Tensorflow & ML hands on

This hands on session will cover the baiscs of Tensorflow and will include the following topics:

Basics of ML

• Regression vs Classification

• Birds-Eye view on a simple Feed-Forward Neural Net & How it learns

• Backprop & Gradient Descent

• ML as a generic function approximation

What is Tensorflow & Keras ?

• Installing keras.

Concepts

• AutoGrad

• Sequential Models

• Layers : Dense, Activation, Units

• Activation functions : Linear, Relu, Softmax

• Optimiser (SGD, RMSProp), Loss Functions

• Features, Training, Testing, Batches, Epochs

• Dropout

• Word Embeddings

Other Networks

• Convolutional Neural Networks

• Recurrent Neural Networks.

Examples

Keras.Js

⁠⁠⁠Speaker bio :
Ganesh Katrapati
PhD candidate at LTRC - IIITH in NLP and AI. He has been working and teaching natural language processing with machine learning since 3 years.He is also a Executive Committee Member of Swecha.

Requirements:

• Basic programming knowledge. Understanding of baisc ML concepts.

• Please bring your laptops with Tensorflow installed.

• IDE of your choice