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Machine Learning Roadmap
Linear Algebra Basics (Vectors, Matrices)
Calculus for ML (Derivatives, Gradients)
Information Theory (Entropy, KL Divergence)
Mathematical Foundations
Probability & Statistics
Optimization Basics (Gradient Descent)
Python for ML (NumPy, Pandas)
Jupyter Notebooks
Programming & Tools
Data Visualization (Matplotlib, Seaborn)
Scikit-learn Basics
Types of ML (Supervised, Unsupervised, Reinforcement)
Overfitting vs Underfitting
Feature Engineering & Scaling
Core ML Concepts
Bias-Variance Tradeoff
Cross-Validation
Model Evaluation Metrics (Accuracy, Precision, Recall, F1, AUC)
Linear Regression
Decision Trees
Support Vector Machines (SVM)
Naive Bayes
Supervised Learning
Logistic Regression
Random Forests
k-Nearest Neighbors (kNN)
Gradient Boosting (XGBoost, LightGBM, CatBoost)
Clustering (k-Means, Hierarchical, DBSCAN)
Anomaly Detection
Unsupervised Learning
Dimensionality Reduction (PCA, t-SNE, UMAP)
Association Rule Learning (Apriori, FP-Growth)
Introduction to Neural Networks
Forward & Backpropagation
RNNs & LSTMs
GANs (Generative Adversarial Networks)
Deep Learning
Activation Functions
CNNs (Convolutional Neural Networks)
Transformers & Attention Mechanisms
Transfer Learning
TensorFlow Basics
Model Deployment (Flask, FastAPI, Docker)
Experiment Tracking
ML Engineering & Tools
PyTorch Basics
ML Pipelines & Workflow (Airflow, MLflow, Kubeflow)
Model Serving & APIs
Reinforcement Learning (Q-Learning, Deep Q Networks)
Natural Language Processing (Word2Vec, BERT, GPT)
Time Series Forecasting
Ethics & Fairness in AI
Advanced Topics
Recommendation Systems
Computer Vision (Image Classification, Object Detection)
AutoML
House Price Prediction
Movie Recommendation System
Sentiment Analysis on Tweets
Practical Projects
Spam Email Classifier
Image Classification (Cats vs Dogs)
Stock Price Prediction
ML Conceptual Q&A
Feature Engineering Scenarios
Coding ML Problems (Kaggle-style)
Interview Preparation
Case Studies (Fraud Detection, Ads Ranking, Search)
System Design for ML (Data Pipelines, Model Serving)
Machine Learning Roadmap
