2015 Mar News, Features
All (116) | Courses, Education (9) | Meetings (14) | News, Features (22) | Opinions, Interviews, Reports (47) | Publications (7) | Software (2) | Top Tweets (8) | Webcasts (7)
- Top /r/MachineLearning Posts, Mar 22-28: Deep Learning flaws & Security, DeepMind Publications, and Keras - Mar 30, 2015.
Computer Vision security issues, DeepMind, statistics with Python, hacking on neural networks, and Keras, a neural network library are all topics on top of /r/MachineLearning this week.
- Top stories for Mar 22-28: More Free Data Mining, Data Science Books; PredictionIO vs Microsoft Azure Machine Learning - Mar 29, 2015.
More Free Data Mining, Data Science Books and Resources; PredictionIO (Open Source Version) vs Microsoft Azure Machine Learning; Do We Need More Training Data or More Complex Models? Data science done well looks easy, which is a big problem.
- Database Pioneer Michael Stonebraker Wins ACM Turing Award, Computing “Nobel Prize” - Mar 25, 2015.
Michael Stonebraker, a database pioneer and a serial entrepreneur, won the 2014 ACM Turing Award (which carries $1 million prize) for fundamental contributions to the concepts and practices in modern database systems.
- Top stories for Mar 15-21: Deep Learning for Text Understanding from Scratch; White House on Big Data and Differential Pricing - Mar 22, 2015.
Deep Learning for Text Understanding from Scratch; 7 common mistakes when doing Machine Learning; White House report on Big Data and Differential Pricing; Why Data Gravity Cannot be Ignored.
- 2015 SIGKDD Data Science/Data Mining PhD Dissertation Award – Nominations due Apr 30 - Mar 21, 2015.
This annual award by ACM SIGKDD seeks to recognize outstanding research by doctoral candidates in the field of data mining, data science, and knowledge discovery. Nominations due Apr 30.
- Top /r/MachineLearning Posts, Mar 8-14: Word vectors, Hardware for Deep Learning, and Neural Graphics Engines - Mar 19, 2015.
Word vectors in NLP, Machine Learning's place in programming, hardware for deep learning, Machine Learning interviews, and neural graphics engines are all topics covered this week on /r/MachineLearning.
- Ontotext Introduces the S4 Developer Challenge - Mar 17, 2015.
The challenge will award a cash prize to developers that write the most interesting demo, application or show case utilizing the S4 capabilities for text analytics, linked data and knowledge graphs. Submissions due Mar 31.
- Top stories for Mar 8-14: 7 common Machine Learning mistakes; Deep Learning for Text Understanding from Scratch - Mar 15, 2015.
7 common mistakes when doing Machine Learning; Deep Learning for Text Understanding from Scratch; SQL-like Query Language for Real-time Streaming Analytics; 10 Steps to Success in Kaggle Data Science Competitions.
- New Poll: Computing platform for your analytics, data mining, data science work or research - Mar 14, 2015.
New KDnuggets Poll is asking: What computing platform you use for analytics, data mining, data science work or research? Please vote.
- Participate in the Rexer Analytics 2015 Data Miner Survey - Mar 14, 2015.
Data Analysts, Predictive Modelers, Data Scientists, Data Miners, and all other types of analytic professionals, students, and academics - please participate in the Rexer Analytics 2015 Data Miner Survey.
- Cartoon: US Chief Data Scientist Most Difficult Challenge - Mar 13, 2015.
New KDnuggets cartoon looks at the most difficult challenge facing the first US Chief Data Scientist DJ Patil @dpatil.
- Feb 2015 Analytics, Big Data, Data Mining Acquisitions and Startups Activity - Mar 12, 2015.
Feb 2015 acquisitions, startups, and company activity in Analytics, Big Data, Data Mining, and Data Science: @Kaggle cuts 1/3 of staff, Infosys buys Panaya, RapidMiner gets $15M, Palantir buys Fancy That, Hitachi buys Pentaho, and more.
- Top stories for Mar 1-7: All Machine Learning Models Have Flaws; Analytics, Data Mining, Data Science professionals salary - Mar 9, 2015.
All Machine Learning Models Have Flaws; Analytics, Data Mining, Data Science professionals well compensated; 7 common mistakes when doing Machine Learning; Interviews with Ted Dunning (MapR) and Kaiser Fung (junkcharts).
- Top /r/MachineLearning Posts, Mar 1-7: Stanford Deep Learning for NLP, Machine Learning with Scikit-learn - Mar 9, 2015.
This week on /r/MachineLearning, we have a new NLP-focused deep learning course from Stanford, an introduction to scikit-learn, visualization of music collections, an implementation of DeepMind, and NLP using deep learning and Torch.
- GISCUP: GIS-focused algorithm competition at ACM SIGSPATIAL GIS 2015 - Mar 6, 2015.
Route planner in real-time one of the most popular web GIS services in use today, and 2015 contest is to find shortest path under polygonal obstacles.
- 10 Predictive Analytics Influencers You Need to Know - Mar 5, 2015.
A list of Predictive Analytics Influencers based on Twitter activity around “#PredictiveAnalytics” and “Predictive Analytics”: Gregory Piatetsky, Vineet Vashishta, Aki Kakko and more.
- 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.
- Top stories in February: 10 things statistics taught about big data; Gartner Analytics MQ: gainers and losers - Mar 5, 2015.
10 things statistics taught us about big data analysis; Data Science's Most Used, Confused, and Abused Jargon; Gartner Analytics MQ: gainers and losers; My Brief Guide to Big Data and Predictive Analytics for non-experts.
- 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
- Analytics, Data Mining, Data Science professionals well compensated - Mar 3, 2015.
US, Canada, and Australian analytics professionals are paid the most, with US/Canada Industry Data Science Managers earning on average $177K, Industry Data Scientists $126K, Academic Researchers $119K, and Data Analysts $86K.
- Top stories for Feb 22-28: Gartner 2015 MQ for Advanced Analytics: gainers and losers; History of Data Science Infographic - Mar 1, 2015.
Gartner 2015 Magic Quadrant for Advanced Analytics Platforms: who gained and who lost; History of Data Science Infographic in 5 strands; Interview: David Kasik, Boeing on Data Analysis vs Data Analytics.
- Additions to KDnuggets Directory in February - Mar 1, 2015.
Big Data Paris, Wharton Conf: Successful Applications of Customer Analytics, analytics consulting firms, Georgetown MS in Analytics, MSc in Data Science in France, and more meetings, companies, education, and solutions.