Home
»
TensorFlow for Deep Learning
TensorFlow for Deep Learning
Regular price
€68.99
603 verified reviews
100% verified
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
Shipping & Delivery
Our Delivery Time Frames Explained
2-4 Working Days: Available in-stock
14-28 Working Days: On Backorder
Will Deliver When Available: On Pre-Order or Reprinting
We ship your order once all items have arrived at our warehouse and are processed. Need those 2-4 day shipping items sooner? Just place a separate order for them!
Close
A01=Bharath Ramsundar
A01=Reza Bosagh Zadeh
AI artificial intelligence TensorFlow Deep Learning machine learning neural networks reinforcement learning convolutional networks TSTMs recurrent networks
Author_Bharath Ramsundar
Author_Reza Bosagh Zadeh
Category=UYQN
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Product details
- ISBN 9781491980453
- Weight: 408g
- Dimensions: 177 x 233mm
- Publication Date: 30 Apr 2018
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines.
TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up. It’s ideal for practicing developers with experience designing software systems, and useful for scientists and other professionals familiar with scripting but not necessarily with designing learning algorithms.
Learn TensorFlow fundamentals, including how to perform basic computation
Build simple learning systems to understand their mathematical foundations
Dive into fully connected deep networks used in thousands of applications
Turn prototypes into high-quality models with hyperparameter optimization
Process images with convolutional neural networks
Handle natural language datasets with recurrent neural networks
Use reinforcement learning to solve games such as tic-tac-toe
Train deep networks with hardware including GPUs and tensor processing units
Bharath Ramsundar received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He is currently a PhD student in computer science at Stanford University with the Pande group. His research focuses on the application of deep-learning to drug-discovery. In particular, Bharath is the lead-developer and creator of DeepChem.io, an open source package founded on TensorFlow that aims to democratize the use of deep-learning in drug-discovery. He is supported by a Hertz Fellowship, the most selective graduate fellowship in the sciences. Reza Bosagh Zadeh is Founder CEO at Matroid and Adjunct Professor at Stanford University. His work focuses on Machine Learning, Distributed Computing, and Discrete Applied Mathematics. Reza received his PhD in Computational Mathematics from Stanford University under the supervision of Gunnar Carlsson. His awards include a KDD Best Paper Award and the Gene Golub Outstanding Thesis Award. He has served on the Technical Advisory Boards of Microsoft and Databricks.
TensorFlow for Deep Learning
€68.99
