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| 007 |
cr||||||||||||||||||||| |
| 008 |
210208 ||| eng |
| 020 |
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|a 9783030570774
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| 100 |
1 |
|
|a Prakash, Kolla Bhanu
|e [editor]
|
| 245 |
0 |
0 |
|a Programming with TensorFlow
|h Elektronische Ressource
|b Solution for Edge Computing Applications
|c edited by Kolla Bhanu Prakash, G. R. Kanagachidambaresan
|
| 250 |
|
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|a 1st ed. 2021
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| 260 |
|
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|a Cham
|b Springer International Publishing
|c 2021, 2021
|
| 300 |
|
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|a X, 190 p
|b online resource
|
| 505 |
0 |
|
|a Introduction -- Installation Guide to Tensorflow -- Hello Tensorflow Program -- Representation of Vector -- Session with Tensorflow -- Matrix elementary operation -- Variable and constant -- Simple mathematical operation -- Matrix -- Variable Concept & Implementation -- Placeholder Concept & Implementation -- Equation with Tensor -- Matplot -- Regression Model -- Neural Network -- Convolutional Neural Network -- Recurrent Neural Network -- Application of Machine Learning & Deep Learning -- Implementing Chatbots -- Working with Text and Sequences + TensorBoard visualization -- TensorFlow Autoencoders -- Advanced TensorFlow Programming -- Reinforcement Learning -- RNN & LSTM using Keras -- Deep Learning with Pytorch -- Conclusion
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| 653 |
|
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|a Machine learning
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| 653 |
|
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|a Compilers (Computer programs)
|
| 653 |
|
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|a Compilers and Interpreters
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| 653 |
|
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|a Machine Learning
|
| 653 |
|
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|a Computational intelligence
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| 653 |
|
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|a Computational Intelligence
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| 653 |
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|a Signal, Speech and Image Processing
|
| 653 |
|
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|a Signal processing
|
| 700 |
1 |
|
|a Kanagachidambaresan, G. R.
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a EAI/Springer Innovations in Communication and Computing
|
| 028 |
5 |
0 |
|a 10.1007/978-3-030-57077-4
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-57077-4?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 621,382
|
| 520 |
|
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|a This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. The book provides a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. The authors begin by working through some basic examples in TensorFlow before diving deeper into topics such as CNN, RNN, LSTM, and GNN. The book is written for those who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. The authors demonstrate TensorFlow projects on Single Board Computers (SBCs). Provides a practical end-to-end guide to TensorFlow, the leading open source software library for building and training neural networks; Pertains to a broad technical audience—from data scientists and engineers to students and researchers; Shows how to implement advanced techniques in deep learning and explore deep neural networks and layers of data abstraction
|