Numerous big & small companies are considering artificial intelligence & machine learning as an important field for their businesses. It is mostly because of the fact that ML promises lots of possibilities in almost all the domains, and these companies want to be competitive in this digital age. Because of this, a lot of individuals are showing their interests to learn different tools for machine learning. Considering this, we have curated an exclusive ebook completely revolving around tensor flow which is one of the most popular and widely used tools or libraries for machine learning applications. Why should I choose this ebook? It will help you in understanding both basics and the advanced concepts of tensor flow along with the codes. It will make you capable enough to easily work with it to build various machine learning applications. This ebook covers a vast range of concepts related to tensor flow along with the real world project for giving you a more clear picture. What makes this ebook so valuable? This ebook on tensor flow consists of all the required topics for the better understanding of tensor flow along with generative adversarial network. Initially, it focuses on the basic introduction, deep learning, tensor flow 2. 0, Data analysis & neural networks. Moreover, it describes different types of autoencoders, ga ns and other crucial aspects related to tensor flow. Moreover, this ebook also includes a live project of "toxic comment classification challenge" in tensor flow. This ebook includes1. A basic introduction to tensor flow, tensor board, the role of python, components & APIs of tensor flow2. Deep learning artificial neural network, recurrent neural network & convolutional neural network3. Tensor flow 2. 0Basics, its importance, variables, placeholders, installation, environment set up, tensor flow graphs4. Machine learning basics essential packages, implementation, scikit learn, classification & regression models & data visualization5. Neural network basics, perceptrons, different activation functions, cost functions, gradient descent & backpropagation6. Autoencoders different types, dimensionality reduction with linear autoencoder, stacked autoencoder7. Generative adversarial networks introductions, deployment, applications & code8. Live project in tensor flow toxic comment classification challenge get started with this ebook now to learn different concepts related to tensor flow & ga ns for acing or building advanced machine learning applications!
