Neural Networks in Unity

Abhishek Nandy is B.Tech in IT and he is a constant learner.He is Microsoft MVP at Windows Platform,Intel Black belt Developer as well as Intel Software Innovator he has keen interest on AI,IoT and Game Development Currently serving as a Application Architect in an IT Firm as well as consulting AI,IoT as well doing projects on AI,ML and Deep learning.He also is an AI trainer and driving the technical part of Intel AI Student developer program.He was involved in the first Make in India initiative where he was among top 50 innovators and got trained in IIMA.

Manisha Biswas is BTech in Information Technology and currently working as Data Scientist at Prescriber360,in kolkata, India.She is involved with several areas of technology including Web Development, IoT,Soft Computing and Artificial Intelligence.She is an Intel Software Innovator and was also awarded the SHRI DEWANG MEHTA IT AWARDS 2016 by NASSCOM,a certificate of excellence for top academic scores. She is founder of WOMEN IN TECHNOLOGY,Kolkata a tech community to empower women to learn and explore new technologies.She always like to invent things,create something new,or to invent a new look for the old things. When not in front of my terminal, She is an explorer,a traveller,a foodie, a doodler and a dreamer.She is always very passionate to share her knowledge and ideas with others.She is following her passion and doing the same currently by sharing her experiences to the community so that others can learn and give shape to her ideas in a new way this lead her to become Google Women Techmakers Kolkata Chapter Lead.

Chapter
1: Core Concepts of Neural NetworksChapter Goal: This chapter will walk through about neural network,will give an overview of how neural network works.No of pages 30-40Sub -Topics
1. What is neural network
2. Perceptron
3. Single layer neural network vs multilayer perceptrons
4. Activation Function and its different types
5. What is Bias
1. The complete neural network flow
Chapter
2: Different types of Neural NetworkChapter Goal: In this chapter we will study about different types of neural network and then discuss the difference between Fully connected vs convolution neural network.No of pages: 40Sub - Topics
1. Feed forward neural network
2. Radial Basis neural network
3. Deep Feed Forward
4. Recurrent neural networks
5. Long-Short term memory
6. Auto encoder
7. Hopfield Network
8. Boltzmann Machine
9. Restricted Boltzmann Machine
10. Support Vector Machines
11. What is Chain Rule?
12. How to traverse a neural network
13. Fully Connected versus CNNs
Chapter
3: Neural Network with UnityChapter Goal: No of pages: 50Sub - Topics:
1. Understanding the structure of neural network
2. Creating a data structure of neural network in C#
3. Creating a new project in Unity for neural network
4. Getting the entire flow in Unity and finalizing the project
5. Using the Spider Asset animation for neural network
6 Compiling the entire project
Chapter
4: Back propagation using UnityChapter Goal: No of pages: 40Sub - Topics:
1. What is Back Propagation?
2. Mathematics required for back propagation
3. Getting started with Unity
4. Back Propagation using Unity C#
5. Completing the project
Chapter
5: Neural Network with Processing and Windows
10 UWPChapter Goal: No of pages: 60Sub - Topics:
1. Getting Started with processing language
2. Creating neural networks with processing
3. Different simulations of neural network with processing
4. Introduction to Windows
10 UWP
5. Developing Neural network with processing for Windows
10 uwp.
6. Making the app ready to be published in Windows Store