OpenAI developed Random Network Distillation (RND), a prediction-based method for encouraging reinforcement learning agents to explore their environments through curiosity, which for the first time exceeds average human performance on Montezuma’s Revenge. Learn more:
Scientists of AI at Google’s Google Brain and DeepMind units acknowledge machine learning is falling short of human cognition and propose that using models of networks might be a way to find relations between things that allow computers to generalize more broadly about the world. By Tiernan Ray | October 20, 2018 — 12:52 GMT (05:52 PDT) | Source […]
4 Panalist from the TiEcon 2017 Conference discuss 7 use cases of AI & machine learning in marketing. Abhishek Pani – Sr. Director, Data Science & New Products, Adobe Harpinder Singh – CEO & Co-Founder, Slice Jessica Cross – Head of Customer Lifecycle, AdRoll John Bara – President & Chief Marketing Officer, Mintigo Moderated by: Nadim […]
Great (free) Machine Learning course for beginners by Caltech University. Introduction to; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lectures 1 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. Watch Video
So what is the difference? “Data Science vs Machine Learning” “A simple distinction between Data Science vs Machine Learning for project managers and team leads.” by Charles Martin, PhD Data Science & Machine Learning Expert (YouTube Channel) OTHER: Artificial Intelligence Vs. Machine Learning Vs Data Science Vs Deep Learning My Quora Answer to: What […]
From PyData Amsterdam, April 2017. Giovanni Lanzani gives a talk on the Data Science Process and where things can go wrong.
Free Machine Learning in Python Course | Online Curriculum springboard.com Use this free curriculum to build a strong foundation in Machine Learning, with concise yet rigorous and hands-on Python tutorials https://www.springboard.com/learning-paths/machine-learning-python/ Go!
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.
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)