What you'll learn

How to create various model and solve the problems hands-on using Keras.

As part of various hands-on activities, students will learn how to apply Deep Learning to real world problems

Requirements

Python language

Description

Following topics are covered as part of the course

Explore building blocks of neural networks

Data representation, Tensor, Back propagation

Keras

Dataset, Applying Keras to cases studies, over fitting / under fitting

Artificial Neural Networks (ANN)

Activation functions

Loss functions

Gradient Descent

Optimizer

Image Processing

Convnets (CNN), hands-on with CNN

Text and Sequences

Text data, Language Processing

Recurrent Neural Network (RNN)

LSTM

Bidirectional RNN

Gradients and Back Propagation - Mathematics

Who this course is for:

Bner Python developers, Data Science students, Students who have some exposure to Machine Learning



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