LEARNING PATH: Keras: Deep Learning with Keras

About this course

Keras is a deep learning library written in Python for quick, efficient training of deep learning models, and can also work with Tensorflow and Theano. Because of its lightweight and very easy to use nature, Keras has become popularity in a very short span of time. So, if you are a data scientist with experience in machine learning with some exposure to neural networks, then go for this Learning Path. Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The highlights of this Learning Path are: Understand the main concepts of machine learning and deep learning Work with any kind of data involving images, text, time series, sound and videos Learn to build auto encoders and generative adversarial networks Let’s take a quick look at your learning journey. You will start with the basics of Keras, in a highly practical manner. You will then dive into deep learning with convolutional and recurrent neural networks, which are the cornerstones of deep learning. You will then take to look at recommender system and some of its types. You will move ahead with a popular Keras framework for style transfer, some advanced techniques and in-depth explanations of the style transfer mechanism. You will also learn to build, train and run generative adversarial networks, go through some of its most popular architectures, and learn techniques to make them work better. Next, you will get an hands-on training of CNNs, RNNs, LSTMs, autoencoders and generative adversarial networks using real-world training datasets. Finally, you will learn the concepts and applications of generative adversarial networks, implementation with Keras, using Batch Normalization to improve performance. By the end of this Learning Path, you will be well-versed with

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