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Data Science 101: GPU Programming for Beginners

The presentation below is an educational resource that sets the stage for parallel programming with GPUs (graphics processing units) and was sponsored by the Center for Astrophysics and Supercomputing at Swinburne University of Technology. GPUs are becoming quite popular for the implementation of deep learning solutions.

Data Science 101: General Learning Algorithms

In the presentation below, Dr. Demis Hassabis from Google DeepMind delivered a talk on “General Learning Algorithms” to the Royal Society in London on May 22, 2015. Hassabis was the co-founder and CEO of DeepMind, a neuroscience-inspired AI company, bought by Google in Jan 2014.

Book Review: Why – A Guide to Finding and Using Causes

A new book, “ Why: A Guide to Finding and Using Causes ,” by Stevens Institute of Technology assistant professor of computer science Samantha Kleinberg is a necessary addition to any data scientist’s bookshelf as it helps bring focus to the dreaded “correlation does not imply causation” conundrum that affects our understanding of data-centric problems.

Data Science and Statistics: Different Worlds?

The video presentation below, courtesy of the Royal Statistical Society, includes a panel of distinguished practitioners to bring their own perspectives on important issues surrounding the growing field of data science.

Coursera Announces First MOOC-Based Master’s Degree in Data Science

Coursera, a leading online education company known for massive open online courses (MOOCs), today announced a professional data science master’s degree from the University of Illinois at Urbana-Champaign.

Becoming a Data Scientist

Here is a compelling interview with data scientist Will Kurt, courtesy of the Becoming a Data Scientist Podcast series. Kurt talks about his path from English & Literature and Library & Information Science degrees to becoming the Lead Data Scientist at KISSmetrics.

Introduction to GPU Computing

As the use of GPUs continues to rise in fields like deep learning, we thought it would be useful to readers not yet familiar with this technology to offer the “Introduction to GPU Computing” presentation below.

Architecting Predictive Algorithms for Machine Learning

In the presentation below, Seth Juarez of DevExpress discusses architecting predictive algorithms for machine learning.

Using Excel Versus Using R

Trying to show the data analysis package R is no more scary than Excel, John Mount of the Win-Vector blog shows a simple analysis both in Excel and in R.

Data Science 101: Recursive Deep Learning

In the talk below, Recursive Deep Learning for Modeling Compositional and Grounded Meaning, Richard Socher, Founder, MetaMind describes deep learning algorithms that learn representations for language that are useful for solving a variety of complex language tasks.