Multilayer-Perceptron-Model

Building and training a multilayer perceptron (MLP) model using Keras, with Tensorflow as its backend for topic classification <<<

Objectives :

1. Build and train a multilayer perceptron (MLP) with Keras
2. Perform topic classification with neural networks

Overview :

Worked with the Reuters dataset, a set of short newswires and their topics, published by Reuters in 1986. It's a very simple, widely used toy dataset for text classification. There are 46 different topics, some of which are more represented than others. But each topic has at least 10 examples in the training set. So in this project, you will build a MLP feed-forward neural network to classify Reuters newswires into 46 different mutually-exclusive topics.

Tasks :

1. Project Overview and Import Libraries
2. Load the Reuters Dataset
3. Vectorize Sequences and One-hot Encode Class Labels
4. Build Multilayer Perceptron Model
5. Train Model
6. Evaluate Model on Test Data

Skills :

1. Data Science
2. Deep Learning
3. Machine Learning
4. Tensorflow
5. keras