课程概述
Welcome to the Foundations of Machine Learning, your practical guide to fundamental techniques powering data-driven solutions. Master key ML domains—supervised learning (prediction), unsupervised learning (pattern discovery), data preprocessing & feature engineering, and time series forecasting—using Pandas, Scikit-learn, Statsmodels, and Prophet to tackle real-world challenges.
By the end of this course, you'll be able to:
- Implement and evaluate key supervised models (e.g., regression, classification, Tree-based models & SVMs) for prediction.
- Apply unsupervised methods (e.g., K-Means, Isolation Forest) for segmentation and anomaly detection.
- Perform robust data preprocessing: handle missing data, encode categoricals, scale features, and apply dimensionality reduction (PCA).
- Build and analyze time series forecasts with ARIMA, Exponential Smoothing, Holt-Winters and Prophet.
Through hands-on exercises and a capstone customer purchase prediction project, you'll develop versatile skills to confidently address common machine learning challenges.
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1 - Foundations of Machine Learning 的 2 个评论（共 2 个）
创建者 Najeebullah
•Dec 12, 2025
The Perfect journey-styled build course! I was very confused in from where to start learning ML this helped me alot
创建者 Jesús M
•Oct 5, 2025
excelente curso, para mi formación profesional