[Continually Updated] MastersInDataScience.org has culled together a list of 23 of the best US Universities/Colleges that offer a Masters in Data Science. Read More
This article is several years old, but it’s still very relevant today. I get asked this question all the time by students. Hope you find it helpful. – Ted
Martin Heller, Contributing Editor, InfoWorld (2017) reviews half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and TensorFlow.
VIDEO | Apache Flink: A Quick Guide to the Next Generation Stream Processing Platform with Dr. Vladimir Bacvanski’s, founder of SciSpike, a company doing custom development, consulting and training. He is the author of the O’Reilly course “Introduction to Big Data”. Watch Video
“TRANSFER LEARNING” From The Harvard Business Review – using the recent Presidential Election & lack of data to illustrate Transfer Learning: “a field that helps to solve these problems by offering a set of algorithms that identify the areas of knowledge which are “transferable” to the target domain. This broader set of data can […]
VIDEOs From the DataEngConf NYC in November. “Demystifying Deep Learning with Visualizations” (44 min) AND “Python Data Wrangling: Preparing for the Future” (37 min).
Data Science Central is best online publication/blog for Data Science. Here are most popular articles and resources from 2016. Enjoy! Read More
IN THIS FOURTH EDITION of the O’Reilly Data Science Salary Survey. They analyzed input from 983 respondents working in the data space, across a variety of industries— representing 45 countries and 45 US states.
Through the results of their 64-question survey, They’ve explored which tools data scientists, analysts, and engineers use, which tasks they engage in, and of course—how much they make. READ MORE
Scala World 2016 took place in the UK in September – Here Martin Odersky, the creator of the Scala programming language gives the keynote. And link to other videos Read More
Machine Learning is at the core of data science and we see it’s applications all over now (i.e. recommender engines, etc.). As Pedro Domingos’s Professor of Computer Science U. Washington writes in the piece, “In reality, the main purpose of machine learning is to predict the future.” It’s important to be aware of the MYTHs associated with Machine Learning. Read More