning models, beyond the usual go-to measures.

  https://www.kdnuggets.com/2017/11/interpreting-machine-learning-models-overview.html

• Getting Started with Machine Learning in One Hour!

  Here is a machine learning getting started guide which grew out of the author's notes for a one hour talk on the subject. Hopefully you find the path helpful.

  https://www.kdnuggets.com/2017/11/getting-started-machine-learning-one-hour.html

• New Poll: When will demand for Data Scientists/Machine Learning experts begin to decline?

  New KDnuggets Poll examines how long the current high demand for Data Scientists/Machine Learning experts will last. Please vote and we will analyze and report the results.

  https://www.kdnuggets.com/2017/10/new-poll-demand-data-scientists-machine-learning-decline.html

• How LinkedIn Makes Personalized Recommendations via Photon-ML Machine Learning tool">How LinkedIn Makes Personalized Recommendations via Photon-ML Machine Learning tool

  In this article we focus on the personalization aspect of model building and explain the modeling principle as well as how to implement Photon-ML so that it can scale to hundreds of millions of users.

  https://www.kdnuggets.com/2017/10/linkedin-personalized-recommendations-photon-ml.html

• How I started with learning AI in the last 2 months">How I started with learning AI in the last 2 months

  The relevance of a full stack developer will not be enough in the changing scenario of things. In the next two years, full stack will not be full stack without AI skills.

  https://www.kdnuggets.com/2017/10/how-started-learning-ai.html

• Using Machine Learning to Predict and Explain Employee Attrition">Using Machine Learning to Predict and Explain Employee Attrition

  Employee attrition (churn) is a major cost to an organization. We recently used two new techniques to predict and explain employee turnover: automated ML with H2O and variable importance analysis with LIME.

  https://www.kdnuggets.com/2017/10/machine-learning-predict-employee-attrition.html

• Understanding Machine Learning Algorithms">Understanding Machine Learning Algorithms

  Machine learning algorithms aren’t difficult to grasp if you understand the basic concepts. Here, a SAS data scientist describes the foundations for some of today’s popular algorithms.

  https://www.kdnuggets.com/2017/10/understanding-machine-learning-algorithms.html

• Top 10 Videos on Machine Learning in Finance">Top 10 Videos on Machine Learning in Finance

  Talks, tutorials and playlists – you could not get a more gentle introduction to Machine Learning (ML) in Finance. Got a quick 4 minutes or ready to study for hours on end? These videos cover all skill levels and time constraints!

  https://www.kdnuggets.com/2017/09/top-10-videos-machine-learning-finance.html

• Ensemble Learning to Improve Machine Learning Results

  Ensemble methods are meta-algorithms that combine several machine learning techniques into one predictive model in order to decrease variance (bagging), bias (boosting), or improve predictions (stacking).

  https://www.kdnuggets.com/2017/09/ensemble-learning-improve-machine-learning-results.html

• 5 Ways to Get Started with Reinforcement Learning

  We give an accessible overview of reinforcement learning, including Deep Q Learning, and provide useful links for implementing RL.

  https://www.kdnuggets.com/2017/09/5-ways-get-started-reinforcement-learning.html

• Machine Learning Translation and the Google Translate Algorithm

  Today, we’ve decided to explore machine translators and explain how the Google Translate algorithm works.

  https://www.kdnuggets.com/2017/09/machine-learning-translation-google-translate-algorithm.html

• New-Age Machine Learning Algorithms in Retail Lending">New-Age Machine Learning Algorithms in Retail Lending

  We review the application of new age Machine Learning algorithms for better Customer Analytics in Lending and Credit Risk Assessment.

  https://www.kdnuggets.com/2017/09/machine-learning-algorithms-lending.html

• Python vs R – Who Is Really Ahead in Data Science, Machine Learning?">Python vs R – Who Is Really Ahead in Data Science, Machine Learning?

  We examine Google Trends, job trends, and more and note that while Python has only a small advantage among current Data Science and Machine Learning related jobs, this advantage is likely to increase in the future.

  https://www.kdnuggets.com/2017/09/python-vs-r-data-science-machine-learning.html

• Top 10 Machine Learning Use Cases: Part 2

  This post is the second in a series whose aim is to shake up our intuitions about what machine learning is making possible in specific sectors — to look beyond the set of use cases that always come to mind.

  https://www.kdnuggets.com/2017/09/ibm-top-10-machine-learning-use-cases-part2.html

• Cartoon: Future Machine Learning Class">Cartoon: Future Machine Learning Class

  New KDnuggets Cartoon looks at an unusual but possible future Machine Learning Class.

  https://www.kdnuggets.com/2017/09/cartoon-machine-learning-class.html

• Are physicians worried about computers machine learning their jobs?

  We review JAMA article on “Unintended Consequences of Machine Learning in Medicine” and argue that a number of alarming opinions in this pieces are not supported by evidence.

  https://www.kdnuggets.com/2017/08/are-physicians-worried-about-computers-machine-learning-their-jobs.html

• An Intuitive Guide to Deep Network Architectures

  How and why do different Deep Learning models work? We provide an intuitive explanation for 3 very popular DL models: Resnet, Inception, and Xception.

  https://www.kdnuggets.com/2017/08/intuitive-guide-deep-network-architectures.html

• Support Vector Machine (SVM) Tutorial: Learning SVMs From Examples

  In this post, we will try to gain a high-level understanding of how SVMs work. I’ll focus on developing intuition rather than rigor. What that essentially means is we will skip as much of the math as possible and develop a strong intuition of the working principle.

  https://www.kdnuggets.com/2017/08/support-vector-machines-learning-svms-examples.html

• What Artificial Intelligence and Machine Learning Can Do—And What It Can’t">What Artificial Intelligence and Machine Learning Can Do—And What It Can’t

  I have seen situations where AI (or at least machine learning) had an incredible impact on a business—I also have seen situations where this was not the case. So, what was the difference?

  https://www.kdnuggets.com/2017/08/rapidminer-ai-machine-learning-can-do.html

• Going deeper with recurrent networks: Sequence to Bag of Words Model

  Deep learning makes it possible to convert unstructured text to computable formats, incorporating semantic knowledge to train machine learning models. These digital data troves help us understand people on a new level.

  https://www.kdnuggets.com/2017/08/deeper-recurrent-networks-sequence-bag-words-model.html

• The Machine Learning Abstracts: Decision Trees

  Decision trees are a classic machine learning technique. The basic intuition behind a decision tree is to map out all possible decision paths in the form of a tree.

  https://www.kdnuggets.com/2017/08/machine-learning-abstracts-decision-trees.html

• The Machine Learning Abstracts: Classification

  Classification is the process of categorizing or “classifying” some items into a predefined set of categories or “classes”. It is exactly the same even when a machine does so. Let’s dive a little deeper.

  https://www.kdnuggets.com/2017/07/machine-learning-abstracts-classification.html

• Optimization in Machine Learning: Robust or global minimum?

  Here we discuss how convex problems are solved and optimised in machine learning/deep learning.

  https://www.kdnuggets.com/2017/06/robust-global-minimum.html

• The world’s first protein database for Machine Learning and AI">The world’s first protein database for Machine Learning and AI

  dSPP is the world first interactive database of proteins for AI and Machine Learning, and is fully integrated with Keras and Tensorflow. You can access the database at peptone.io/dspp

  https://www.kdnuggets.com/2017/06/dspp-protein-database-machine-learning-ai.html

• Making Sense of Machine Learning">Making Sense of Machine Learning

  Broadly speaking, machine learners are computer algorithms designed for pattern recognition, curve fitting, classification and clustering. The word learning in the term stems from the ability to learn from data.

  https://www.kdnuggets.com/2017/06/making-sense-machine-learning.html

• Does Machine Learning Have a Future Role in Cyber Security?

  In the past, ML learning hasn't had as much success in cyber security as in other fields. Many early attempts struggled with problems such as generating too many false positives, which resulted mixed attitudes towards it.

  https://www.kdnuggets.com/2017/06/machine-learning-future-role-cyber-security.html

• Which Machine Learning Algorithm Should I Use?">Which Machine Learning Algorithm Should I Use?

  A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is "which algorithm should I use?” The answer to the question varies depending on many factors, including the size, quality, and nature of data, the available computational time, and more.

  https://www.kdnuggets.com/2017/06/which-machine-learning-algorithm.html

• Top Stories, May 22-28: Analytics, Data Science, Machine Learning Software Poll Results; Machine Learning Crash Course

  New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll; Machine Learning Crash Course: Part 1; Text Mining 101: Mining Information From A Resume; Data science platforms are on the rise and IBM is leading the way; An Introduction to the MXNet Python API

  https://www.kdnuggets.com/2017/05/top-news-week-0522-0528.html

• Machine Learning Workflows in Python from Scratch Part 1: Data Preparation">Machine Learning Workflows in Python from Scratch Part 1: Data Preparation

  This post is the first in a series of tutorials for implementing machine learning workflows in Python from scratch, covering the coding of algorithms and related tools from the ground up. The end result will be a handcrafted ML toolkit. This post starts things off with data preparation.

  https://www.kdnuggets.com/2017/05/machine-learning-workflows-python-scratch-part-1.html

• Machine Learning Crash Course: Part 1

  This post, the first in a series of ML tutorials, aims to make machine learning accessible to anyone willing to learn. We’ve designed it to give you a solid understanding of how ML algorithms work as well as provide you the knowledge to harness it in your projects.

  https://www.kdnuggets.com/2017/05/machine-learning-crash-course-part-1.html

• New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll">New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll

  Python caught up with R and (barely) overtook it; Deep Learning usage surges to 32%; RapidMiner remains top general Data Science platform; Five languages of Data Science.
   
   

  https://www.kdnuggets.com/2017/05/poll-analytics-data-science-machine-learning-software-leaders.html

• The Path To Learning Artificial Intelligence

  Learn how to easily build real-world AI for booming tech, business, pioneering careers and game-level fun.

  https://www.kdnuggets.com/2017/05/path-learning-artificial-intelligence.html

• 5 Machine Learning Projects You Can No Longer Overlook, May

  In this month's installment of Machine Learning Projects You Can No Longer Overlook, we find some data preparation and exploration tools, a (the?) reinforcement learning "framework," a new automated machine learning library, and yet another distributed deep learning library.

  https://www.kdnuggets.com/2017/05/five-machine-learning-projects-cant-overlook-may.html

• Data Science & Machine Learning Platforms for the Enterprise

  A resilient Data Science Platform is a necessity to every centralized data science team within a large corporation. It helps them centralize, reuse, and productionize their models at peta scale.

  https://www.kdnuggets.com/2017/05/data-science-machine-learning-platforms-enterprise.html

• New Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?">New Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?

  Vote in KDnuggets 18th Annual Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? We will clean, analyze, visualize, and publish the results.

  https://www.kdnuggets.com/2017/05/new-poll-software-analytics-data-mining-data-science-machine-learning.html

• Machine Learning overtaking Big Data?">Machine Learning overtaking Big Data?

  Is Machine Learning is overtaking Big Data?! We also examine trends for several more related and popular buzzwords, and see how BD, ML. Artificial Intelligence, Data Science, and Deep Learning rank.

  https://www.kdnuggets.com/2017/05/machine-learning-overtaking-big-data.html

• Top 10 Machine Learning Videos on YouTube, updated">Top 10 Machine Learning Videos on YouTube, updated

  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/2017/05/top-10-machine-learning-videos-on-youtube-updated.html

• The Guerrilla Guide to Machine Learning with Python">The Guerrilla Guide to Machine Learning with Python

  Here is a bare bones take on learning machine learning with Python, a complete course for the quick study hacker with no time (or patience) to spare.

  https://www.kdnuggets.com/2017/05/guerrilla-guide-machine-learning-python.html

• AI & Machine Learning Black Boxes: The Need for Transparency and Accountability

  When something goes wrong, as it inevitably does, it can be a daunting task discovering the behavior that caused an event that is locked away inside a black box where discoverability is virtually impossible.

  https://www.kdnuggets.com/2017/04/ai-machine-learning-black-boxes-transparency-accountability.html

• Forrester vs Gartner on Data Science Platforms and Machine Learning Solutions">Forrester vs Gartner on Data Science Platforms and Machine Learning Solutions

  Who leads in Data Science, Machine Learning, and Predictive Analytics? We compare the latest Forrester and Gartner reports for this industry for 2017 Q1, identify gainers and losers, and strong leaders vs contenders.

  https://www.kdnuggets.com/2017/04/forrester-gartner-data-science-platforms-machine-learning.html

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

  It's about that time again... 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out. Find tools for data exploration, topic modeling, high-level APIs, and feature selection herein.

  https://www.kdnuggets.com/2017/04/five-machine-learning-projects-cant-overlook-april.html

• Machine Learning Finds “Fake News” with 88% Accuracy

  In this post, the author assembles a dataset of fake and real news and employs a Naive Bayes classifier in order to create a model to classify an article as fake or real based on its words and phrases.

  https://www.kdnuggets.com/2017/04/machine-learning-fake-news-accuracy.html

• 10 Free Must-Read Books for Machine Learning and Data Science">10 Free Must-Read Books for Machine Learning and Data Science

  Spring. Rejuvenation. Rebirth. Everything’s blooming. And, of course, people want free ebooks. With that in mind, here's a list of 10 free machine learning and data science titles to get your spring reading started right.

  https://www.kdnuggets.com/2017/04/10-free-must-read-books-machine-learning-data-science.html

• Top /r/MachineLearning Posts, March: A Super Harsh Guide to Machine Learning; Is it Gaggle or Koogle?!?

  A Super Harsh Guide to Machine Learning; Google is acquiring data science community Kaggle; Suggestion by Salesforce chief data scientist; Andrew Ng resigning from Baidu; Distill: An Interactive, Visual Journal for Machine Learning Research

  https://www.kdnuggets.com/2017/04/top-reddit-machine-learning-march.html

• Applying Machine Learning To March Madness

  March Madness is upon us. But before you get your brackets set, check out this overview of using machine learning to do the heavy lifting for you. A great discussion, and a timely topic.

  https://www.kdnuggets.com/2017/03/machine-learning-march-madness.html

• Software Engineering vs Machine Learning Concepts

  Not all core concepts from software engineering translate into the machine learning universe. Here are some differences I've noticed.

  https://www.kdnuggets.com/2017/03/software-engineering-vs-machine-learning-concepts.html

• Gartner Data Science Platforms – A Deeper Look

  Thomas Dinsmore critical examination of Gartner 2017 MQ of Data Science Platforms, including vendors who out, in, have big changes, Hadoop and Spark integration, open source software, and what Data Scientists actually use.

  https://www.kdnuggets.com/2017/03/thomaswdinsmore-gartner-data-science-platforms.html

• 7 More Steps to Mastering Machine Learning With Python">7 More Steps to Mastering Machine Learning With Python

  This post is a follow-up to last year's introductory Python machine learning post, which includes a series of tutorials for extending your knowledge beyond the original.
   
   

  https://www.kdnuggets.com/2017/03/seven-more-steps-machine-learning-python.html

• Learning to Learn by Gradient Descent by Gradient Descent

  What if instead of hand designing an optimising algorithm (function) we learn it instead? That way, by training on the class of problems we’re interested in solving, we can learn an optimum optimiser for the class!

  https://www.kdnuggets.com/2017/02/learning-learn-gradient-descent.html

• 6 areas of AI and Machine Learning to watch closely">6 areas of AI and Machine Learning to watch closely

  Artificial Intelligence is a generic term and many fields of science overlaps when comes to make an AI application. Here is an explanation of AI and its 6 major areas to be focused, going forward.

  https://www.kdnuggets.com/2017/01/6-areas-ai-machine-learning.html

• Great Collection of Minimal and Clean Implementations of Machine Learning Algorithms

  Interested in learning machine learning algorithms by implementing them from scratch? Need a good set of examples to work from? Check out this post with links to minimal and clean implementations of various algorithms.

  https://www.kdnuggets.com/2017/01/great-collection-clean-machine-learning-algorithms.html

• 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