I offer end-to-end Machine Learning services focused on building robust Supervised and Unsupervised models that solve real-world business and research problems. With hands-on expertise in Python, R, Scikit-learn, TensorFlow, and PyTorch, I design, develop, and deploy intelligent solutions tailored to client needs.
My supervised learning expertise includes:
Regression Models: Linear, Logistic, Ridge, Lasso, and advanced tree-based methods.
Classification Models: Decision Trees, Random Forests, Gradient Boosting (XGBoost, LightGBM, CatBoost), and Neural Networks.
Time Series Forecasting: ARIMA, Prophet, and Deep Learning-based forecasting methods.
My unsupervised learning expertise includes:
Clustering: K-means, DBSCAN, Hierarchical Clustering.
Dimensionality Reduction: PCA, t-SNE, Autoencoders.
Anomaly Detection: Identifying fraud, outliers, and rare events in data.
Key services I provide:
Data Preparation & Feature Engineering
Model Development & Evaluation
Hyperparameter Tuning for Performance Optimization
Model Deployment & Integration with Applications
Visualization of Results & Business Insights
Why work with me?✅ Successfully delivered 50+ projects in Machine Learning, Data Science, and Analytics.✅ Strong experience in both academic research and industry applications.✅ Ability to explain technical concepts in a clear, client-friendly way.✅ On-time delivery, milestone-based approach, and complete confidentiality.
Whether it’s predicting customer behavior, detecting anomalies, or automating decision-making, I provide customized Machine Learning solutions that improve efficiency, reduce risks, and maximize growth opportunities.