NLP-INTERESTSHIP

Hello everyone, welcome to NLP Interesthip. I will be uploading slides and notebooks here that we will be learning during this project. For every module, there will be 1 notebook and 1 slide.

Feel free to utilise these slides and notebooks for your learnings.

Resources

Module-1

• Introduction to NLP, NLP Applications, Corpus, Tokenization, Normalization, Stemming, Lemmatization, Stop Words Removal.
• Slides
• Notebook

Module-2

• Transformers, Attention, Transfer Learning, BERT Model, Fine Tuning.
• Slides
• Notebook

Module-3

• Understanding problem statement, understanding the dataset, text preprocessing.
• Slides
• Notebook

Module-4

• Logistic Regression, Naive Bayes, Confusion Matrix, TF-IDF, Task 1 Solution, etc.
• Slides
• Notebook

Module-5

• EDA Graphs Explained, Boxplots, Voilon Plots, Implementation of various ML Algorithms, K-Fold Cross Validation, Stratified K-Fold Sampling etc.
• Slides
• Notebook

Module-6

• Implementation using BERT Model Details Explained
• Slides
• Notebook

Module-7

• Actual Implementation
• Notebook

Youtube Video Links :

1. Logistic Regression : https://youtu.be/f6PNgEbopfQ
2. Naive Bayes : https://youtu.be/Pv75s9I8-mA
3. Performance Metrics : https://youtu.be/Fb6dXbDjCA8

Blog Links:

1. BERT - https://medium.com/@pallavipannu678/bidaf-vs-bert-observations-f79c79425b6d
2. TF-IDF - https://medium.com/@pallavipannu678/a-simple-chatbot-kissanbot-bb701a1b218a

Links for K-Fold CV and Stratified K-Fold Sampling

1. https://www.analyticsvidhya.com/blog/2022/02/k-fold-cross-validation-technique-and-its-essentials/
2. https://www.geeksforgeeks.org/stratified-k-fold-cross-validation/
3. https://towardsdatascience.com/what-is-stratified-cross-validation-in-machine-learning-8844f3e7ae8e