| About the Book | Book |
|---|---|
| Use TensorFlow 2.x in the Google Colab ecosystem to create state-of-the-art deep learning models guided by hands-on examples. The Colab ecosystem provides a free cloud service with easy access to on-demand GPU (and TPU) hardware acceleration for fast execution of the models you learn to build. This book teaches you state-of-the-art deep learning models in an applied manner with the only requirement being an Internet connection. The Colab ecosystem provides everything you need, including Python, TensorFlow 2.x, GPU and TPU support, and Jupyter Notebooks. |  |
👉 Take advantage of the built-in support of the Google Colab ecosystem
👉 Work with TensorFlow data sets
👉 Create input pipelines to feed state-of-the-art deep learning models
👉 Create pipelined state-of-the-art deep learning models with clean and reliable Python code
👉 Leverage pre-trained deep learning models to solve complex machine learning tasks
👉 Create a simple environment to teach an intelligent agent to make automated decisions
| Sr No | Chapters | Colab |
|---|---|---|
| 1 | Build TensorFlow Input Pipelines | |
| 2 | Increase the Diversity of Your Dataset with Data Augmentation | |
| 3 | TensorFlow Datasets | |
| 4 | Deep Learning with TensorFlow Datasets | |
| 5 | Introduction to Tensor Processing Units | |
| 6 | Simple Transfer Learning with TensorFlow Hub | |
| 7 | Advanced Transfer Learning | |
| 8 | Stacked Autoencoders | |
| 9 | Convolutional and Variational Autoencoders | |
| 10. | Generative Adversarial Networks | |
| 11 | Progressive Growing Generative Adversarial Networks | |
| 12 | Fast Style Transfer | |
| 13 | Object Detection | |
| 14 | An Introduction to Reinforcement Learning |
🙏Thanks for Reading...!!!
All the rights are reserved by the original author only.