Artificial Neural Network
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Training Highlights
- The course takes a practical and “hands-on”approach to teaching Machine Learning.
- Concepts will be introduced through practical examples and participants will be given exercises to be completed within and outside of contact hours. Use of the popular deep learning tool – Tensorflow multi-node Spark cluster
What One Will Learn
- Concepts of Artificial Neural Networks and Deep Learning Networks.
- Participants will understand these topics through practical tools like Tensorflow.
Prerequisite
- Proficiency over Python programming language is a must.
- Good understanding of statistical machine learning techniques is a definite pre-requisite.
Curriculum
Module 1
- Course Overview and Pedagogy
Module 2
Why ANN and Deep Learning
Concepts
Examples and Exercises
Module 3
Introduction to Deep Learning
Machine v/s Deep Learning
Architectures
Deep Learning Tools – Overview
Deep Learning Tools – Overview
Installation & setup
Non-GPU and GPU versions
Module 4
Tensorflow
Overview of Interfaces
Module 5
Tensorflow – Part 2
Creating Tensorflow Models
Exercises
Module 6
Tensorflow – Part 3
Convolutional Neural Nets
Exercise: Digit Recognition
Exercise: Image Recognition