Preview NLP : Zero to Expert

Module 1 - Course Outline

Introduction Part

Module 2 - Dataset Gathering & Data Quality Assurance

Dataset Gathering

How to Ensure Data Quality

Coding Part-1 (Cohen Kappa Score)

Coding Part 2 (Cohen Kappa Score Data Analysis)

Module 3 - Preprocessing Techniques

Common Techniques of Preprocessing in NLP

Feature Representation and the techniques

Coding Part-1 (Preprocessing, NLTK)

Coding Part-2 (Preprocessing)

Module 4 - RNN(Recurrent neural network) Model

Basic ANN (Explanation with Example)

RNN Part- 1 (Explanation with Example)

RNN Part- 2 (Dimensions in RNN, Bidirectional RNNs)

Module 5 - LSTM(Long Short Term Memory) Model

LSTM Part-1 (Introduction, Theory Example)

LSTM Part- 2 (Explanation with Example)

Module 6 - GRU(Gated Recurrent Unit) Model

GRU Lecture (Explanation with Example)

Module 7 - Interpretibility & Bias

Interpretibility & Explainable AI Lecture

Bias Part- Is your Model Biased ?

Course Review Form