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This will be a hands-on session in deep learning. It will provide a conceptual and simplified approach to build foundation for deep learning.
Benefits: It will be easy to use neural networks once the conceptual understanding of the network is clear. Once any wrapper is mastered, tensor flow library can be used to implement the same thing. Use of building prototypes using Keras will be helpful to students and researchers in this area.
1. Introduction to Neural Network
2. How neural network learns
3. Neural network in Action
4. Developing neural network using encapsulation
5. Neural Networks in keras
6. MNIST in keras
7. Sentiment Analysis in keras
1. Anaconda Python Distribution https://www.continuum.io/downloads
2. Keras library. (Using conda install keras)
3. Pycharm IDE (Optional)
The Eminent Speaker: Ajinkya Kolhe
Ajinkya is a freelance trainer for Python, Java and Linux. He has 4 years of experience as a software developer and 1 year experience in teaching. He is currently working in "Deep Learning" for Computer Vision and Natural Language Processing. He is pursuing M.Tech with specialization in Deep Learning for text analysis.