This repository consists of all the files, resources, and recorded session links which are discussed during Machine Learning using Python Online Training.

Everyone should compulsory follow the below instruction in order to get the attendance --> Certificate

1. Login format rollnumber-name-college
2. Don't give spaces in roll number or shorcut of your roll number
3. Don't give spaces between rollnumber and name (only - single minus or hyphen character)
4. Make sure roll number should match with the registered roll number
5. Minimum 120/150 minutes should attend in 150/180 minutes session with same login format

1. Ml Introduction
2. ML Types
3. Ml Use cases
4. Difference b/w ML AI,DL
5. ML life cycle
6. Types of variables in stastics

[Day5-_Notebook_Link]

[DayNo_Recorded_Video_Link]

• Diffent types of machine learning algorithems
• Simple Linear Regression
  • Intution
  • statistical Formula's
  • Evolution Metrics

[Day6-_Notebook_Link]

[DayNo_Recorded_Video_Link]

• Linear Regression with Multiple variables
  • Linear Equation
  • Preprocessing data
  • Evalution Metrics for LR
• Non-Linear Regression
• Polynomial Regression
  • formula
    • y=ax^2+bx^1+cx^0+c+e
  • Transforming normal features into polynomail features with degree
  • Finfinding the evalution metrics of model

[Day7-_Notebook_Link]

• what us over fitting
• what is under fitting
• How to handle that over fitting and under fitting problems in ML
• Bias,Variance
• Calculations behind the L1 & L2 Regularisation's

[Day8 -note book]