Spacy for NLP

What you'll be able to do

• Setup Spacy
• Tokenization in NLP
• POS Tagging
• Rule Based Matching
• Word 2 Vector
• Training the NLP models
• Chatbots with Spacy and Rasa

1. 01Introduction to Spacy7 lessons · 28 min

   1. Overview of SpacyPreview5:02
   2. How to Get Queries Resolved1:00
   3. Download Resources1:00
   4. Common Use CasesPreview4:12
   5. Introduction to Spacy Models7:51
   6. What happens inside Spacy Models3:12
   7. Install Spacy and Models6:11
2. 02Linguistic Features13 lessons · 51 min

   1. Data structures in Spacy4:22
   2. Data structures in Spacy - Make a doc from scratch3:01
   3. Data structures in Spacy - nlp.make.doc()2:49
   4. String Store4:35
   5. How Tokenization Works3:36
   6. Create Custom Tokenization Rules5:43
   7. Build Custom Tokenizer3:59
   8. Named Entity Recognition7:27
   9. POS Tagging5:25
   10. Dependency Parsing1:27
   11. Need for Dependency Parsing1:58
   12. Navigating the Parse Tree2:23
   13. Noun Chunks4:10
3. 03Rule Based Matching4 lessons · 19 min

   1. Contextual Token Matching7:41
   2. Phrase Matching6:47
   3. Handling Large Number of Patterns3:44
   4. Course Review1:00
4. 04Pipelines and Custom Attributes10 lessons · 38 min

   1. Understanding Spacy Pipelines4:02
   2. How to Apply Particular Component3:37
   3. Manipulating the Pipeline3:51
   4. Entity Ruler1:55
   5. How to Create Custom Pipeline Components2:50
   6. Custom Sentence Segmenter5:37
   7. Efficient Text Processing Approaches6:35
   8. User Defined Attributes4:16
   9. Property Extensions2:27
   10. Method Extensions3:17
5. 05Word Vectors5 lessons · 36 min

   1. Need for Word Vectors11:16
   2. Advantage of Vector Representation4:36
   3. How Word Vectors are Computed9:21
   4. Understanding Cosine Similarity9:21
   5. Course Review1:00
6. 06Training Models2 lessons · 11 min

   1. The Training Loop4:03
   2. Train a New NER Model from Scratch7:16
7. 07Training Custom NER Models5 lessons · 15 min

   1. Training Custom NER Models5:06
   2. Training Custom NER Models - Part 23:00
   3. Training Custom NER Models - Part 32:43
   4. Training Custom NER Models - Part 42:55
   5. Course Review1:00
8. 08Training Text Classification Models - Ecommerce Reviews6 lessons · 20 min

   1. Text Classification with Textcat - Part 14:11
   2. Text Classification with Textcat - part 22:11
   3. Text Classification with Textcat - part 33:22
   4. Text Classification with Textcat - part 42:27
   5. Text Classification with Textcat - part 52:33
   6. Text Classification with Textcat - part 65:05
9. 09Training Custom POS Tagger Model3 lessons · 10 min

   1. Training Customer POS Tagger Model - part 14:21
   2. Training Customer POS Tagger Model - part 24:43
   3. Course Review1:00
10. 10Training Custom Intent Parser4 lessons · 16 min

    1. Training Custom Intent Parser - Part 14:44
    2. Training Custom Intent Parser - Part 22:47
    3. Training Custom Intent Parser - Part 33:16
    4. Training Custom Intent Parser - Part 45:19
11. 11Chatbot with Spacy and Rasa7 lessons · 26 min

    1. Building Chatbot with Spacy and Rasa5:53
    2. Intent Classification4:25
    3. NLU Pipeline2:25
    4. Training NLU Model2:33
    5. RASA Core2:03
    6. Writing Stories8:08
    7. Course Review1:00

What you need

• Basics of Python
• Foundational knowledge of Data Science
• High school maths

Who this course is for

• Data Science Aspirants
• Data Science Professionals
• Software/Data engineers interested in quantitative analysis
• Professionals working with large datasets
• Data analysts, economists, researchers

Your instructor

Prabhakaran S

Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this course!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!

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