Text Analytics

Week

Instructor

Content

1
February 14th

FLP & RR

• -  Course Overview

• -  Whats Natural Language Processing/Text Analytics and why does it matter.

• -  Python Refresher

• -  Setting up Python (Anaconda and Jupyter Notebooks)

2
February 21th

RR

• -  Methodology, corpora and evaluation

• -  Introduction to the NLTK

• -  Corpus cleaning and creation of train/val/test sets.

3
February 28th

RR

- Bag-of-word models.
- Tokenization.
- Distance metrics.
- Comparison of documents.

4
March 14th

RR

• -  N-grams

• -  TF-IDF features

• -  Feature engineering

• -  Stemming

• -  POS filtering

5
March 21th

RR

• -  Distance based classification (KNN)

• -  N-gram Counting

• -  Simple document classifier.

6
March 28th

RR

- Information Retrieval
- QuestionAnswering
- Building a simple customer support chatbot

7
April 4nd

RR

- First Test & Presentation about the project.

8
April 11th

RR

• -  Sequence models

• -  Markov models and hidden Markov models

• -  Dynamic programming algorithms

9
April 25rd

• -  Machine Learning: Naive Bayes and Perceptron

• -  Document classification revisited I

10 May 2th

RR

• -  Multi-layer Perceptron (Overview)

• -  Representation Learning (introduction to word embeddings)

• -  Document classification revisited II

11 May 9th

RR

- Word Embeddings - SentimentAnalysis

12
May 16th

RR

• -  Invited talk.

• -  NLP industry applications.

• -  Project deadline.

13
May 23st

RR

- Sequence modelling (Deep Learning overview)

14
May 30th

RR

- Second Test
- Sequence modelling (Deep Learning overview)