🚀 Roadmap to Master Machine Learning in 50 Days! 🤖📊

📅 Week 1–2: ML Basics Math
🔹 Day 1–5: Python, NumPy, Pandas, Matplotlib
🔹 Day 6–10: Linear Algebra, Statistics, Probability

📅 Week 3–4: Core ML Concepts
🔹 Day 11–15: Supervised Learning – Regression, Classification
🔹 Day 16–20: Unsupervised Learning – Clustering, Dimensionality Reduction

📅 Week 5–6: Model Building Evaluation
🔹 Day 21–25: Train/Test Split, Cross-validation
🔹 Day 26–30: Evaluation Metrics (MSE, RMSE, Accuracy, F1, ROC-AUC)

📅 Week 7–8: Advanced ML
🔹 Day 31–35: Decision Trees, Random Forest, SVM, KNN
🔹 Day 36–40: Ensemble Methods (Bagging, Boosting), XGBoost

🎯 Final Stretch: Projects Deployment
🔹 Day 41–45: ML Projects – e.g., House Price Prediction, Spam Detection
🔹 Day 46–50: Model Deployment (Flask + Heroku/Streamlit), Intro to MLOps

💡 Tools to Learn:
• Scikit-learn
• Jupyter Notebook
• Google Colab
• Git GitHub

💬 Tap ❤️ for more!