Name
L1 - Introduction to Machine Learning.key
L1 - Introduction to Machine Learning.pdf
L2 - Decision Trees.key
L2 - Decision Trees.pdf
L3 - Basic Concepts.key
L3 - Basic Concepts.pdf
L4 - Nearest Neighbours.key
L4 - Nearest Neighbours.pdf
L5 - Perceptron.key
L5 - Perceptron.pdf
L5b - Functions and Objects in Python Primer.key
L5b - Functions and Objects in Python Primer.pdf
L6 - Features and Evaluation.key
L6 - Features and Evaluation.pdf
L7 - Linear Models.key
L7 - Linear Models.pdf
L8 - Probabilistic Modeling.key
L8 - Probabilistic Modeling.pdf
L9-10 - Neural Networks.key
L9-10 - Neural Networks.pdf
L11 - Kernel Methods.key
L11 - Kernel Methods.pdf
L12 - Unsupervised Learning.key
L12 - Unsupervised Learning.pdf
L13 - Mixture Models and EM.key
L13 - Mixture Models and EM.pdf
L14 - EM in General.key
L14 - EM in General.pdf
L15 - Dimensionality Reduction.key
L15 - Dimensionality Reduction.pdf
L16 - Deep Learning.key
L16 - Deep Learning.pdf
L16 - Deep Learning.pdf
L16 - Deep Learning.pptx
L17 - Revision.key
L17 - Revision.pdf
Neural Networks - XOR Demo.xlsx
What is F20ML.pdf
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