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TENSORFLOW FOR DEEP LEARNING. FROM LINEAR REGRESSION TO REINFORCEMENT LEARNING
Título:
TENSORFLOW FOR DEEP LEARNING. FROM LINEAR REGRESSION TO REINFORCEMENT LEARNING
Subtítulo:
Autor:
ZADEH, R
Editorial:
O´REILLY
Año de edición:
2018
ISBN:
978-1-4919-8045-3
Páginas:
2018
66,95 € -10,0% 60,26 €

 

Sinopsis

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