000			01461 a2200205 4500
003			OSt
005			20240712164238.0
008			240712b |||||||| |||| 00| 0 eng d
020			_a9781484283769
040			_bEnglish
082			_a006.3/MIC
100			_aMichelucci, Umberto
245			_aApplied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python
250			_a2nd ed
260			_bApress _c2024
300			_axxviii, 380p
520			_aThis book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks. All the code presented in the book will be available in the form of Jupyter notebooks which would allow you to try out all examples and extend them in interesting ways. A companion online book is available with the complete code for all examples discussed in the book and additional material more related to TensorFlow and Keras. All the code will be available in Jupyter notebook format and can be openeddirectly in Google Colab (no need to install anything locally) or downloaded on your own machine and tested locally.
650			_2Intermediate understanding of machine learning, linear algebra, calculus, and basic Python programming.
942			_cB _2ddc
999			_c698672 _d698672