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AI/ML for Practitioners

  1. Unit: 1 Introduction for Data Analytics, Machine Learning and Artificial Intelligence
    5 Topics
  2. Unit 2: Machine Learning: Understanding jargons
    9 Topics
  3. Unit 3: Building a data science team and responsibility assignment
    6 Topics
  4. Unit 4: Python: Journey from Foundation Level
    9 Topics
  5. Unit 5: Advanced Topics Overview in Machine Learning
    6 Topics
  6. Unit 6: Statistical: Foundation building Block for Machine Learning
    9 Topics
  7. Unit 7: Applied Python with data analytics Libraries
    4 Topics
  8. Unit 8: Foundation building in Machine Learning Techniques
    7 Topics
  9. Unit 9: Supervised Machine Learning with application in Classification (Prediction)
    10 Topics
  10. Unit 10: Unsupervised Machine Learning: Clustering
    4 Topics
  11. Unit 11: Case studies: Discussions and implementations – I
    2 Topics
  12. Unit 12: Case studies: Discussions and implementations – II
    3 Topics
  13. Unit 13: Deep Learning foundation
    4 Topics
Lesson 8, Topic 3
In Progress

Linear Regression: Single and Multiple Linear Regression (Estimation)

Nikhil Shah March 26, 2021
Lesson Progress
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