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 🤝
- Introduction
- Data Wrangling / Feature Engineering
- Exploratory Data Analysis
- Model Building
- Evaluation and Conclusion
Let the code speak.....
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Project Title 1: Unleash the power of feature engineering in a captivating machine learning journey.
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Project Title 2: Navigate through the intricacies of model building, training, and optimal evaluation.