Machine Learning Portfolio

Explore the repository featuring a series of machine learning projects i've done from various online sources , encompassing Classical Machine Learning techniques like Rregression, Classification, Clustering and Boosting Algorithms 🚀

Each project, is done for academic and self-learning purposes is presented in the form of Jupyter Notebooks.

Tools Utilized: NumPy, Pandas, Seaborn, Matplotlib, Scikit-learn, Hyperopt, TPOT and many more... 🛠️

Let's connect : LinkedIn 🤝

Project Structure

1. Introduction
2. Data Wrangling / Feature Engineering
3. Exploratory Data Analysis
4. Model Building
5. Evaluation and Conclusion

Notebook Showcase

Let the code speak.....

• Project Title 1: Unleash the power of feature engineering in a captivating machine learning journey.

• Project Title 2: Navigate through the intricacies of model building, training, and optimal evaluation.