Interactive guide series

Machine Learning, Explored

Seven interactive guides covering the core of applied ML — statistics, modeling, evaluation, deep learning, NLP, and system design. Drag the sliders, press play, and learn by doing.

01 Statistics & Probability Hypothesis testing, confidence intervals, Bayes' theorem, and key distributions. → 02 Machine Learning Five core ML algorithms with interactive playgrounds and live visualizations. → 03 Model Evaluation Classification metrics, ROC vs PR curves, and regression scoring. → 04 Data Cleaning & Preprocessing Missing values, feature scaling & encoding, and outlier detection with SMOTE. → 05 Deep Learning Neural networks & backpropagation, CNNs, and regularization with optimizers. → 06 NLP & Generative AI Transformer self-attention, LoRA fine-tuning, and RAG pipelines. → 07 Business Cases & ML System Design A/B test sample sizing and fraud detection ML system design walkthroughs. →
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