Embedded Files
All Course Materials (PPTs/ Notes) [Section 1 & 2]
ML_Introduction_Aut25.pdf2nd_week_Notes.pdfSection-1-Week-1-Notes.pdfML24-Week2C-LogisticRegression-Sec2.pptxML23-Week2A-LinearRegression-Part1.pptxML_LinearRegression_6th_Aug.pdfML23-Week2B-LinearRegression-Part2-regularization (1).pptx2nd_week_Notes.pdfML24-DT-Part2-Sec2_SA.pptxEntropy_GI_20_Aug.pdfML_Ridge_Regression_7th_Aug.pdfDT_13_Aug.pdfML24-Probability-part1-2-S2SA.pptxBias_Varience_22_aug.pdfML_Logistic_Regression_8th_Aug.pdfML24-DT-Part1-Sec2_SA.pptxError_Decomposition_21_Aug.pdfNaive_Bayes_27_Aug.pdfNaive_Bayes_29_Aug.pdfML23-NaiveBayes.pptxSVM_4_Sep.pdfNaive_Bayes_28_Aug.pdf11-dual-gen-scribed.pdfSVM_3_Sep.pdfML24-SVM-Part1SAS2.pptxcs229-notes3.pdfClass Test Solutions
Class Test Solutions
ML_2025_SET2.pdfML_2025_SET3.pdfML_2025_SET1.pdfReference Notebooks
Reference Notebooks
Lasso Regression: Notebook
Course Coverage [Section 1 & 2]
Additional References (Handouts, Codes, Blogs)
Additional References (Handouts, Codes, Blogs)
Visualization of PLA (and later useful for neural net): Visualization of Perceptron Learning Algorithm
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