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Leading organizations like Google, Square, Netflix, Huawei and Uber are currently using Keras. This tutorial walks through the installation of Keras, basics of deep learning, Keras models, Keras layers, Keras modules and finally conclude with some real-time applications.
- Keras Tutorial
Leading organizations like Google, Square, Netflix, Huawei...
- Keras Tutorial
Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world.
Are you looking for tutorials showing Keras in action across a wide range of use cases? See the Keras code examples: over 150 well-explained notebooks demonstrating Keras best practices in computer vision, natural language processing, and generative AI. You can install Keras from PyPI via: You can check your local Keras version number via:
Neural Network library written in Python Designed to be minimalistic & straight forward yet extensive Built on top of either Theano as newly TensorFlow Why use Keras? Keras has a number of pre-built layers. Notable examples include: Regular dense, MLP type. Other types of layer include: Dropout Noise Pooling Normalization Embedding And many more...
Overview of the tutorial •What is Keras ? •Basics of Keras environment •Building Convolutional neural networks •Building Recurrent neural networks •Introduction to other types of layers •Introduction to Loss functions and Optimizers in Keras •Using Pre-trained models in Keras •Saving and loading weights and models
Chapter 1: Getting started with keras; Chapter 2: Classifying Spatiotemporal Inputs with CNNs, RNNs, and MLPs; Chapter 3: Create a simple Sequential Model; Chapter 4: Custom loss function and metrics in Keras; Chapter 5: Dealing with large training datasets using Keras fit_generator, Python generators, and HDF5 file format
Leading organizations like Google, Square, Netflix, Huawei and Uber are currently using Keras. This tutorial walks through the installation of Keras, basics of deep learning, Keras models, Keras layers, Keras modules and finally conclude with some real-time applications.
