Using Ensembles in Kaggle Data Science Competitions- Part 3
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.
on Jun 27, 2015 in Competition, Data blending, Kaggle, Logistic Regression, Predictive Models
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.
on Jun 26, 2015 in Recurrent Neural Networks, Text Classification
Open Source Enabled Interactive Analytics: An Overview
Explaining the aspects of creating an interactive data driven dashboard using open source technologies i.e. MongoDB, D3.Js, DC.JS and Node JS.
on Jun 26, 2015 in Anmol Koul, D3.js, Data Visualization, Javascript, MongoDB
Using Ensembles in Kaggle Data Science Competitions – Part 2
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!
on Jun 26, 2015 in Competition, Data blending, Data Science, Kaggle, Netflix
Top 20 R packages by popularity
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!
on Jun 25, 2015 in CRAN, R, R Packages, Top list
Top 20 R Machine Learning and Data Science packages
We list out the top 20 popular Machine Learning R packages by analysing the most downloaded R packages from Jan-May 2015.
on Jun 24, 2015 in CRAN, Data Science, Machine Learning, R, R Packages, Top list
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.
on Jun 23, 2015 in 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
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.
on Jun 18, 2015 in Convolutional Neural Networks, CUDA, Deep Learning, GPU, Pylearn2, Python, Ran Bi, Theano, Torch
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.
on Jun 17, 2015 in Big Data Hype, Data Quality, IMDb, Machine Learning, Quora, Xavier Amatriain
Interview: Joseph Babcock, Netflix on Genie, Lipstick, and Other In-house Developed Tools
We discuss role of analytics in content acquisition, data architecture at Netflix, organizational structure, and open-source tools from Netflix.
on Jun 16, 2015 in Data Science, ETL, In-house, Interview, Joseph Babcock, Netflix, Open Source, Tools
Interview: Joseph Babcock, Netflix on Discovery and Personalization from Big Data
We discuss the steps involved in Discovery process at Netflix, impact due to multitude of devices, system generated logs, and surprising insights.
on Jun 15, 2015 in Experimentation, Insights, Interview, Joseph Babcock, Knowledge Discovery, Netflix, Personalization
Cognitive Computing: Solving the Big Data Problem?
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.
on Jun 12, 2015 in Cognitive Computing, DeepMind, Google, IBM Watson, Qualcomm, Rick Delgado
Which Big Data, Data Mining, and Data Science Tools go together?
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.
on Jun 11, 2015 in Apache Spark, Data Mining Software, Excel, Hadoop, Knime, Poll, Python, R, RapidMiner, SQL
Love, Sex and Predictive Analytics
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.
on Jun 4, 2015 in Love, Match.com, OkCupid, Online Dating, Predictive Analytics, Recommendation, Tinder
Top 30 Social Network Analysis and Visualization Tools
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.
on Jun 1, 2015 in Data Science Tools, Graph Visualization, Social Network Analysis
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.
on Jun 1, 2015 in GitHub, Machine Learning, Open Source, Python, scikit-learn
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