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Machine Learning Roadmap - Intermediate

Follow this step-by-step roadmap to master machineLearning at Intermediate level

1

Supervised Learning

4 weeks
  • ▹Linear Regression
  • ▹Logistic Regression
  • ▹Decision Trees
  • ▹Random Forests
  • ▹Support Vector Machines (SVM)
  • ▹K-Nearest Neighbors (KNN)
  • ▹Mini-Project: House Price Prediction
2

Unsupervised Learning

3 weeks
  • ▹Clustering (K-Means, Hierarchical, DBSCAN)
  • ▹Dimensionality Reduction (PCA, t-SNE)
  • ▹Association Rule Mining (Apriori, FP-Growth)
  • ▹Mini-Project: Customer Segmentation
3

Model Evaluation & Validation

3 weeks
  • ▹Cross Validation
  • ▹Confusion Matrix
  • ▹Precision, Recall, F1-Score
  • ▹ROC Curve & AUC
  • ▹Hyperparameter Tuning (Grid Search, Random Search)
  • ▹Mini-Project: Credit Card Fraud Detection
4

Feature Engineering

2 weeks
  • ▹Feature Selection Techniques
  • ▹Polynomial Features
  • ▹Feature Importance
  • ▹Dimensionality Reduction for Features
  • ▹Mini-Project: Spam Email Classifier
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