Natural-Language-Processing-Specialization and NLP-Specialization

These are competitor implementations of the same Coursera NLP Specialization course, where users would choose one repository based on code quality and completeness rather than using both together.

Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 25/25
Maintenance 0/25
Adoption 4/25
Maturity 1/25
Community 16/25
Stars: 854
Forks: 699
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 5
Forks: 7
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
No License Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About Natural-Language-Processing-Specialization

amanjeetsahu/Natural-Language-Processing-Specialization

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

Covers four courses implementing classical to modern NLP architectures: sentiment analysis via logistic regression and naive Bayes, vector space models with PCA, sequence modeling with GRUs and LSTMs for tasks like named entity recognition and language generation, and transformer-based approaches including encoder-decoder attention for machine translation, T5/BERT for question-answering, and reformer models for dialogue systems. Implementations progress from foundational algorithms like minimum edit distance and n-gram language models through Word2Vec training to advanced techniques like Siamese networks for semantic similarity and attention mechanisms.

About NLP-Specialization

Anri-Lombard/NLP-Specialization

NLP Specialisation by Coursera

Scores updated daily from GitHub, PyPI, and npm data. How scores work