Tutors

Innomatics Research Labs

PROGRAM OVERVIEW

CURRICULUM

  Machine Learning

  • Intro to ML - 1
  • Intro to ML - 2
  • Data Pre Processing Files
  • Simple Linear Regression Files
  • Simple Linear Regression
  • Data Pre Processing
  • Math Behind
  • Linear Regression and Gradient Descent
  • Linear Regression - III
  • Gradient Descent
  • Multiple Regression Lab
  • Polynomial Regression
  • Multiple Regression lab File
  • Polynomial Regression and Regression Project Files
  • Class File on Simple Multiple and Polynomial Regression Topics
  • Regression evaluation metrics Bias variance tradeoff Underfitting - Overfitting
  • binary classification example project
  • Complete Kaggle Tutorial
  • Bias and variance , underfitting, Overfitting revision Regularisation : L1 and L2 and Lab
  • Logistic Regression
  • Regularization and Logistics Regression Files
  • Classification Evaluation Metrics
  • kNN
  • kNN Files
  • Revision & Doubts Session - Topics Till Dates
  • Decision Tree
  • Decision Tree - II
  • Imabalabce dataset and Hyper parameter tunning
  • Decision Tree Files
  • Ensemble Techniques - Random Forest
  • SVM & Boosting
  • Clustering
  • Revision
  • Project Doubts and Support
  • Feature Selection - Multicollinearity and Forward backwards with Lab
  • Ensemble - random forest and Bossting Files with Project Lab
  • SVM Theory Files
  • Clustering theory and Lab File
  • Imbalanced Data Classification Lab File
  • Hyperparameter Tuning lab File

  Projects

  • ML Classification Project
  • ML Regression Project