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Natural Language Processing

NLP helps computer to understand human language and also allows machines to communicate with us. According to the Wiki definition, Natural-language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to fruitfully process large amounts of natural language data.

NLP applications

  1. Translating the languages,
  2. Text processing in various languages,
  3. Automatic text summarization,
  4. Analyzing sentiments,
  5. Speech recognition,
  6. Named entity recognition,
  7. Phrase extraction,
  8. Tense identification,
  9. Relationship extraction, etc.

ROADMAP LIST

  1. Maths: Calculus, Linear Algebra, Stats and Probability
  2. Text Preprocessing
  3. Information Extraction
  4. Feature Extraction
  5. Part Of Speech Tagging
  6. Named Entity Extraction
  7. WordEmbedding
  8. Text Similarity
  9. Semantic similarity
  10. Text clustering
  11. Text Classification
  12. sentiment
  13. Text summarization
  14. Chatbot
  15. Machine Translation
  16. Text to Speech
  17. Speech to Text

BOOKS

  1. Linear Algebra by Gilbert Strang
  2. INFORMATION RETRIEVAL
  3. Mastering NLP with Python
  4. Neural Network
  5. Artificial-Intelligence-A-Modern-Approach-4th-Edition-1
  6. Alppaydin_MachineLearning_2010
  7. Artificial Intelligence. Structures and Strategies for Complex Problem Solving. Sixth Edition (George F. Luger)

DATASET

  1. Google NLP dataset
  2. UCI repository
  3. NLP Datasets

COURSE

  1. INTRO TO MACHINE LEARNING
  2. MACHINE LEARNING
  3. Neural Network
  4. DEEP LEARNING
  5. NEURAL NETWORK AND DEEP LEARNING
  6. Zero to Deep Learning
  7. Courses in Kaggle

ROADMAP

For Coding

1. Maths

Pre-requisites:

Calculus

Linear Algebra

Stats and Probability

2. Text Preprocessing

3. Information Extraction

4. Feature Extraction

5. Part Of Speech Tagging

6. Named Entity Extraction

7. WordEmbedding

8. Text Similarity

9. Semantic similarity

10. Text clustering

11. Text Classification

12. sentiment

13. Text summarization

14. Chatbot

15. Machine Translation

16. Text to Speech

17. Speech to Text

OTHERS:

1. Web applications and api

2. Database

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A simple RoadMap to Natural Language Processing(NLP)

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