Xinyi2016 / awesome-nlp

Recommended resources for NLP practice from preprocessing to model serving

awesome-nlp

A collection of recommended resources for NLP practice from preprocessing to model serving

Maintainers - Sara Z.

---

Contents

• Quantitative Text Analysis
  • [Linguistic features]
• Deep learning with TensorFlow
• Neural architecture search
• Model serving
• Pipeline construction

---

Quantitative Text Analysis

• Tools:
  • Java: Mallet, Yoshikoder, Lexicoder
  • R: tm, tidytext, quanteda
  • Python: NLTK, Gensim
• PySpark processing
• Regular expression cheat sheet Java / python / PySpark / SQL

FAQ

• Generative vs. Discriminative models

---

Deep learning with TensorFlow

Back to Top

• Basic math for deep learning code
• RNN code theory
• Tensorboard code

FAQ

• Epoch vs. Batch sizes vs. Iterations theory

---

Neural architecture search

Back to Top

• Efficient Neural Architecture Search via Parameter Sharing code theory

---

Model serving

Back to Top

• Machine Learning model serving with Java code

---

Pipeline construction

Back to Top

Docker and Kubernetes

• All the Docker commands I used last week tutorial

High performance programming

• Understanding memory and time usage tutorial