ICP12

Welcome to the In Class Programming 12:

Objective: We are going to discuss types of Artificial Neural Networks and Recurrent Neural Network and training the dataset.

Implementation:

1. Save the model and use the saved model to predict on new text data (ex, “A lot of good things are happening. We are respected again throughout the world, and that's a great thing.@realDonaldTrump”)

CODE: OUTPUT:

2. Apply GridSearchCV on the source code provided in the class

CODE: OUTPUT:

3. Apply the code on spam data set available in the source code (text classification on the spam.csv data set)

CODE: OUTPUT:

Video: ICP12

Conclusion: In these in class programming, I have learnt about the Recurrent Neural Network(RNN) and how the weights update process takes place using the back propagation through time.