Nishant Shukla is a computer vision researcher focused on applying machine-learning techniques in robotics. Senior technical editor : Kenneth Fricklas.
Machine Learning with TensorFlow
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- Nombre de pages251
- FormatGrand Format
- PrésentationBroché
- Poids0.468 kg
- Dimensions18,7 cm × 23,3 cm × 2,0 cm
- ISBN978-1-61729-387-0
- EAN9781617293870
- Date de parution01/03/2018
- ÉditeurManning
- ContributeurKenneth Fricklas
Résumé
TensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine. Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms.
Then, you'll move on to the money chapters : exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own. What's Inside : Matching your tasks to the right machine-learning and deep-learning approaches ; Visualizing algorithms with TensorBoard ; Understanding and using neural networks.
Then, you'll move on to the money chapters : exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own. What's Inside : Matching your tasks to the right machine-learning and deep-learning approaches ; Visualizing algorithms with TensorBoard ; Understanding and using neural networks.