Keras Tutorial With TensorFlow | Building Deep Learning Models With Python | Great Learning
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This Keras Tutorial With TensorFlow will show you how to use Keras, which is a neural network API written in Python, and integrated with TensorFlow. We will learn how to prepare and process data for artificial neural networks, build and train artificial neural networks from scratch.
Keras is an Open Source Neural Network library written in Python that runs on top of Theano or Tensorflow. It is designed to be modular, fast, and easy to use. Keras doesn’t handle low-level computation. Instead, it uses another library to do it, called the “Backend. So Keras is a high-level API wrapper for the low-level API, capable of running on top of TensorFlow, CNTK, or Theano.
If you want to make a simple network model with a few lines, Keras can help you with that. Leading organizations like Google, Square, Netflix, Huawei, and Uber are currently using Keras. This tutorial will walk you through different topics such as What is Keras and how to use it, How to start with Tensorflow, Difference between TensorFlow 1.18 and Tensorflow2.0, and much more.
00:00:34 – Agenda
00:00:35 – Brief about Tensorflow
00:03:26 – Agenda
00:11:30 -Difference between Tensorflow 1.18 and Tensorflow 2.0
00:18:27 – Brief about Tensorflow 2.0
00:21:11 – Getting started with Tensorflow
00:45:36 – Different types of model in Keras
00:58:05 -Getting started with Keras
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