WISE: Technical ML201

Unit 01

• CFP

• Session 1

  • Environment Setup

• Session 2

  • Introduction to ML
  • Examples

• Session 3

  • Sage Math

• CFU

Unit 02

• CFP

• Session 1

  • Linear Algebra

    • Introduction to Matrices
    • Types of Matrices, Vectors

• Session 2

  • Numpy
  • Exercises on Numpy

• Session 3

  • Linear Algebra

    • Matrix Operations

• CFU

Unit 03

• CFP

• Session 1

  • Eigen Values and Vectors

• Session 2

  • Scipy
  • Exercises on Scipy

• Session 3

  • Operations on Vectors

• CFU

Unit 04

• CFP

• Session 1

  • Data: Acquiring, Cleaning and Exploring

• Session 2

  • Pandas
  • Exercises on Pandas

• Session 3

  • Derivatives

• CFU

Unit 05

• CFP

• Session 1

  • Chain Rule

• Session 2

  • Matplotlib
  • Exercises on Matplotlib

• Session 3

  • Integration

• CFU

Unit 06

• CFP

• Session 1

  • Probability

    • Sampling of the data

• Session 2

  • Probability Distributions
  • Exercises

• Session 3

  • Sampling from a population (Exercise)

• CFU

Unit 07

• CFP

• Session 1

  • Distribution of Statistic
  • Exercises

• Session 2

  • ML Pipeline

• Session 3

  • Properties of Mean
  • Mean, SD and Histograms

• CFU

Unit 08

• CFP

• Session 1

  • SD and normal Curve
  • Exercises

• Session 2

  • Central Limit theorem

• Session 3

  • Exercises related to Central Limit theorem

• CFU

Unit 09

• CFP

• Session 1

  • Percentiles
  • The BootStrap

• Session 2

  • Exercises on Session 1 topics

• Session 3

  • Confidence Intervals
  • Exercises

• CFU

Unit 10

• CFP

• Session 1

  • Hypotheses testing

• Session 2

  • Assessing Models
  • Exercises

• Session 3

  • Decisions and Uncertainty
  • Exercises

• CFU

Unit 11

• CFP

• Session 1

  • Regression

• Session 2

  • Exercises on Regression

• Session 3

  • Gradients

• CFU

Unit 12

• CFP

• Session 1

  • Gradient Descent

• Session 2

  • Exercises on Gradient Descent

• Session 3

  • Regression vs Classification: Linear Classifier
  • Exercises

• CFU