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vedant_pawale

Vedant Pawale

@vedant_pawale

Machine Learning Engineer, Predictive Modeling and Data Analysis

Índia
Inglês, Hindi, Marata
Algumas informações são exibidas no idioma inglês.
Sobre mim
I'm a Machine Learning engineer specializing in classical ML — regression, classification, and predictive modeling using Python. I build clean, production-ready models (Random Forest, XGBoost, and other tree-based methods) with a focus on data preprocessing, feature engineering, and model evaluation. I deliver documented code, clear performance metrics, and a README explaining how the model works and how to use it. Currently pursuing a B.Tech in AI & ML Engineering, I combine academic rigor with hands-on project experience — no unnecessary complexity, just reliable, interpretable ML solutions.... Saiba mais

Habilidades

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vedant_pawale
Vedant Pawale
offline • 
Tempo médio de resposta: 1 hora

Conheça meus serviços

Machine learning
I will build a machine learning model for prediction and classification
A partir deUS$ 90 /projetoMais detalhes

Portfólio

Experiência profissional

Self-Employed_/ Freelancer

Freelance Machine Learning Developer

Self-Employed / Freelancer • Autônomo

Jul 2026 - Present • 3 mos

Building and delivering end-to-end machine learning solutions including classification, regression, and predictive analytics models. Projects span credit risk assessment, customer churn prediction, and sales forecasting — covering data preprocessing, model training, evaluation, and clear documentation for non-technical stakeholders. Actively developing a portfolio of pure ML solutions (no deep learning) for real-world business problems.

CodeAlpha

Machine Learning Intern

CodeAlpha • Meio período

Aug 2026 - Sep 2026 • 1 mo

Completed a virtual internship in Machine Learning with CodeAlpha, working on real-world ML problems across the end-to-end pipeline — data preprocessing, feature engineering, model building, and evaluation. Strengthened practical skills in Python, scikit-learn, and applied ML workflows while delivering task-based projects within program deadlines.