Back

Machine Learning Roadmap - Beginner

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

1

Mathematics Foundations

3 weeks
  • ▹Linear Algebra (Vectors, Matrices, Operations)
  • ▹Calculus Basics (Derivatives, Gradients, Partial Derivatives)
  • ▹Probability & Statistics Basics
  • ▹Distributions (Normal, Binomial, Poisson)
  • ▹Bayes’ Theorem
2

Python for ML

2 weeks
  • ▹NumPy Basics
  • ▹Pandas for Data Handling
  • ▹Matplotlib & Seaborn for Visualization
  • ▹Jupyter Notebook Workflow
  • ▹Mini-Project: Data Cleaning & Visualization
3

Introduction to ML

2 weeks
  • ▹What is Machine Learning?
  • ▹Types of ML (Supervised, Unsupervised, Reinforcement)
  • ▹ML Workflow (Data → Model → Evaluate → Deploy)
  • ▹Overfitting vs Underfitting
  • ▹Bias-Variance Tradeoff
4

Data Preprocessing

2 weeks
  • ▹Handling Missing Values
  • ▹Encoding Categorical Variables
  • ▹Feature Scaling (Normalization & Standardization)
  • ▹Train-Test Split
  • ▹Mini-Project: Titanic Survival Prediction (Data Preprocessing)
GeekDost - Roadmaps & Snippets for Developers