人工智能与机器学习基础

Official materials pageHTML ↓ Official public syllabusHTML ↓ Related classesPDF ↓ Summer 2020 syllabusHTML ↓ Summer 2020 syllabus · alternateHTML ↓

CS229 IntroPPTX ↓ cs229-notes1PDF ↓ cs229-notes2PDF ↓ cs229-notes3PDF ↓ cs229-notes4PDF ↓ cs229-notes5PDF ↓ cs229-notes6PDF ↓ cs229-notes7aPDF ↓ cs229-notes7bPDF ↓ cs229-notes8PDF ↓ CS229_NOTE8 · alternatePDF ↓ cs229-notes9PDF ↓ cs229-notes10PDF ↓ cs229-notes11PDF ↓ cs229-notes12PDF ↓ cs229-notes13PDF ↓ Deep learning notesPDF ↓ Maximum EntropyPDF ↓ Bias–Variance AnalysisPDF ↓ Advice for applying machine learningPDF ↓ Evaluation MetricsPPTX ↓

Linear algebra reviewPDF ↓ Probability reviewPDF ↓ Convex optimization IPDF ↓ Convex optimization IIPDF ↓ Hidden Markov ModelsPDF ↓ GaussiansPDF ↓ More on GaussiansPDF ↓ Summer 2020 · Linear algebraPDF ↓ Summer 2020 · Linear algebra slidesPDF ↓ Summer 2020 · ProbabilityPDF ↓ Summer 2020 · Probability slidesPDF ↓ Summer 2020 · GaussiansPDF ↓ Summer 2020 · More on GaussiansPDF ↓ Summer 2020 · Gaussian processesPDF ↓

Problem Set 0 · templatePDF ↓ Problem Set 1PDF ↓ Problem Set 1 · dataZIP ↓ Problem Set 2PDF ↓ Problem Set 2 · dataZIP ↓ Problem Set 3PDF ↓ Problem Set 3 · dataZIP ↓

matlab_session.mMATLAB ↓ logistic_grad_ascent.mMATLAB ↓ sigmoid.mMATLAB ↓

Lecture 1PDF ↓ Lecture 19PDF ↓ Linear algebra reviewPDF ↓ Linear algebra review slidesPDF ↓ Linear algebra annotated slidesPDF ↓ Probability reviewPDF ↓ Probability review slidesPDF ↓ Python review slidesPDF ↓ Python review materialsZIP ↓ BoostingPDF ↓ Convolutional networksPDF ↓ Decision treesPDF ↓ Evaluation metricsPDF ↓ Midterm reviewPDF ↓