# Deep Learning With Keras and TensorFlow

## Deep Learning With Keras and TensorFlow On udemy

**Deep Learning With TensorFlow **& **Keras**. Go from beginner to mastery in Neural Networks

### Redeem On Udemy

#### What you'll learn in Deep Learning With Keras and TensorFlow

- Understand TensorFlow in detail
- Define Convolutional Network
- Describe Recurrent Neural Network
- Explain the Restricted Boltzmann Machine (RBM)
- Explain Autoencoders in detail

### About the Course: Deep Learning With Keras and TensorFlow

The “Deep Learning with Keras and TensorFlow” course is an intermediate level course, curated exclusively for both beginners and professionals.

The course covers the basics as well as the advanced level concepts. The course contains content based videos along with practical demonstrations, that performs and explains each step required to complete the task.

**Learning Objectives:**

#### By the end of the course, you will be able to learn about:

- Introduction to TensorFlow
- TF2x and Eager Execution
- TensorFlow Hello World
- Linear Regression With TensorFlow
- Logistic Regression With TensorFlow
- Intro to Deep Learning
- Deep Neural Networks
- Intro to Convolutional Networks
- CNN for Classifications
- CNN Architecture
- Understanding Convolutions
- CNN with MNIST Dataset
- The Sequential Problem
- The RNN Model
- The LSTM Model
- LTSM Basics
- Applying RNNs to Language Modeling
- LSTM Language Modeling
- Intro to RBMs
- Training RBMs
- RBM with MNIST
- Introduction to Autoencoders
- Autoencoder structure
- ...and much more!

If you're new to this technology, then don't worry - the course covers the topics from the basics. If you have done some programming before, you should pick it up quickly.

If you are a programmer looking to switch into an exciting new career track, this course will teach you the basic techniques used by real-world industry Machine Learning and Deep Learning developers. These are topics any successful technologist absolutely needs to know about, so what are you waiting for? **Enroll now!**