ML Developer | Data Science | Agentic AI
Languages
Libraries & Frameworks
Tools & Databases
| Category | Algorithms |
|---|---|
| Supervised | Linear & Logistic Regression, Ridge, Lasso, ElasticNet, KNN, Naive Bayes, Decision Trees, Random Forest, Gradient Boosting, AdaBoost, SVM, XGBoost, Voting & Stacking Ensembles |
| Unsupervised | K-Means, DBSCAN, Hierarchical Clustering, Isolation Forest, LOF, PCA |
| Deep Learning | ANN, CNN, RNN, Activation Functions |
| Reinforcement Learning | SARSA, Q-Learning โ practiced on FrozenLake, CliffWalking, and Taxi environments |
๐ Machine Learning Journey โ End-to-end ML practice covering supervised & unsupervised algorithms, real datasets, SQL analytics, web scraping, and projects like the CreditWise Loan System.
๐ง Deep Learning โ ANN, CNN, and RNN implementations along with activation function experiments.
๐ฎ Reinforcement Learning โ SARSA and Q-Learning implementations practiced across FrozenLake, CliffWalking, and Taxi environments.