Welcome to "The NLP Path" - your curated collection of essential resources for the journey through Natural Language Processing (NLP). Whether you're a beginner or an advanced learner, these resources are designed to guide you through the diverse and evolving landscape of NLP.
This collection is meticulously organized to provide you with a comprehensive understanding of key concepts, methodologies, and advancements in NLP. Dive in and explore!
- Title: "Distributed Representations of Words and Phrases and their Compositionality"
- Published: 2013
- Overview: This seminal paper introduces the concept of vector representations for millions of phrases, laying the groundwork for modern NLP applications. It's a must-read for understanding how words and phrases can be encoded to capture linguistic meanings.
- Access Paper: Read Here
- Title: "Enriching Word Vectors with Subword Information"
- Published: 2016
- Overview: This influential paper details the FastText model, an extension of the Word2Vec model incorporating subword information. It marks a significant advancement in handling rare words and understanding morphological nuances in various languages.
- Access Paper: Read Here
- NPVec1: Word Embeddings for Nepali - Construction and Evaluation Paper
- n-grams
- The Sigmoid Function
- SoftMax
- Negative Sampling
- Negative Log-Likelihood [Cross-Entropy Loss Log-likelihood]
- Embeddings: What they are and why they matter
- Embeddings for Everything: Search in the Neural Network Era
- https://github.com/PacktPublishing/fastText-Quick-Start-Guide/blob/master/chapter5/Training_visualizations.py
- https://radimrehurek.com/gensim/models/fasttext.html
The field of NLP is continually evolving, and we aim to keep this collection up-to-date with the latest research and insights. Keep an eye on this space for more resources!