π Passionate about Machine Learning, Data Analysis, and AI-driven solutions.
β‘ Strong foundation in Python, classical ML, and applied AI for real-world engineering problems.
π Working on EV Intelligent Energy Management Systems (IEMS), Fault Detection, and Predictive Modeling.
- π§ Background in Electrical Engineering with specialization in Power Systems
- π Skilled in Data Cleaning, EDA, Feature Engineering, Model Building & Evaluation
- π§ͺ Building portfolio projects across ML, NLP, CV, and Deployment
- π Applying ML in power systems & EV domains (Fault Detection, IEMS)
- Python, NumPy, Pandas, Matplotlib, Seaborn
- Jupyter Notebook, VS Code
- MATLAB, Simulink
- scikit-learn, XGBoost, Random Forest, Logistic Regression, SVM
- Hyperparameter Tuning (GridSearchCV, RandomizedSearchCV)
- Cross-Validation, Pipelines, Feature Importance
- TensorFlow / Keras
- CNNs, RNNs / LSTMs
- Transformers (planned)
- Git / GitHub
- Streamlit & Flask (Deployment)
- Excel, Data Visualization
- Random Forest + RandomizedSearchCV
- Feature importance (RMS currents, voltages)
- Real engineering application
π Repo: https://github.com/Darksteel047/fault_detection_by_logistic_reg_randomforest_classifier
- Text vectorization using TF-IDF
- Compared Naive Bayes & Logistic Regression
- Added confusion matrix for both models
- 98β99% accuracy on test set
π Repo: https://github.com/Darksteel047/email_spam_detection
- Regression pipeline with preprocessing
- EDA + residual analysis
- Clean, beginner-friendly regression model
π Repo: https://github.com/Darksteel047/rainfall-prediction-eda-linear_reg
- Full EDA & visualization project
- Insights on restaurants, ratings, online orders
- Great for portfolio readability
π Repo: https://github.com/Darksteel047/Zomato_EDA
- π LinkedIn: https://in.linkedin.com/in/arnavjyoti-kalita-00747ag
- π GitHub: https://github.com/darksteel047