Support Vector Machine FROM SCRATCH
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1
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Introduction to the Course
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Introduction To Instructor
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Why Machine Learning
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Why Support Vector Machine
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Course Overview
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2
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Introduction to Machine Learning, Learning Process and Supervised Learning
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UnSupervised Learning and Reinforcement Learning
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History and Future of Machine Learning
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Dataset, Label and Features
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Training Data,Testing Data and Outliers
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Model
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Model (Difference between Classification and Regression)
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Model (Function,Parameters,Hyperparameters)
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Training a model,Cost,Error,Loss,Risk,Accuracy
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Optimization
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Overfitting,Underfitting,Just RightOptimum (Part 1)
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Overfitting,Underfitting,Just RightOptimum (Part 2)
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Validation and Cross Validation,Generalization,Data Snooping,Validation Set
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Probability Distributions and Curse of Dimensionlity
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Small Sample Size problems,One Shot Learning
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Importance of Data in Machine Learning,Data Encoding and Preprocessing
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General Flow of a typical Machine Learning Project
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3
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Introduction to Python
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Introduction to IDE,Hello World
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Introduction to Data Type, Numbers
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Variable and Operators (Numbers)
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Variables and Operators (Rational Operators and Functions)
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Variables and Operators (String)
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Variables and Operators (String and print Statement)
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Lists(Indexing,Slicing-Built in Lists Functions)
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Lists(Copying a List)
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Tuples(Indexing,Slicing,Built in Tuple Functions)
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Set(initialize,Built in Set Functions)
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Dictionary
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Logical Operator,Decision Making,For Loops,While Loops,Functions
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Logical Operator,Decision Making,For Loops,While Loops,List Comprehension
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Functions
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Calculator Project
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4
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Introduction SVM
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Linear Discriminants
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Linear Discriminants higher spaces
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Linear Discriminants Decision Boundary
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Generalized Linear Model
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Feature Transformation
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Max Margin Linear Discriminant
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Hard Margin Vs Soft Margin
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Confidence
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Multiclass Extension
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SVM Vs Logistic Regression Sparsity
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SVM Optimization
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SVM Langrangian Dual
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Kernels
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Python Packages & Titanic DataSet
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Using Numpy, Pandas and Matplotlib (Part 1)
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Using Numpy, Pandas and Matplotlib (Part 2)
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Using Numpy, Pandas and Matplotlib (Part 3)
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Using Numpy, Pandas and Matplotlib (Part 4)
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Using Numpy, Pandas and Matplotlib (Part 5)
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Using Numpy, Pandas and Matplotlib (Part 6)
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DataSet Preprocessing
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SVM with Sklearn
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SVM without Sklearn (Part 1)
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SVM without Sklearn (Part 2)
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5
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Optional SVM Optimization (Part 1)
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Optional SVM Optimization (Part 2)
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Optional SVM Optimization (Part 3)
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Optional SVM Optimization (Part 4)
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Optional SVM Optimization (Part 5)
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Optional SVM Optimization (Part 6)