Lesson Archives

  1. Clustering

    • Introduction to unsupervised learning
    • Introduction to clustering
    • K-Means
    • Hierarchical clustering
  2. Descision Tree

    • Introduction to decision tree
    • Terminologies
    • Entropy and Gini index
    • Visualizing decision tree
    • Handling over fitting (Pruning)
  3. Classification

    • Logistic regression
    • Sigmoid function
    • Multi-class regression
    • Confusion matrix
    • Accuracy, Recall, Precision, F1 score
    • AUC-ROC
    • Co-relation coefficient and heatmap
    • Chi square test
    • ANNOVA
    • Random Feature elimination
    • PCA
  4. Forms

    • Template driven forms
    • Reactive forms
    • Form Validation
      • Built-in validators
      • Custom Validators
  5. Triggers

    • Introduction
    • Creating, altering, dropping triggers
    • for/after/instead of triggers
    • Introduction Creating, executing, modifying, Dropping sp's
    • Executing extended sp's
    User Defined Functions 
    • Introduction
    • Creating, executing, altering, dropping UDF’s

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