Support Vector Machine A-Z: Support Vector Machine Python ©

BY
Udemy

Lavel

Beginner

Mode

Online

Fees

₹ 2899

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course and certificate fees

Fees information
₹ 2,899
certificate availability

Yes

certificate providing authority

Udemy

The syllabus

Introduction to course

  • Introduction to the Course
  • Introduction To Instructor
  • Why Machine Learning
  • Why Support Vector Machine
  • Course Overview
  • Please give us some feedback and Review
  • Link to the Python codes for the projects and the data

Introduction to Machine Learning

  • Link to the Python codes for the projects and the data
  • Introduction to Machine Learning, Learning Process and Supervised Learning
  • UnSupervised Learning and Reinforcement Learning
  • History and Future of Machine Learning
  • Dataset, Label and Features
  • Training Data,Testing Data and Outliers
  • Model
  • Model (Difference between Classification and Regression)
  • Model (Function,Parameters,Hyperparameters)
  • Training a model,Cost,Error,Loss,Risk,Accuracy
  • Optimization
  • Overfitting,Underfitting,Just RightOptimum (Part 1)
  • Overfitting,Underfitting,Just RightOptimum (Part 2)
  • Validation and Cross Validation,Generalization,Data Snooping,Validation Set
  • Probability Distributions and Curse of Dimensionlity
  • Small Sample Size problems,One Shot Learning
  • Importance of Data in Machine Learning,Data Encoding and Preprocessing
  • General Flow of a typical Machine Learning Project

Introduction to Python

  • Link to the Python codes for the projects and the data
  • Introduction to Python
  • Introduction to IDE,Hello World
  • Introduction to Data Type, Numbers
  • Variable and Operators (Numbers)
  • Variables and Operators (Rational Operators and Functions)
  • Variables and Operators (String)
  • Variables and Operators (String and print Statement)
  • Lists(Indexing,Slicing-Built in Lists Functions)
  • Lists(Copying a List)
  • Tuples(Indexing,Slicing,Built in Tuple Functions)
  • Set(initialize,Built in Set Functions)
  • Dictionary
  • Logical Operator,Decision Making,For Loops,While Loops,Functions
  • Logical Operator,Decision Making,For Loops,While Loops,List Comprehension
  • Functions
  • Calculator Project

Support Vector Machine

  • Link to the Python codes for the projects and the data
  • Introduction SVM
  • Linear Discriminants
  • Linear Discriminants higher spaces
  • Linear Discriminants Decision Boundary
  • Generalized Linear Model
  • Feature Transformation
  • Max Margin Linear Discriminant
  • Hard Margin Vs Soft Margin
  • Confidence
  • Multiclass Extension
  • SVM Vs Logistic Regression Sparsity
  • SVM Optimization
  • SVM Langrangian Dual
  • Kernels
  • Python Packages & Titanic DataSet
  • Using Numpy, Pandas and Matplotlib (Part 1)
  • Using Numpy, Pandas and Matplotlib (Part 2)
  • Using Numpy, Pandas and Matplotlib (Part 3)
  • Using Numpy, Pandas and Matplotlib (Part 4)
  • Using Numpy, Pandas and Matplotlib (Part 5)
  • Using Numpy, Pandas and Matplotlib (Part 6)
  • DataSet Preprocessing
  • SVM with Sklearn
  • SVM without Sklearn (Part 1)
  • SVM without Sklearn (Part 2)

Optional SVM Section

  • Link to the Python codes for the projects and the data
  • Optional SVM Optimization (Part 1)
  • Optional SVM Optimization (Part 2)
  • Optional SVM Optimization (Part 3)
  • Optional SVM Optimization (Part 4)
  • Optional SVM Optimization (Part 5)
  • Optional SVM Optimization (Part 6)

Bonus Lecture

  • Link to the Python codes for the projects and the data
  • THANK YOU Bonus Video

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