Neural Networks with Keras Cookbook
This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach.
We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data.
Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks.
We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems.
Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game.
By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter.
|Course Length||17 hours 2 minutes|
|Date Of Publication||28 Feb 2019|
|Creating the dataset for a bounding box|
|Generating region proposals within an image, using selective search|
|Calculating an intersection over a union between two images|
|Detecting objects, using region proposal-based CNN|
|Performing non-max suppression|
|Detecting a person using an anchor box-based algorithm|
|Building an RNN from scratch in Python|
|Implementing RNN for sentiment classification|
|Building a LSTM Network from scratch in Python|
|Implementing LSTM for sentiment classification|
|Implementing stacked LSTM for sentiment classification|
|The optimal action to take in a simulated game with a non-negative reward|
|The optimal action to take in a state in a simulated game|
|Q-learning to maximize rewards when playing Frozen Lake|
|Deep Q-learning to balance a cart pole|
|Deep Q-learning to play Space Invaders game|