DeepMind moves to TensorFlow
Posted by Koray Kavukcuoglu, Research Scientist, Google DeepMind At DeepMind, we conduct state-of-the-art research on a wide range of algorithms, from deep learning and reinforcement learning to systems neuroscience, towards the goal of building Artificial General Intelligence. A key factor in facilitating rapid progress is the software environment used for research. For nearly four years, the ope
A Full Hardware Guide to Deep Learning | Deep Learning
Deep Learning is very computationally intensive, so you will need a fast CPU with many cores, right? Or is it maybe wasteful to buy a fast CPU? One of the worst things you can do when building a deep learning system is to waste money on hardware that is unnecessary. Here I will guide you step by step through the hardware you will need for a cheap high performance system. In my work on parallelizin
Fundamentals of Deep Learning
Read it now on the O’Reilly learning platform with a 10-day free trial. O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers. With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this p
Portfolio
Introduction Approximately 25 years of experience Passionate about data privacy and censorship resistance Lead a team of ~30 engineers from hiring to delivering the product to the first customer. Worked in following projects / companies Ethereum Foundation ( worked on Swarm when it was part of Ethereum geth code) Swarm Foundation Prysmatic Labs (worked on PoS Merge) Shardeum Foundation (worked on
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Amazon.com: Deep Learning (Adaptive Computation and Machine Learning series): Goodfellow, Ian, Bengio, Yoshua, Courville, Aaron: Books
Amazon.com: Artificial Intelligence for Humans, Volume 3: Deep Learning and Neural Networks (English Edition): Heaton, Jeff: Digital Ebook Purchas
Amazon.co.jp: 深層学習 Deep Learning (監修:人工知能学会): 麻生英樹 (著), 安田宗樹 (著), 前田新一 (著), 岡野原大輔 (著), 岡谷貴之 (著), 久保陽太郎 (著), ボレガラダヌシカ (著), 神嶌敏弘 (編集), 人工知能学会 (監修): 本
http://www-labs.iro.umontreal.ca/~bengioy/dlbook/
