Spacy for NLP

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Section 1: Introduction to Spacy

  1. Overview of Spacy
  2. How to Get Queries Resolved
  3. Download Resources
  4. Common Use Cases
  5. Introduction to Spacy Models
  6. What happens inside Spacy Models
  7. Install Spacy and Models

Section 2: Linguistic Features

  1. Data structures in Spacy
  2. Data structuresin Spacy - Make a doc from scratch
  3. Data structuresin Spacy - nlp.make.doc()
  4. String Store
  5. How Tokenization Works
  6. Create Custom Tokenization Rules
  7. Build Custom Tokenizer
  8. Named Entity Recognition
  9. POS Tagging
  10. Dependency Parsing
  11. Need for Dependency Parsing
  12. Navigating the Parse Tree
  13. Noun Chunks

Section 3: Rule Based Matching

  1. Contextual Token Matching
  2. Phrase Matching
  3. Handling Large Number of Patterns
  4. Course Review

Section 4: Pipelines and Custom Attributes

  1. Understanding Spacy Pipelines
  2. How to Apply Particular Component
  3. Manipulating the Pipeline
  4. EntityRuler
  5. How to Create Custom Pipeline Components
  6. Custom Sentence Segmenter
  7. Efficient Text Processing Approaches
  8. User Defined Attributes
  9. Property Extensions
  10. Method Extensions

Section 5: Word Vectors

  1. Need for Word Vectors
  2. Advantage of Vector Representation
  3. How Word Vectors are Computed
  4. Understanding Cosine Similarity
  5. The Training Loop
  6. Train a New NER Model from Scratch

Section 6: Training Custom NER Models

  1. Training Custom NER Models
  2. Training Custom NER Models- Part 2
  3. Training Custom NER Models- Part 3
  4. Training Custom NER Models- Part 4

Section 7: Training Text Classification Models - Ecommerce Reviews

  1. Text Classification with Textcat - Part 1
  2. Text Classification with Textcat - part 2
  3. Text Classification with Textcat - part 3
  4. Text Classification with Textcat - part 4
  5. Text Classification with Textcat - part 5
  6. Text Classification with Textcat - part 6

Section 8: Training Custom POS Tagger Model

  1. Training Customer POS Tagger Model- part 1
  2. Training Customer POS Tagger Model- part 2
  3. Course Review

Section 9: Training Custom Intent Parser

  1. Training Custom Intent Parser - Part 1
  2. Training Custom Intent Parser - Part 2
  3. Training Custom Intent Parser - Part 3
  4. Training Custom Intent Parser - Part 4

Section 10: Chatbot with Spacy and Rasa

  1. Building Chatbot with Spacy and Rasa
  2. Intent Classification
  3. NLU Pipeline
  4. Training NLU Model
  5. RASA Core
  6. Writing Stories
  7. Course Review
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