This book has been written in layman’s terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, they stick to intuitive explanations and visuals.
“This list of 500+ was started in 2012, updated in 2014 and also very recently according to the author. It was compiled by 101.datascience.community, and broken down by degree (master / bachelor / certificate / doctorate) and location (online / on-site.)” – Source Data Science Central Read More
VIDEO | NYC Machine Learning Meetup 2016 | Dan Melamed “How To Learn From What Your Users Might Not See”
At the Machine Learning Meetup in NYC, Dan Melamed gave a machine learning talk titled: “How To Learn From What Your Users Might Not See”. This talk will focus on contextual bandits and their applications.
In this tutorial, Dan will show how to learn from such data in a principled, efficient, and unbiased manner. The techniques that he will describe were largely responsible for a click-thru rate gain of over 25% on MSN.com. Watch Video
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
In 2013, Airbnb had a small, centralized team of five data scientists serving the data needs of the company. Since then, they have grown to become one of the largest, most innovative startup teams with over 70 data scientists now serving separate business units. In addition to setting a consistently high bar on new hires and focusing on technical mentorship from peers, the structure of the organization has been key to successful growth. Read More
Kaggle is a community of almost 450K data scientists who have built nearly 2 million machine learning models to participate in its competitions. Data scientists come to Kaggle to learn, collaborate and develop the state of the art in machine learning. This talk will cover some of the lessons on winning techniques we have learned from the Kaggle community. Watch Video
(Re-post) Got a need for speed processing Big Data? In this video talk given at the Apache Flink Meetup in NYC, Slim Baltagi goes over everything you need to know right now about Flink. If you utilize big data analytics, then this is a must watch video!! Enjoy Learn More
Next Tuesday (April 19th), Metis’s 6 Week program “Intro to Data Science” begins. It runs Tuesday and Thursday evenings from 6:30pm – 9:30pm in midtown NYC. I was at the Open House last week and will be attending.There are a couple of seats left. Love the lead instructor Sergey Fogelson. Read More
[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
The Data Incubator is an intensive 7 week bootcamp that prepares the best scientists and engineerings with advanced degrees to work as data scientists and quants. Read More