Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 4 Minute(s)
Language
English
Taught by
Proton Expert Systems & Solutions
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
1 views
Course Overview
Running ML Algorithms using Tensorflow with Google Colab
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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Course Content
- 8 section(s)
- 22 lecture(s)
- Section 1 Introduction
- Section 2 Introduction to TensorFlow and Google Colaboratory
- Section 3 Implementing Classification and Regression using TensorFlow
- Section 4 Neural Networks and Artificial Neural Network (ANN)
- Section 5 Recurrent Neural Network (RNN) and Time Series Prediction
- Section 6 Working with Convolution Neural Network (CNN)
- Section 7 Recommender System, Transfer Learning and Fine Tuning
- Section 8 Generative Adversarial Network (GAN)
What You’ll 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
Skills covered in this course
Reviews
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PPaola Ghione
It misses the part concerning the evaluation of the model on the unseen set
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RRashmi V Namaye
This is a really great course for Tensorflow. The organization of the course is awesome, very well designed, and easy to follow along with Hands-on
