The session will cover implementation of Artificial Neural Networks , Convolutional Neural Networks
using Tensorflow and we will also look at training Machine Learning models using the SKlearn library.
We will be looking at Kaggle datasets and then build our model based on the data.
This session will give you a hands on experience with the Tensorflow API.
Topics going to be covered in this session:
1) ANN implementation using Keras
- Get a kaggle dataset(IRIS dataset)
- Train an ANN
- How to get inference
2) CNN implementation using Keras
- Demo on MNIST(Hands on)
- Train a CNN
- Getting inference
- Demo on data augmentation
3) Decision Tree Regression/Classification (using SKlearn)
- Random forest regresion/classification