Machine Learning (1978)

• How To Become A Machine Learning Expert In One Simple Step - Mar 29, 2016.
  
  This post looks at perhaps the most important, and often overlooked, step in learning machine learning, an aspect which can make the biggest difference in one's skill set.

  Advice, Kaggle, Machine Learning

• 100 Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning - Mar 29, 2016.
  
  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.

  Pages: 1 2

  Big Data, Blogs, Data Science, Deep Learning, Hadoop, Machine Learning

• Don’t Buy Machine Learning - Mar 28, 2016.
  
  In many projects, the amount of effort spent on R&D on Machine Learning is usually a small fraction of the total effort, or it’s not even there because we plan it for a future phase after building the application first.

  Advice, Industry, Machine Learning

• Salford Systems: Software Engineer. Machine Learning algorithms. C++ - Mar 12, 2016.
  
  Salford Systems is an advanced data mining software and consulting company, affiliated with some of the world greatest Machine Learning scientists, and leads the industry with exciting, innovative products.

  C++, CA, Machine Learning, Salford Systems, San Diego, Software Engineer

• The Data Science Puzzle, Explained - Mar 10, 2016.
  
  The puzzle of data science is examined through the relationship between several key concepts in the data science realm. As we will see, far from being concrete concepts etched in stone, divergent opinions are inevitable; this is but another opinion to consider.

  Pages: 1 2

  Artificial Intelligence, Data Mining, Data Science, Deep Learning, Explained, Machine Learning

• AI and Machine Learning: Top Influencers and Brands - Mar 8, 2016.
  
  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.

  About Gregory Piatetsky, AI, Influencers, Kirk D. Borne, Machine Learning, Onalytica, Top list

• scikit-feature: Open-Source Feature Selection Repository in Python - Mar 3, 2016.
  
  scikit-feature is an open-source feature selection repository in python, with around 40 popular algorithms in feature selection research. It is developed by Data Mining and Machine Learning Lab at Arizona State University.

  Data Mining, Data Science, Feature Extraction, Feature Selection, Machine Learning, Python

• Machine Learning at your fingertips – 60+ free APIs, from HPE Haven OnDemand - Feb 29, 2016.
  
  HPE Haven on Demand has 60+ Machine Learning free APIs to connect, extract, analyze, search, predict - get your API Key and RSVP for the HPE Analytics World Tour.

  Amsterdam, API, Beijing, CA, Haven OnDemand, HPE, Machine Learning, Palo Alto, Paris, Singapore

• The Machine Learning Problem of The Next Decade - Feb 26, 2016.
  
  How can businesses integrate imperfect machine-learning algorithms into their workflow?

  Pages: 1 2

  Accuracy, Cars, CrowdFlower, Kaggle, Lukas Biewald, Machine Learning, Prediction, Self-Driving Car

• HPI Future SOC Lab offers researchers free access to a powerful Big Data & Computing infrastructure - Feb 19, 2016.
  
  The HPI Future SOC (Service-Oriented Computing) Lab is a cooperation of the Hasso Plattner Institute (HPI) and industrial partners, providing free access to a powerful Big Data & Computing infrastructure. It is now accepting project proposals.

  Cloud Computing, Data Incubator, In-Memory Computing, Machine Learning, Research

• Amazon Machine Learning: Nice and Easy or Overly Simple? - Feb 17, 2016.
  
  Amazon Machine Learning is a predictive analytics service with binary/multiclass classification and linear regression features. The service is fast, offers a simple workflow but lacks model selection features and has slow execution times.

  Amazon, Classification, Machine Learning, MLaaS

• Ensemble Methods: Elegant Techniques to Produce Improved Machine Learning Results - Feb 12, 2016.
  
  Get a handle on ensemble methods from voting and weighting to stacking and boosting, with this well-written overview that includes numerous Python-style pseudocode examples for reinforcement.

  Pages: 1 2

  Boosting, Ensemble Methods, Machine Learning, Python

• Does Machine Learning allow opposites to attract? - Feb 11, 2016.
  
  Most online dating sites use 'Netflix-style' recommendations which match people based on their shared interests and likes. What about those matches that work so well because people are so different - here is my example.

  Love, Machine Learning, Online Dating, Recommendations

• Machine Learning Course for R&D Specialists, 4-8 April, Delft, The Netherlands - Feb 1, 2016.
  
  Do you want to go beyond theory and learn how to create working Machine Learning solutions? This 5-day course provides you with practical step-by-step methodology.

  Delft, Machine Learning, MATLAB, Netherlands, perClass

• Introducing Quora’s Machine Learning Sessions Series - Jan 19, 2016.
  
  Quora is launching a new format for interacting with domain experts and sharing knowledge, and its first topic is Machine Learning. Yoshua Bengio is the first expert, and he is accepting questions now.

  Machine Learning, Question answering, Quora, Xavier Amatriain, Yoshua Bengio

• Yahoo Releases the Largest-ever Machine Learning Dataset for Researchers - Jan 18, 2016.
  
  Are you interested in massive amounts of data for research? Yahoo has just released the largest-ever machine learning dataset to the research community.

  Anonymized, Dataset, Machine Learning, Yahoo

• Hitchhikers Guide to Azure Machine Learning Studio - Jan 15, 2016.
  
  Learn Azure ML Studio through this brief hands-on tutorial. This step-by-step guide will help you get a quick-start and grasp the basics of this Predictive Modeling tool.

  Pages: 1 2 3 4

  AWS, Azure ML, Decision Trees, edX, Machine Learning, Web services

• 20 Questions to Detect Fake Data Scientists - Jan 1, 2016.
  
  Hiring Data Scientists is no easy job, particularly when there are plenty of fake posers. Here is a handy list of questions to help separate the wheat from the chaff.

  Data Scientist, Data Visualization, import.io, Kirk D. Borne, Machine Learning, Outliers

• What questions can data science answer? - Jan 1, 2016.
  
  There are only five questions machine learning can answer: Is this A or B? Is this weird? How much/how many? How is it organized? What should I do next? We examine these questions in detail and what it implies for data science.

  Pages: 1 2

  Classification, Clustering, Machine Learning, Regression

• TensorFlow is Terrific – A Sober Take on Deep Learning Acceleration - Dec 30, 2015.
  
  TensorFlow does not change the world. But it appears to be the best, most convenient deep learning library out there.

  Deep Learning, Facebook, Google, Machine Learning, TensorFlow, Torch, Zachary Lipton

• Tour of Real-World Machine Learning Problems - Dec 26, 2015.
  
  The tour lists 20 interesting real-world machine learning problems for data science enthusiasts to learn by solving.

  Datasets, Kaggle, Learning from Data, Machine Learning, Research, UCI

• The future of analytics – top 5 predictions for 2016 - Dec 23, 2015.
  
  Analytics has never been more needed or interesting and the future looks exciting. Top 2016 trends include Machine learning established in the enterprise, Internet of Things hype hits reality, and Big data moves beyond hype to enrich modeling.

  2016 Predictions, Cybersecurity, Industry, IoT, Machine Learning

• Top KDnuggets tweets, Dec 14-20: DeepLearning in a Nutshell: History and Training; Top 10 #MachineLearning Algorithms, updated - Dec 21, 2015.
  
  Top 10 #MachineLearning Algorithms, updated; Cartoon: Surprise #DataScience #Recommendations; DeepLearning in a Nutshell: History and Training; Update: Google #TensorFlow #DeepLearning Is Improving.

  Algorithms, Deep Learning, Machine Learning, TensorFlow

• KDnuggets™ News 15:n41, Dec 16: Top 10 Machine Learning Projects on Github; How to use Python and R together - Dec 16, 2015.
  
  Top 10 Machine Learning Projects on Github; Using Python and R together: 3 main approaches; Top 2015 KDnuggets Stories on Analytics, Big Data, Data Science; 22 Big Data experts predictions for 2016.

  GitHub, Machine Learning, Python vs R

• Top KDnuggets tweets, Dec 07-13: 50 Useful Machine Learning and Prediction APIs; 35 R Job Interview Questions, Answers - Dec 14, 2015.
  
  R Programming: 35 Job #Interview Questions and Answers; A Look into #MachineLearning First Cheating #Scandal; The current state of #machine #intelligence 2.0 ; #Dilbert Dark #humor on combining #DNA tests and #Bevaviour #Predictions;

  API, Deep Learning, Fashion, Hiring, Machine Learning, R

• Top 10 Machine Learning Projects on Github - Dec 14, 2015.
  
  The top 10 machine learning projects on Github include a number of libraries, frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.

  Pages: 1 2

  GitHub, Machine Learning, Matthew Mayo, Open Source, scikit-learn, Top 10

• Top 10 Deep Learning Tips & Tricks - Dec 14, 2015.
  
  Deep Learning has been at the forefront of data science innovations throughout 2015. Dr. Arno Candel offers help through some valuable tips.

  Arno Candel, Deep Learning, H2O, Machine Learning, Tips, Top 10

• Top 5 Big Data / Machine Learning Podcasts - Dec 10, 2015.
  
  Podcasts are probably one of the most underrated forms of communication, especially given that, for the most part, they are free. Here we have collected best of big data and machine learning podcasts.

  Big Data, Machine Learning, Podcast, TED

• KDnuggets™ News 15:n40, Dec 9: 50 useful Machine Learning & Data Science APIs; How Do Neural Nets Learn - Dec 9, 2015.
  
  50 Useful Machine Learning & Prediction APIs; How do Neural Networks Learn?; Free Data Science Curriculum; Spark + Deep Learning: Distributed Deep Neural Network Training with SparkNet.

  Data Visualization, Deep Learning, KDD-2016, Machine Learning, Neural Networks, Sentiment Analysis

• Beyond One-Hot: an exploration of categorical variables - Dec 8, 2015.
  
  Coding categorical variables into numbers, by assign an integer to each category ordinal coding of the machine learning algorithms. Here, we explore different ways of converting a categorical variable and their effects on the dimensionality of data.

  Data Exploration, Machine Learning, Python, Will McGinnis

• 20 Lessons From Building Machine Learning Systems - Dec 8, 2015.
  
  Data science is not only a scientific field, but also it requires the art and innovation from time to time. Here, we have compiled wisdom learned from developing data science products for over a decade by Xavier Amatriain.

  Pages: 1 2 3

  Devendra Desale, Learning from Data, Machine Learning, Xavier Amatriain

• 50 Useful Machine Learning & Prediction APIs - Dec 7, 2015.
  
  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!

  Pages: 1 2

  API, Data Science, Face Recognition, IBM Watson, Image Recognition, Machine Learning, NLP, Sentiment Analysis

• KDnuggets™ News 15:n39, Dec 2: 7 Steps to Master Machine Learning w. Python; Hardest Part of Data Science - Dec 2, 2015.
  
  7 Steps to Mastering Machine Learning With Python; The hardest parts of data science; Deep Forger: Art Forgery Meets Deep Neural Nets; Bot or Not: an end-to-end data analysis in Python.

  Art, Deep Learning, Machine Learning, Python

• 5 Tribes of Machine Learning – Questions and Answers - Nov 27, 2015.
  
  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.

  Ensemble Methods, Machine Learning, Pedro Domingos, Recommender Systems

• Detecting In-App Purchase Fraud with Machine Learning - Nov 25, 2015.
  
  Hacking applications allow users to make in-app purchases for free. With help from a few big games in the GROW data network we were able to build a model that classifies each purchase as real or fraud, with a very high level of accuracy.

  Fraud Detection, Machine Learning, Online Games

• Using Machine Learning To Predict Gender - Nov 24, 2015.
  
  Here is an experiment from the CrowdFlower AI team, where they used user’s tweeter account link color, description, and a single random tweet with the word “and” or “the” in it and guessed who’s behind the curtain.

  Pages: 1 2

  CrowdFlower, Emoji, Gender, Machine Learning, Twitter

• H2O World 2015 – Day 3 Highlights - Nov 20, 2015.
  
  Highlights from talks delivered by machine learning experts from Fast Forward Labs, H20.ai, Kaiser and Macy's at H2O World held in Mountain View.

  Pages: 1 2

  Advanced Analytics, Data Science Team, H2O, Machine Intelligence, Machine Learning, Predictive Analytics, Skills, Success

• H2O World 2015 – Day 2 Highlights - Nov 19, 2015.
  
  Highlights from talks delivered by machine learning experts from H20.ai, Jawbone, Stanford, Quora & PayPal at H2O World held in Mountain View.

  Pages: 1 2

  Arno Candel, H2O, Machine Learning, Monica Rogati, PayPal, Predictive Analytics, Quora, Stanford, Xavier Amatriain

• 7 Steps to Mastering Machine Learning With Python - Nov 19, 2015.
  
  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!

  Pages: 1 2

  7 Steps, Anaconda, Caffe, Deep Learning, Machine Learning, Matthew Mayo, Python, scikit-learn, Theano

• The Data Science Conference 2015 Highlights - Nov 18, 2015.
  
  Here are the highlights from The Data Science Conference 2015, Nov 12-13 at University of Chicago. A two-day conference on Data Science, big data, machine learning, artificial intelligence & predictive modeling discussions -"for professionals" by professionals.

  Artificial Intelligence, Chicago, Data Science, Highlights, IL, Machine Learning, Predictive Modeling

• H2O World 2015 – Day 1 Highlights - Nov 16, 2015.
  
  Highlights from talks and tutorials delivered by machine learning experts at H2O World 2015 held in Mountain View.

  CA, Data Science, Deep Learning, H2O, Machine Learning, Mountain View, Overfitting, Python, Unicorn

• TensorFlow Disappoints – Google Deep Learning falls shallow - Nov 16, 2015.
  
  Google recently open-sourced its TensorFlow machine learning library, which aims to bring large-scale, distributed machine learning and deep learning to everyone. But does it deliver?

  Pages: 1 2

  Deep Learning, Google, Machine Learning, Matthew Mayo, Python, TensorFlow

• Boeing: Machine Learning Technologist – Level 4/5 - Nov 14, 2015.
  
  A successful candidate will have background in statistics, probability, mathematics, databases, and strong programming skills, including Python, R, Matlab, C, C++, Java are necessary, and will join Boeing R&D center.

  AL, Boeing, Huntsville, Machine Learning, Technologist

• CMU: Assistant Professor in Applied Statistical Machine Learning - Nov 9, 2015.
  
  CMU is seeking both tenure-track and research-track candidates with strong training in statistical machine learning and a demonstrated commitment to bringing methodological innovation to application-driven research.

  Applied Statistics, CMU, Faculty, Machine Learning, PA, Pittsburgh

• What No One Tells You About Real-Time Machine Learning - Nov 9, 2015.
  
  Real-time machine learning has access to a continuous flow of transactional data, but what it really needs in order to be effective is a continuous flow of labeled transactional data, and accurate labeling introduces latency.

  Dmitry Petrov, Machine Learning, Real-time

• 5 Best Machine Learning APIs for Data Science - Nov 5, 2015.
  
  Machine Learning APIs make it easy for developers to develop predictive applications. Here we review 5 important Machine Learning APIs: IBM Watson, Microsoft Azure Machine Learning, Google Prediction API, Amazon Machine Learning API, and BigML.

  Pages: 1 2

  Amazon, API, Azure ML, BigML, DeZyre, Google, IBM Watson, Machine Learning

• Beginners Guide: Apache Spark Machine Learning with Large Data - Nov 5, 2015.
  
  This informative tutorial walks us through using Spark's machine learning capabilities and Scala to train a logistic regression classifier on a larger-than-memory dataset.

  Pages: 1 2 3

  Apache Spark, Dmitry Petrov, Machine Learning

• KDnuggets™ News 15:n36, Nov 4: Integrating R, Python; Neural Net in 11 lines; Top 20 AI/Machine Learning books - Nov 4, 2015.
  
  Integrating Python and R; A Neural Network in 11 lines; Amazon Top 20 Books in AI, Machine Learning; How Big Data is used in Recommendation Systems to change to change our lives; Data Science of IoT.

  AI, Books, Data Visualization, IoT, Machine Learning, Neural Networks, Recommender Systems, Topological Data Analysis

• Amazon Top 20 Books in AI & Machine Learning - Nov 2, 2015.
  
  These are the most popular AI & machine learning books on Amazon. Have a look... you may find something of interest here.

  Amazon, Artificial Intelligence, Book, Machine Learning, Matthew Mayo

• KDnuggets™ News 15:n34, Oct 21: How to Learn Machine Learning; Data Science Ethics? MetaMind MasterMind - Oct 21, 2015.
  
  New Poll: Should Data Science Include Ethics Training?; The Best Advice From Quora on "How to Learn Machine Learning; Big Data + Wrong Method = Big Fail; MetaMind Mastermind Richard Socher: Uncut Interview;

  Ethics, Machine Learning, Richard Socher, Smart City

• Top KDnuggets tweets, Oct 13-19: R vs Python: head to head; Machine Learning for Developers tutorial - Oct 20, 2015.
  
  Machine Learning for Developers - very nice tutorial; R vs #Python: head to head #Data Analytics; Data Science Skills and the Improbable Unicorn Data Scientist; How Tesla AutoPilot learns.

  Machine Learning, Pedro Domingos, Python vs R, Scala, Tesla, Tutorials

• DistrictDataLabs Courses on Data Mining, Machine Learning, R, NLP, Social Media, and more - Oct 17, 2015.
  
  District Data Labs upcoming workshops and courses include Data Mining & Machine Learning with R, Building a Django Data Product, Analyzing Social Media Data with R, and Natural Language Processing with R.

  Arlington, Data Mining, District Data Labs, Django, Machine Learning, NLP, Python, R, Social Media Analytics, VA

• The Best Advice From Quora on ‘How to Learn Machine Learning’ - Oct 15, 2015.
  
  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.

  Pages: 1 2

  Books, Machine Learning, Matthew Mayo, MOOC, Quora, Sean McClure, Xavier Amatriain

• Does Deep Learning Come from the Devil? - Oct 9, 2015.
  
  Deep learning has revolutionized computer vision and natural language processing. Yet the mathematics explaining its success remains elusive. At the Yandex conference on machine learning prospects and applications, Vladimir Vapnik offered a critical perspective.

  Berlin, Deep Learning, Machine Learning, Support Vector Machines, SVM, Vladimir Vapnik, Yandex, Zachary Lipton

• 90+ Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning - Oct 8, 2015.
  
  Stay on top of your data science skills game! Here's a list of 90+ active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.

  Pages: 1 2

  Big Data, Blogs, Data Science, Deep Learning, Hadoop, Machine Learning

• Topological Analysis and Machine Learning: Friends or Enemies? - Sep 29, 2015.
  
  What is the interaction between Topological Data Analysis and Machine Learning ? A case study shows how TDA decomposition of the data space provides useful features for improving Machine Learning results.

  Ayasdi, Machine Learning, random forests algorithm, Topological Data Analysis

• Interview: Michael Brodie – We Can’t Rely on Machines - Sep 28, 2015.
  
  Michael Brodie, a leading database researcher, is convinced that Big Data has more potential than the hype suggests, but also more risks.

  Pages: 1 2

  Big Data, Machine Learning, Michael Brodie, Opportunities, Switzerland, Threat to Humanity

• Machine Learning Course. Learn to build solutions, Delft, Netherlands, 16-20 November - Sep 26, 2015.
  
  This course provides you with practical step-by-step methodology to go beyond theory and learn how to create working Machine Learning solutions.

  Delft, Machine Learning, Netherlands

• The Master Algorithm – new book by top Machine Learning researcher Pedro Domingos - Sep 25, 2015.
  
  Wonderfully erudite, humorous, and easy to read, the Master Algorithm by top Machine Learning researcher Pedro Domingos takes you on a journey to visit the 5 tribes of Machine Learning experts and helps you understand what the Master Algorithm can be.

  Algorithms, Book, Machine Learning, Pedro Domingos

• H2O World 50% off for 24 hours only – Open Source Machine Learning - Sep 23, 2015.
  
  Join machine learning industry leaders, H2O customers, and community in a day of H2O training and two days of talks. 50% OFF valid for 24 hours only.

  CA, H2O, Hilary Mason, Machine Learning, Monica Rogati, Mountain View, Open Source, Robert Tibshirani

• Top KDnuggets tweets, Sep 15-21: Top Machine Learning researcher Pedro Domingos new book: The Master Algorithm - Sep 23, 2015.
  
  Top Machine Learning researcher Pedro Domingos new book: The Master #Algorithm; #Dilbert brilliant take on Character; SentimentBuilder - Free Online Natural #Language Processing Tool.

  Dilbert, Machine Learning, NLP, Pedro Domingos, Quora, Xavier Amatriain, Yoshua Bengio

• Support “Talking Machines” – the best podcast on Machine Learning, Data Science and AI - Sep 20, 2015.
  
  Excitement, and worry, about ML, AI, and data science is at a fever pitch. It’s our responsibility to bring the conversation back to reality, and support the projects that do, or face another ‘winter’.

  Data journalism, Machine Learning, Podcast, Talking Machines

• Top 10 Quora Machine Learning Writers and Their Best Advice - Sep 18, 2015.
  
  Top Quora machine learning writers give their advice on pursuing a career in the field, academic research, and selecting and using appropriate technologies.

  Machine Learning, Quora, random forests algorithm, Top 10, Xavier Amatriain, Yoshua Bengio

• Doing Data Science at Twitter - Sep 16, 2015.
  
  Data scientist career exciting, fulfilling and multidimensional career path. Understand through the journey of a data scientist of twitter about data scientists roles, responsibilities and skills required to perform them.

  Pages: 1 2 3

  A/B Testing, Data Science Skills, Data Science Tools, Machine Learning

• Are you trying to acquire Machine Learning Skills? - Sep 16, 2015.
  
  Embarking on a journey through the lands of machine learning? Here are few important lessons like Feature Engineering, Model tuning, Overfitting, Ensembling etc. which you should keep in mind along the way.

  Boosting, Data Science Skills, edX, Ensemble Methods, Feature Engineering, Machine Learning, MOOC, Overfitting

• Aug 2015 Analytics, Big Data, Data Mining, Data Science Acquisitions, Startup roundup - Sep 11, 2015.
  
  Aug 2015 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: HyperVerge, Top 100 by funding, Deep Genomics, Driveway Software, BigML, and many more.

  BigML, Bitcoin, Datameer, Deep Learning, Funding, Machine Learning, Startups

• 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more - Sep 4, 2015.
  
  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.

  Book, Brendan Martin, Data Mining, Data Science, Free ebook, Machine Learning, Python, R, SQL

• API for Prediction and Machine Learning: poll results and analysis - Sep 1, 2015.
  
  APIs are set procedures which provide easy to use, automated, robust solution to the recurring programming challenges. Here, we analyzed major players in the big data domain are providing machine learning APIs.

  API, Azure ML, H2O, indico, Machine Learning, Poll

• Join machine learning leaders at H2O World, Nov 9-11, early bird rates now - Aug 28, 2015.
  
  Join H2O for 3-day machine learning conference, hear from top experts including Hilary Mason, Rob Tibshirani, and Stephen Boyd, participate in a hackathon and hands-on data science training.

  CA, H2O, Hilary Mason, Machine Learning, Mountain View, Robert Tibshirani

• Gartner 2015 Hype Cycle: Big Data is Out, Machine Learning is in - Aug 28, 2015.
  
  Which are the most hyped technologies today? Check out Gartner's latest 2015 Hype Cycle Report. Autonomous cars & IoT stay at the peak while big data is losing its prominence. Smart Dust is a new cool technology for the next decade!

  Big Data, Citizen Data Scientist, Gartner, Machine Learning

• KDnuggets™ News 15:n28, Aug 26: How long at your Analytics job? Paradoxes of Data Science; Big Data Security - Aug 26, 2015.
  
  New Poll: How long did you stay at your analytics/data science job? Paradoxes of Data Science; HeroX Cognitive Computing Challenge; Information Management 10 IT Security Books for Big Data Scientists.

  Books, Certificate, Competition, Information Management, Machine Learning, Security

• Top KDnuggets tweets, Aug 18-24: Machine Learning Certifications, #DataScience Bootcamps; AshleyMadison Data Analysis - Aug 25, 2015.
  
  Ashley Madison Data analysis: 86% male, 30-46 is the trouble zone; Paradoxes of #DataScience examined; AI Market Overview and more visuals; MachineLearning Certifications and Best #DataScience Bootcamps.

  AI, Ashley Madison, Bootcamp, Certification, edX, Machine Learning, R

• YCML Machine Learning library on Github - Aug 24, 2015.
  
  YCML is a new Machine Learning library available on Github as an Open Source (GPLv3) project. It can be used in iOS and OS X applications, and includes Machine Learning and optimization algorithms.

  Backpropagation, GitHub, iOS, Machine Learning, Open Source, Optimization

• Top /r/MachineLearning Posts, July: Visual Intro to Machine Learning, Google new patent controversy, Deep Learning and famous art - Aug 20, 2015.
  
  A Visual Introduction to Machine Learning, Why Google's new patent applications are alarming, Art with Google's Inceptionism code, Google Photo's algorithm gone wrong and a Neural network tutorial made it to the top this month!

  Art, D3.js, Google, Machine Learning, Patents, Reddit

• Recycling Deep Learning Models with Transfer Learning - Aug 14, 2015.
  
  Deep learning exploits gigantic datasets to produce powerful models. But what can we do when our datasets are comparatively small? Transfer learning by fine-tuning deep nets offers a way to leverage existing datasets to perform well on new tasks.

  Deep Learning, Image Recognition, ImageNet, Machine Learning, Neural Networks, Transfer Learning, Zachary Lipton

• Three Essential Components of a Successful Data Science Team - Aug 10, 2015.
  
  A Data Science team, carefully constructed with the right set of dedicated professionals, can prove to be an asset to any organization,

  Business Analyst, Data Engineer, Data Science Team, Machine Learning, Team

• The Big ‘Big Data’ Question: Hadoop or Spark? - Aug 5, 2015.
  
  With a considerable number of similarities, Hadoop and Spark are often wrongly considered as the same. Bernard carefully explains the differences between the two and how to choose the right one (or both) for your business needs.

  Pages: 1 2

  Apache Spark, Bernard Marr, Data Science Tools, Distributed Systems, Hadoop, Machine Learning, Performance, RDD

• Top KDnuggets tweets, Jul 28 – Aug 03: Very nice Visual Introduction to Machine Learning; Microsoft Capitulation and The End of Windows Everywhere - Aug 4, 2015.
  
  Very nice: A Visual Introduction to #MachineLearning; Microsoft, Capitulation and The End of Windows Everywhere; Data is Ugly - @importio Tales of #DataCleaning; 8 Tools That Show Whats on the Horizon for #Python

  Art, import.io, Machine Learning, Microsoft, Python

• NYC Data Science Academy courses & bootcamps in Data Engineering, Data Science, R, Python, and Machine Learning - Jul 31, 2015.
  
  Upcoming training from NYC Data Science Academy: 6-Week Intensive Data Engineering Bootcamp, 12-Week Data Science Bootcamp, courses in R, Python, Data Science and Machine Learning, and more.

  Apache Spark, Bootcamp, Data Science Education, Hadoop, Machine Learning, New York City, NY, NYC Data Science Academy, Python, R, scikit-learn

• KDnuggets™ News 15:n24, Jul 29: Big Data to Big Profits; Mining Massive Datasets; Data for Humanity - Jul 29, 2015.
  
  From Big Data to Big Profits: A Lesson from Google's Nest; Coursera/Stanford "Mining Massive Datasets", free online course; Data for Humanity: A Request for Support; To Code or Not to Code with KNIME.

  Data Mining, Innovation, Machine Learning, Sentiment Analysis, SIGKDD

• arXiv.org and the 24 Hour Research Cycle - Jul 21, 2015.
  
  ArXiv.org gives researchers the ability to instantly publish research, free of peer review and the publication cycle. This capability offers both advantages and pitfalls. We should warily eye the 24-7 news cycle as a cautionary tale for how this could go wrong.

  arXiv, Data Science, Machine Learning, Research, Zachary Lipton

• 50+ Data Science and Machine Learning Cheat Sheets - Jul 14, 2015.
  
  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.

  Cheat Sheet, Data Science, Django, Hadoop, Machine Learning, Python, R

• Can deep learning help find the perfect date? - Jul 10, 2015.
  
  When a Machine Learning PhD student at University of Montreal starts using Tinder, he soon realises that something is missing in the dating app - the ability to predict to which girls he is attracted. Harm de Vries applies Deep Learning to assist in the pursuit of the perfect match.

  Deep Learning, ICML, Love, Machine Learning, Online Dating, Predictive Analytics

• Standardizing the World of Machine Learning Web Service APIs - Jul 8, 2015.
  
  We introduce Protocols and Structures for Inference (PSI) API specification which enables delivering flexible Machine Learning by specifying how datasets, learning algorithms and predictors can be presented as web resources.

  API, Machine Learning, RESTful API, Web services

• Top /r/MachineLearning Posts, June: Neural Network Generated Images, Free Data Science Books, Super Mario World - Jul 2, 2015.
  
  Generating images with neural networks, free data science books, machine learning for playing Mario, implementing neural networks in Python, and video generation based on terms were all covered this month on /r/MachineLearning.

  Convolutional Neural Networks, Data Science, Free ebook, Machine Learning, Neural Networks, numpy, Python, Reddit, Video Games, Youtube

• Top KDnuggets tweets, Jun 22-29: Kaggle Machine Learning Tutorial in R; 50 Smartest Companies – shaping the #technology landscape - Jun 30, 2015.
  
  Free @Kaggle #MachineLearning Tutorial in R - learn how to compete; 50 Smartest Companies - shaping the #technology landscape; Excellent Tutorial on #Sequence #Learning using #Recurrent #Neural #Networks; How a #DataScientist buys a #car.

  Kaggle, Machine Learning, R, Recurrent Neural Networks, Tesla, Tutorial, Uber

• Using Ensembles in Kaggle Data Science Competitions – Part 1 - Jun 25, 2015.
  
  How to win Machine Learning Competitions? Gain an edge over the competition by learning Model Ensembling. Take a look at Henk van Veen's insights about how to get improved results!

  Pages: 1 2

  Competition, Correlation, Data Science, Kaggle, Machine Learning, Use Cases

• Top 20 R Machine Learning and Data Science packages - Jun 24, 2015.
  
  We list out the top 20 popular Machine Learning R packages by analysing the most downloaded R packages from Jan-May 2015.

  CRAN, Data Science, Machine Learning, R, R Packages, Top list

• Top 10 Machine Learning Videos on YouTube - Jun 23, 2015.
  
  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.

  Andrew Ng, Computer Vision, Deep Learning, Geoff Hinton, Google, Grant Marshall, Machine Learning, Neural Networks, Robots, Video Games, Youtube

• Model-Based Machine Learning, Free Early Book Draft - Jun 22, 2015.
  
  Are you a newbie to machine Learning? Here's a fresh new perspective to learning it. It's called "Model-based machine Learning". It makes the process of creating effective machine learning solutions much more systematic for any newcomer!

  Book, Free ebook, Machine Learning

• Amazon: Machine Learning – Technical Project Manager (TPM) - Jun 19, 2015.
  
  The Amazon machine learning team's goal is to make machine learning accessible to developers of all skill levels. You will own and drive key programs for building machine learning solutions to high-impact business problems.

  Amazon, Machine Learning, Project Manager, Seattle, WA

• In Machine Learning, What is Better: More Data or better Algorithms - Jun 17, 2015.
  
  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.

  Big Data Hype, Data Quality, IMDb, Machine Learning, Quora, Xavier Amatriain

• Top KDnuggets tweets, Jun 09-15: Which Big Data, Data Mining, Data Science Tools go together? Good Comparison of ML classifiers - Jun 16, 2015.
  
  Which #BigData, #DataMining and #DataScience Tools go together? Good Comparison of ML classifiers: Decision Trees, Regression, SVM, #NeuralNets; In #machinelearning, what is better more #data or better algorithms? Need both.

  Data Mining Software, Data Visualization, Decision Boundaries, Machine Learning, Painting

• Not So Fast: Questioning Deep Learning IQ Results - Jun 15, 2015.
  
  Did deep learning just leap towards human intelligence? Not so fast.

  arXiv, Deep Learning, IQ, Machine Learning, MIT, Zachary Lipton

• Decision Boundaries for Deep Learning and other Machine Learning classifiers - Jun 15, 2015.
  
  H2O, one of the leading deep learning framework in python, is now available in R. We will show how to get started with H2O, its working, plotting of decision boundaries and finally lessons learned during this series.

  Decision Boundaries, Deep Learning, H2O, Machine Learning, SVM

• Top KDnuggets tweets, Jun 2-8: Starting salaries for #DataScientists have gone north of $200,000 - Jun 9, 2015.
  
  Starting salaries for #DataScientists have gone north of $200K; Top 20 #Python #MachineLearning #OpenSource Projects; Neural Networks and Deep Learning, free online book (draft); #Airbnb announces #Aerosolve, an #OpenSource #MachineLearning #software package.

  AirBnB, Free ebook, Machine Learning, Open Source, Python, Salary

• Best Big Data, Data Science, Data Mining, and Machine Learning podcasts - Jun 9, 2015.
  
  We present the top 12 Data Science & Machine Learning related Podcasts by popularity on iTunes. Check out latest episodes to stay up-to-date & become a part of the data conversations!

  Artificial Intelligence, Big Data, Data Science, Machine Learning, Podcast

• Top 20 Python Machine Learning Open Source Projects - Jun 1, 2015.
  
  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.

  GitHub, Machine Learning, Open Source, Python, scikit-learn

• Top /r/MachineLearning Posts, May: Unreasonable Effectiveness of Recurrent Neural Networks, Time-Lapse Mining - Jun 1, 2015.
  
  The Unreasonable Effectiveness of Recurrent Neural Networks, Time-lapse mining from Net photos, Deep Learning Textbook Part I, Kaggle R Tutorial, and Free Machine Learning ebooks.

  Deep Learning, Free ebook, Grant Marshall, Kaggle, Machine Learning, Neural Networks, R, Recurrent Neural Networks, Reddit

• Will the Real Data Scientists Please Stand Up? - May 18, 2015.
  
  Job postings for data scientists are everywhere. But what is a data scientist? I present a few archetypes.

  Data Science, Data Science Jargon, Data Science Skills, Machine Learning, Zachary Lipton

• Machine Learning Wars: Amazon vs Google vs BigML vs PredicSis - May 12, 2015.
  
  Comparing 4 Machine Learning APIs: Amazon Machine Learning, BigML, Google Prediction API and PredicSis on a real data from Kaggle, we find the most accurate, the fastest, the best tradeoff, and a surprise last place.

  Pages: 1 2

  Amazon, BigML, Google, Louis Dorard, Machine Learning, PredicSis

• Interview: Alison Burnham, Scorebig on Optimal, Real-time Pricing through Analytics - May 8, 2015.
  
  We discuss Analytics at ScoreBig, company’s business model, unexpected insights, challenges in customer value management, advice, and more.

  Advice, Analytics, Big Data, Career, Customer Analytics, Customer Value, Interview, Machine Learning, Pricing, Real-time

• Boeing: Advanced Info Technologist in Machine Learning - Apr 28, 2015.
  
  This position is focusing on Machine Learning and Data Mining with a strong background in statistics, probability, mathematics, databases, and strong programming skills. Help build something better for yourself, for our customers and for the world.

  AL, Boeing, Huntsville, Machine Learning, Technologist

• Top /r/MachineLearning Posts, Apr 19-25: Neural nets for nipple detection; NHL Goal celebration hack - Apr 27, 2015.
  
  Convolutional neural nets and Android App for nipple detection (NSFW), NHL goal detection, Geoff Hinton recent AI talk, top machine learning podcasts, and matrix multiplication in deep learning.

  Deep Learning, Geoff Hinton, Grant Marshall, Machine Learning, Podcast, Reddit

• Interview: Michael Li, Data Incubator on Bridging the Data Science Skills Gap between Academia and Industry - Apr 21, 2015.
  
  We discuss the response from hiring companies, recommendations for aspirants, retaining data science talent, advice, and more.

  Academics, Advice, Career, Data Science Skills, Industry, Interview, Machine Learning, Recommendations, Trends

• Cloud Machine Learning Wars: Amazon vs IBM Watson vs Microsoft Azure - Apr 16, 2015.
  
  Amazon recently announced Amazon Machine Learning, a cloud machine learning solution for Amazon Web Services. Able to pull data effortlessly from RDS, S3 and Redshift, the product could pose a significant threat to Microsoft Azure ML and IBM Watson Analytics.

  Pages: 1 2

  Amazon, Azure ML, IBM Watson, Logistic Regression, Machine Learning, MetaMind, Prediction, Regression, Zachary Lipton

• Booking: Data Scientist – Machine Learning - Apr 15, 2015.
  
  Work side by side with Developers, Designers and Product Owners to translate terabytes of data into unforgettable holidays for millions of people around the globe. Generous worldwide relocation package.

  Amsterdam, Booking.com, Data Scientist, Machine Learning, Netherlands

• Top /r/MachineLearning Posts, Apr 5-11: Amazon Machine Learning, Numerical Optimization, and Conditional Random Fields - Apr 14, 2015.
  
  Amazon Machine Learning as a Service, Numerical Optimization, Extracting data from NYTimes recipes, Intro to Machine Learning with sci-kit, and more.

  Amazon, Deep Learning, Kaggle, Machine Learning, Probability, Python, Reddit, scikit-learn

• Awesome Public Datasets on GitHub - Apr 6, 2015.
  
  A long, categorized list of large datasets (available for public use) to try your analytics skills on. Which one would you pick?

  Pages: 1 2

  Datasets, Finance, GitHub, Government, Machine Learning, NLP, Open Data, Time series data

• Poll: Machine Learning APIs - Apr 4, 2015.
  
  Poll from Bart Baesens at KU Leuven asks about your usage of Machine Learning APIs and other predictive analytics tools.

  API, Bart Baesens, Machine Learning, Poll

• Top KDnuggets tweets, Mar 26-29: The Basic Recipe for #MachineLearning in one slide; The Grammar of Data Science – comparing Python and R - Mar 30, 2015.
  
  The Basic Recipe for Machine Learning in one slide; The Grammar of Data Science - comparing Python and R; Uber Data Science team reveals why taxis may never be able to compete; Comparing @PredictionIO (Open Source Version) vs Microsoft Azure Machine Learning.

  Azure ML, Machine Learning, PredictionIO, Python, Python vs R, R, Uber

• PredictionIO (Open Source Version) vs Microsoft Azure Machine Learning - Mar 26, 2015.
  
  Azure Machine Learning and PredictionIO are tools that both have similar visions and similar features, but when digging deeper you’ll notice key differences and key advantages to each.

  Pages: 1 2 3

  Azure ML, Louis Dorard, Machine Learning, Marketplace, Microsoft Azure, PredictionIO

• More Free Data Mining, Data Science Books and Resources - Mar 25, 2015.
  
  More free resources and online books by leading authors about data mining, data science, machine learning, predictive analytics and statistics.

  Book, Data Mining, Data Science, Free ebook, Machine Learning

• Interview: Brad Klingenberg, StitchFix on Decoding Fashion through Analytics and ML - Mar 21, 2015.
  
  We discuss the challenges in making personal styling recommendations, unexpected insights, interesting trends, motivation, advice, desired qualities in data scientists and more.

  Advice, Analytics, Brad Klingenberg, Data Science, Fashion, Interview, Machine Learning, Stitch Fix, Trends

• Interview: Vince Darley, King.com on the Serious Analytics behind Casual Gaming - Mar 18, 2015.
  
  We discuss key characteristics of social gaming data, ML use cases at King, infrastructure challenges, major problems with A-B testing and recommendations to resolve them.

  A/B Testing, Analytics, Gaming, Infrastructure, King.com, Machine Learning, Predictive Analysis, Vince Darley

• NYC Data Science Courses, Bootcamps, Meetups - Mar 17, 2015.
  
  NYC Data Science Academy spring schedule includes 3 classes, 3 Meetups, 7 bootcamp events on Data Science, R, Python, Machine Learning, scikit-learn, and related topics.

  Bootcamp, Knewton, Machine Learning, Meetup, New York City, NY, NYC Data Science Academy, Python, R, scikit-learn

• D-Wave Systems (Quantum Computing): Machine Learning Researcher - Mar 14, 2015.
  
  The science fiction future is here. Help design and implement novel machine learning and deep learning algorithms that leverage the power of the D-Wave quantum computer.

  BC, Burnaby, Canada, D-Wave Systems, Deep Learning, Machine Learning, Quantum Computing, Researcher

• Report – MLconf: what industry leaders say about machine learning - Mar 14, 2015.
  
  MLconf hosted in 4 different cities, NYC, Seattle, Atlanta and San Francisco with speakers from big, established companies and from emerging startups, bringing more ideas and experience into the game.

  CA, Deep Learning, Facebook, Machine Learning, MLconf, Netflix, New York City, NY, San Francisco

• Top KDnuggets tweets, Mar 09-11: Learning path from noob to Kaggler in Python; 10 steps for success in Kaggle competitions - Mar 12, 2015.
  
  Comprehensive learning path from noob to Kaggler in Python; 10 steps for success in Kaggle competitions; Machine learning packages #Python #Java #BigData #Lua #Clojure #Scala, R; Very useful LeaRning Path on R - Step by Step Guide.

  Barcelona, Kaggle, Learning Path, Machine Learning, Online Education, Prismatic, Python, R

• Machine Learning Table of Elements Decoded - Mar 11, 2015.
  
  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.

  Big Data Software, Java, Julia, Machine Learning, NLP, Python, R, Scala, scikit-learn, Weka

• KDnuggets™ News 15:n08, Mar 11: 7 common Machine Learning mistakes; Statistical Reasoning - Mar 11, 2015.
  
  7 common mistakes when doing Machine Learning; 10 Predictive Analytics Influencers; Kaiser Fung on Why Statistical Reasoning is more important than Number Crunching; The Elements of Data Analytic Style - checklist; KDD-2017.

  Influencers, Jurgen Schmidhuber, Kaiser Fung, KDD-2017, Machine Learning, Mistakes, Predictive Analytics

• ICS (Prague): AVAST Fellowship in machine learning and data science - Mar 9, 2015.
  
  Contribute to a range of projects including machine learning applications in computer security and antivirus software using big data analysis of behavioral data.

  antivirus, AVAST, Czech Republic, Fellowship, ICS, Machine Learning, Malware, Prague

• 7 common mistakes when doing Machine Learning - Mar 7, 2015.
  
  In statistical modeling, there are various algorithms to build a classifier, and each algorithm makes a different set of assumptions about the data. For Big Data, it pays off to analyze the data upfront and then design the modeling pipeline accordingly.

  Pages: 1 2

  Machine Learning, Mistakes, Overfitting, Regression, SVM

• Interview: Lei Shi, ChinaHR.com on Unraveling Insights from Unstructured Data - Mar 7, 2015.
  
  We discuss challenges in leveraging Big Data, important attributes while profiling employers and job seekers, competitive landscape, desired skills in data scientists and more.

  Competition, Decision Making, Hiring, Interview, Jobs, Machine Learning, Trends

• Top /r/Machine Learning Posts, February: Automating Tinder, Jurgen Schmidhuber, and Shazam - Mar 5, 2015.
  
  Automating Tinder with Eigenfaces, the elephant in the room of Machine Learning, the Jürgen Schmidhuber AMA, and Shazam's music recognition algorithm make up the top posts in the last month on /r/MachineLearning.

  Deep Learning, Eigenface, Jurgen Schmidhuber, Machine Learning, Reddit, Tinder

• Top /r/MachineLearning Posts, Feb 22-28: Jurgen Schmidhuber AMA and Machine Learning Done Wrong - Mar 4, 2015.
  
  The Jürgen Schmidhuber AMA begins taking questions, machine learning done wrong, GPUs for deep learning, Google opens its native MapReduce capabilities, and Google publishes its DeepMind paper this week on /r/MachineLearning

  Deep Learning, DeepMind, GPU, Jurgen Schmidhuber, Machine Learning, Reddit

• KDnuggets™ News 15:n07, Mar 4: Analytics/Data Science Salaries; Machine Learning Flaws; Strata Highlights - Mar 4, 2015.
  
  Analytics, Data Mining, Data Science salary survey by region and role; Strata + Hadoop World 2015 San Jose - Highlights; All Machine Learning Models Have Flaws; Interview: Ted Dunning, MapR on The Real Meaning of Real-Time in Big Data, and more.

  Deep Learning, Hadoop, Machine Learning, Poll, Salary, Strata, Ted Dunning

• Interview: Ted Dunning, MapR on Apache Mahout & Technology Landscape in ML - Mar 3, 2015.
  
  We discuss Apache Mahout, its comparison with Spark and H2O, trends, advice, desired qualities in data scientists and more.

  Advice, Apache Mahout, Apache Spark, H2O, Interview, Machine Learning, MapR, Ted Dunning

• All Machine Learning Models Have Flaws - Mar 3, 2015.
  
  This classic post examines what is right and wrong with different models of machine learning, including Bayesian learning, Graphical Models, Convex Loss Optimization, Statistical Learning, and more.

  Bayesian, Decision Trees, Gradient Descent, John Langford, Machine Learning, Statistical Learning

• PredictionIO: Machine Learning Engineer (Evangelist) - Feb 26, 2015.
  
  Are you passionate about machine learning and open source? Do you have the ability to engage other developers and data scientists? If yes, read on ...

  API, CA, Machine Learning, Open Source, PredictionIO, San Francisco, Scala, USA