Machine Learning Course using Python

  • What is Machine Learning?
  • History of Machine Learning
  • How Artificial Intelligence relates to Machine Learning
  • Data Science vs Machine Learning
  • Fundamentals of Machine Learning
  • Introduction to K- nearest neighbour method
  • Different phases of predictive modelling
  • Understanding tasks and work using an example classification problem
    based on the K- nearest neighbour method
  • Implementation using the scikit- learn library
  • Classification
    • Decision tree
    • Naïve bayes
    • Logistic Regression
    • Know your neighbour (KKN)
    • Support vector machine
  • Regression
    • Linear Regression
    • Support vector machine
    • Know your neighbor (KKN)
    • Ridge regression
  • What is model complexity
  • What is Generalization performance
  • Understanding the connection between Model Complexity and
    Generalization performance
  • Importance of proper feature scaling
  • How to control model complexity by applying techniques like
    regularization to avoid overfitting
  • Use of cross-validation for model evaluation
  • Evaluation
    • Understanding of evaluation and model section methods
    • Optimize the performance of the machine learning model
  • Advance supervised machine learning concepts
    • Ensembles of tree (random forests, grading boosted trees)
    • Neural networks (with an optional summary on deep learning)
    • Learning the critical problem of data leakage in machine learning and
      how to detect and avoid it
  • K- Mean clustering
  • Document retrieval : A case study in clustering and measuring
    similarity
  • Recommending products
  • Unsupervised Learning- Deep Learning
  • Meaning and importance of deep learning
  • Artificial neural networks
  • Introduction to Tensor flow
  • Introductory remark about python
  • A brief history of python
  • How python is different from other languages
  • Python versions
  • IDLE
  • How to execute a python program
  • Writing your first program
  • Python keywords and identifiers
  • Python statements
  • Comments in python
  • Command line arguments
  • Getting user input
  • Exercise
  • Variable and Data Type
    • Introduction
    • Variables
    • Data Types
    • Numbers
    • Strings
    • Lists, Tuples and dictionary
    • Exercise
  • Decision making and Loops
    • Introduction
    • Control Flow and Syntax
    • The if statement
    • Python Operators
    • The while loop
    • Break and continue
    • The For loop
    • Pass statement
    • Exercise
  • Functions
    • Introduction
    • Calling a function
    • Function arguments
    • Built in functions
    • Scope of variables
    • Decorators
    • Passing function to function
    • Lambda
    • Closures
    • Exercise
  • Modules and packages
    • Introduction to modules
    • Importing modules
    • Standard modules-sys
    • Standard module-OS
    • The dir function
    • Packages
    • Exercise
      • Exception Handling
        • Error
        • Run time Error
        • Handling IO Exception
        • Try Except statement
        • Raise
        • Assert
        • Exercise
      • Files and directories
        • Introduction
        • Writing Data to a file
        • Reading Data from a file
        • Additional file methods
        • Working with files
        • Working with Directories
        • Exercise
      • Class and objects
        • Introduction to classes and objects
        • Creating classes
        • Instance methods
        • Special class method
        • Inheritance
        • Method overriding
        • Data hiding
        • Exercise
      • Regular Expressions
        • Introduction
        • Match function
        • Search function
        • Grouping
        • Matching at Beginning or end
        • Match objects
        • Flags
        • Exercise
      • Socket Programming
        • What are Sockets?
        • Creating sockets
        • Server client- socket methods
        • Connecting client-server
        • Client-server chatting program
        • Exercise
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