AI
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Course Description

Contents


  1. Decoding Artificial Intelligence
  2. Meaning, Scope, and Stages Of Artificial Intelligence
  3. Three Stages of Artificial Intelligence
  4. Applications of Artificial Intelligence
  5. Image Recognition
  6. Applications of Artificial Intelligence – Examples
  7. Effects of Artificial Intelligence on Society
  8. Supervises Learning for Telemedicine
  9. Solves Complex Social Problems
  10. Benefits Multiple Industries
  11. Key Takeaways

Fundamentals of Machine Learning and Deep Learning

  1. Fundamentals Of Machine Learning and Deep Learning
  2. Meaning of Machine Learning
  3. Relationship between Machine Learning and Statistical Analysis
  4. Process of Machine Learning
  5. Types of Machine Learning
  6. Meaning of Unsupervised Learning
  7. Meaning of Semi-supervised Learning
  8. Algorithms of Machine Learning
  9. Regression
  10. Naive Bayes
  11. Naive Bayes Classification
  12. Machine Learning Algorithms
  13. Deep Learning
  14. Artificial Neural Network Definition
  15. Definition of Perceptron
  16. Online and Batch Learning
  17. Key Takeaways

Machine Learning Workflow

  1. Learning Objective
  2. Machine Learning Workflow
  3. Get more data
  4. Ask a Sharp Question
  5. Add Data to the Table
  6. Check for Quality
  7. Transform Features
  8. Answer the Questions
  9. Use the Answer
  10. Key takeaways

Performance Metrics

    • Performance Metrics
    • Need For Performance Metrics
    • Key Methods Of Performance Metrics
    • Confusion Matrix Example
    • Terms Of Confusion Matrix
    • Minimize False Cases
    • Minimize False Positive Example
    • Accuracy
    • Precision
    • Recall Or Sensitivity
    • Specificity
    • F1 Score
    • Key takeaways