Deep Learning NLP with spaCy


Unlock the power of AI and enhance your expertise with our course on spaCy, a cutting-edge, open-source library for advanced Natural Language Processing (NLP) in Python. Elevate your knowledge and upskill in the trending field of AI, exploring practical applications like ChatGPT. spaCy seamlessly integrates with renowned AI frameworks such as TensorFlow, PyTorch, Scikit-learn, and Gensim, fostering a dynamic ecosystem for deep learning. This course is meticulously crafted to empower you in constructing sophisticated statistical models for various NLP challenges, ensuring that your skills are not just theoretical but applicable to real-world projects. Join us to delve into spaCy’s capabilities and stay ahead in the ever-relevant world of AI and chatbot development.

Course Objectives:

  • Non-destructive tokenization
  • Named entity recognition
  • Pre-trained word vectors
  • Deep learning integration
  • Part-of-speech tagging


7 hours, 1 Day Course

Mode of Delivery

Classroom-based, Instructor-led Training

Course Outlines

  1. Get Started spaCy
    1. What is NLP
    2. Applications of NLP
    3. Online NLP Demo
    4. What is spaCy
    5. Install spaCy and Download Models
  2. Linguistic Features
    1. spaCy nlp Process
    2. Tokenization
    3. Stop Words
    4. Stemming
    5. Lemmatizing
    6. Part of Speech Tagging
    7. Dependency Parsing
    8. Visualizing Dependency and POS
    9. Named Entities Recognition
  3. Processing Pipelines
    1. What is Processing Pipeline
    2. Default Pipeline Components
    3. Disable Pipeline Component
    4. Rename Pipeline Component
    5. Add Custom Pipeline Component
  4. Vectors and Similarity
    1. What is Word Vectorization
    2. Count Vectorization
    3. Word2Vec
    4. Word2Vec using Gensim
    5. spaCy Pre-trained Vectors
    6. Word Similarity
  5. Machine Learning with spaCy
    1. Machine Learning Frameworks
    2. Machine Learning Workflow
    3. Text Classification with SciKit Learn and spaCy