Machine Learning with Scikit-learn, PyTorch & Hugging Face Professional Certificate
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.
– 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.
