Brochure
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- 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
Support Vector Machine A-Z: Support Vector Machine Python ©
Quick Facts
| particular | details | |||
|---|---|---|---|---|
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course and certificate fees
Fees information
₹ 2,899
certificate availability
Yes
certificate providing authority
Udemy
The syllabus
Introduction to course
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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