Introduction to Neural Networks
Aditya Sathe (~sathe-aditya) |
What are Neural Networks? How do they work?
How does the concept of probability take its place in Neural Networks?
How do Neural Networks provide the output?
We will walk through the concept of Neural Networks, how they work and where they benefit over other ML algorithms in this workshop.
The workshop will cover the various types of neural networks while highlighting the advantages & disadvantages of each.
Participants will get to work with some basic types of Neural Networks, and at the end, will be able to design:
- A Neural Network that can generate it's own stories.
- A Neural Network that can distinguish handwritten digits
The workshop will conclude with a demo of a Neural Network to determine whether a user will like a particular video file or not.
Proceedings of the workshop:
- Introduction to Neural Nets
- Types of Neural Nets
- Tensorflow and TFLearn
- Hands-on with Neural Networks
- Demo of a Neural Network
Basic knowledge of Python
A general idea of Machine Learning
A *NIX/Windows machine with:
- Python 2/3
- Tensorflow (and its dependancies)
Session contents can be found here.
Aditya Sathe is a CS senior at VIT University, Chennai Campus. He developed interest in Machine Learning in his sophomore year.
Since then he has worked on numerous projects involving Machine Learning, Data Mining, Image Processing, Natural Language Processing and Internet of Things.
Interning at startups that heavily implement Machine Learning in their product line helped him garner firsthand experience at what goes on behind-the-scenes while being directly involved with product development.
He has a keen interest in research activities and is working with a few professors in and outside India.