• Course Structure & Outline Free
  • About this Series Free
  • Setting Expectations Free

  • Supervised vs. Unsupervised Learning Free
  • Classification vs. Regression Free
  • RECAP: Key Concepts Free
  • Classification 101 Free
  • Classification Workflow Free
  • Feature Engineering Free
  • Data Splitting Free
  • Overfitting Free
  • QUIZ: Intro to Classification Free

  • Common Classification Models Free
  • Intro to K-Nearest Neighbors (KNN) Pro
  • KNN Examples Pro
  • CASE STUDY: KNN Pro
  • Intro to Naïve Bayes Pro
  • Naïve Bayes | Frequency Tables Pro
  • Naïve Bayes | Conditional Probability Pro
  • CASE STUDY: Naïve Bayes Pro
  • Intro to Decision Trees Pro
  • Decision Trees | Entropy 101 Pro
  • Entropy & Information Gain Pro
  • Decision Tree Examples Pro
  • Random Forests Pro
  • CASE STUDY: Decision Trees Pro
  • Intro to Logistic Regression Pro
  • Logistic Regression Example Pro
  • False Positives vs. False Negatives Pro
  • Logistic Regression Equation Pro
  • The Likelihood Function Pro
  • Multivariate Logistic Regression Pro
  • CASE STUDY: Logistic Regression Pro
  • Intro to Sentiment Analysis Pro
  • Cleaning Text Data Pro
  • Bag of Words Analysis Pro
  • CASE STUDY: Sentiment Analysis Pro
  • QUIZ: Classification Models Pro

  • Intro to Selection & Tuning Pro
  • Hyperparameters Pro
  • Imbalanced Classes Pro
  • Confusion Matrix Pro
  • Accuracy, Precision & Recall Pro
  • Multi-class Confusion Matrix Pro
  • Multi-class Scoring Pro
  • Model Selection Pro
  • Model Drift Pro
  • QUIZ: Model Selection & Tuning Pro

  • Looking Ahead to Part 3 Pro
  • Course Feedback Survey Pro
  • Share the Love Pro
  • Next Steps Pro