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Book Overview & Buying
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Table Of Contents
Getting Started with TensorFlow 2.0 for Deep Learning
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Getting Started with TensorFlow 2.0 for Deep Learning
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Overview of this book
Deep learning is a trending technology if you want to break into cutting-edge AI and solve real-world, data-driven problems. Google’s TensorFlow is a popular library for implementing deep learning algorithms because of its rapid developments and commercial deployments.
This course provides you with the core of deep learning using TensorFlow 2.0. You’ll learn to train your deep learning networks from scratch, pre-process and split your datasets, train deep learning models for real-world applications, and validate the accuracy of your models.
By the end of the course, you’ll have a profound knowledge of how you can leverage TensorFlow 2.0 to build real-world applications without much effort.
All the notebooks and supporting files for this course are available on GitHub at
https://github.com/PacktPublishing/Getting-Started-with-TensorFlow-2.0-for-Deep-Learning-Video
Table of Contents (7 chapters)
Deep Learning Basics
TensorFlow 2.0 for Deep Learning
Working with CNNs for Computer Vision and Deep Learning
Working with LSTM for Text Data and Deep Learning
Working with RNNs for Time Series Sequences and Deep Learning
Autoencoders AE and Denoising AE
Deep Learning Mini-Projects
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