Implement ML using TensorFlow 2.3 (Apr 2023)
Running ML Algorithms using Tensorflow with Google Colab
What you will learn
Introduction to TensorFlow
Introduction to Google Colaboratory (Colab)
Classification and Regression Mechanism
Neural networks and implementation of neural network
Recommender System
Transfer Learning and Fine Tuning
Implementation of Deep convolutional GAN
Implementation of Cycle GAN
Why take this course?
This course takes you through hands-on approach with TensorFlow using Google Colab.
In this course you will have an overview of TensorFlow. TensorFlow is an open source software library released by Google. It is a Python library/framework which allows developers to express arbitrary computation as data flow graph and for easy calculation of complex mathematical expressions.
Here you will look upon TensorFlow architecture, Advantages and benefits of TensorFlow. You will also explore on Neural networks and implementation, types of neural Network in depth using Classification and regression mechanism. Also learn and understand about the advantages and benefits of using neural networks in brief.
Further, you will learn what is recommender system with an example and different ways to approach recommender system. Besides, you will also get to know the importance of recommender system.
You will explore on how to perform transfer learning on building the model and how to fine tune it. Additionally, you will have a brief overview about GAN (Generative adversarial Network)
Our focus is to teach topics that flow smoothly. The course teaches you everything you need to know about Implementation of ML using TensorFlow 2.3 with hands-on examples.
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