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• Using Ensembles in Kaggle Data Science Competitions- Part 3 - Jun 27, 2015.
  
  Earlier, we showed how to create stacked ensembles with stacked generalization and out-of-fold predictions. Now we'll learn how to implement various stacking techniques.

  Competition, Data blending, Kaggle, Logistic Regression, Predictive Models

• Excellent Tutorial on Sequence Learning using Recurrent Neural Networks - Jun 26, 2015.
  
  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.

  Recurrent Neural Networks, Text Classification

• Open Source Enabled Interactive Analytics: An Overview - Jun 26, 2015.
  
  Explaining the aspects of creating an interactive data driven dashboard using open source technologies i.e. MongoDB, D3.Js, DC.JS and Node JS.

  Anmol Koul, D3.js, Data Visualization, Javascript, MongoDB

• Using Ensembles in Kaggle Data Science Competitions – Part 2 - Jun 26, 2015.
  
  Aspiring to be a Top Kaggler? Learn more methods like Stacking & Blending. In the previous post we discussed about ensembling models by ways of weighing, averaging and ranks. There is much more to explore in Part-2!

  Competition, Data blending, Data Science, Kaggle, Netflix

• Top 20 R packages by popularity - Jun 25, 2015.
  
  Wondering which are the most popular R packages? Here's an analysis based on most downloaded R packages from Jan to May 2015 to identify the top trending packages in the R world!

  CRAN, R, R Packages, Top list

• 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

• Popular Deep Learning Tools – a review - Jun 18, 2015.
  
  Deep Learning is the hottest trend now in AI and Machine Learning. We review the popular software for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch.

  Convolutional Neural Networks, CUDA, Deep Learning, GPU, Pylearn2, Python, Ran Bi, Theano, Torch

• 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

• Interview: Joseph Babcock, Netflix on Genie, Lipstick, and Other In-house Developed Tools - Jun 16, 2015.
  
  We discuss role of analytics in content acquisition, data architecture at Netflix, organizational structure, and open-source tools from Netflix.

  Data Science, ETL, In-house, Interview, Joseph Babcock, Netflix, Open Source, Tools

• Interview: Joseph Babcock, Netflix on Discovery and Personalization from Big Data - Jun 15, 2015.
  
  We discuss the steps involved in Discovery process at Netflix, impact due to multitude of devices, system generated logs, and surprising insights.

  Experimentation, Insights, Interview, Joseph Babcock, Knowledge Discovery, Netflix, Personalization

• Cognitive Computing: Solving the Big Data Problem? - Jun 12, 2015.
  
  With a shortage of data scientists, what are the alternatives for making sense of Big Data? We examine Cognitive Computing, its strengths, and how it can fit into the current Big Data landscape.

  Cognitive Computing, DeepMind, Google, IBM Watson, Qualcomm, Rick Delgado

• Which Big Data, Data Mining, and Data Science Tools go together? - Jun 11, 2015.
  
  We analyze the associations between the top Big Data, Data Mining, and Data Science tools based on the results of 2015 KDnuggets Software Poll. Download anonymized data and analyze it yourself.

  Apache Spark, Data Mining Software, Excel, Hadoop, Knime, Poll, Python, R, RapidMiner, SQL

• Love, Sex and Predictive Analytics - Jun 4, 2015.
  
  Here, we are trying to understand the working mechanisms of dating sites, algorithms used and role of predictive analytics while matchmaking. We have also gleaned some interesting analytical insights from them.

  Love, Match.com, OkCupid, Online Dating, Predictive Analytics, Recommendation, Tinder

• Top 30 Social Network Analysis and Visualization Tools - Jun 1, 2015.
  
  We review major tools and packages for Social Network Analysis and visualization, which have wide applications including biology, finance, sociology, network theory, and many other domains.

  Pages: 1 2 3

  Data Science Tools, Graph Visualization, Social Network Analysis

• 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