MLTrain is coming back to New York City for another training event. Nick Vasiloglou and Alex Dimakis will cover several Machine Learning and TensorFlow topics. We have prepared a 2 day curriculum. You can register for each day individually or for both days. The space is offered by Ebay! When: 6/2-6/3 2017, 9:00am to 2:00pm
Video of keynote from Strata + Hadoop World in San Jose 2017. Machine learning at Google with Rob Craft (Google)
(Reposted due to popular demand) Another great video from Josh Wills. Josh is Sr. Director of Data Science at Cloudera and has a gift for making fairly complicated technology explanations very digestible to the novice and intermediary techie.
What I most love about this video is how Josh explains -very clearly – the issue of translating analytics Machine Learning on a large set of data records (many individuals) and making it work well in a “real life” production environment on a single individual (think eCommerce). Watch Video
The University of Illinois’ Coordinated Science Laboratory had it student run conference last month. This video is Dr. Andy Feng – VP Architecture at Yahoo! He leads the architecture and design of big data and machine learning initiatives. “In this talk, we illustrate Yahoo use cases and datasets, and explain the evolution of big-data technology stack.” Watch Video
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
The 20th anniversary of the GOTO Copenhagen Conference took place last month. Two 50 Minute videos – Machine Learning and Deep Learning. 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
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
Watch a Video Lecture from the NIPS Conference in December on Probabilistic Machine Learning from one of the greats, Zoubin Ghahramani, Professor of Information Engineering at the University of Cambridge, where he leads the Machine Learning Group. Read More
Deep Learning is type of Machine learning that has become very popular with the reduced cost of processing power.
Every Data Scientist who is dealing in massive data sets that update regularly should learn about it. Here are 2 great videos on Deep Learning from the GTC Conference in 2015 from top Data Scientists in the world Andrew Ng and Jeff Dean. Read More