Tutors

Innomatics Research Labs

PROGRAM OVERVIEW

CURRICULUM

  Machine Learning

  • Introduction AI/ML
  • Understanding ML Frame Work
  • Solving a ML Problem
  • Data Preprocessing I - Handling Missing values -- Fill, drop techeniques
  • Data Preprocessing Lab - II Handling Outliers , Parsing Date features
  • Data Preprocessing - III Encoding categorical features -- One Hot encoding
  • Data Pre Processing - IV Encoding categorical features -- Label Encoding, Ordinal Encoding
  • Data PrePrecossing LAB V - Train test split, Feature Scaling, Building a ML Model
  • Data PrePrecossing LAB - Text PreProcessing
  • Data PrePrecossing LAB - Text PreProcessing - Bag of words/Count Vectorizer
  • Intro to Data Science AI and ML Class File
  • Solving the Problems in Machine Learning Class File
  • Tabular Data Pre Processing Class File
  • Unstructured Text Data preprocessing Class File
  • Tabular Data PreProcessing Lab File
  • Text Preprocessing Lab File
  • Text Pre Processing TF IDF and Project Discussion
  • Text Pre Processing Updated File
  • Image Preprocessing - I
  • Image preprocessing File
  • Image Preprocessing - II
  • Image Processing - III
  • MNIST - Hand Written Digit Recognition File
  • Introduction to Vectors & Scalars (Linear Algebra - Part 1
  • Dot Product, Distance calculation (Linear Algebra - Part 2 )
  • Projection vector, Equation of line - (Linear Algebra - Part 3)
  • Simple Linear Regression Algorithm
  • Gradient Descent
  • LInear Algebra Complete Concept PDF
  • Simple Linear Regression Class PDF
  • Derivation of Gradient Descent Class PDF
  • Gradient Descent - II
  • Simple Linear Regression using Gradient Descent -- Lab
  • Gradient Descent File
  • Multiple Linear Regression
  • Multiple Linear Regression PDF
  • Simple and Multiple Regression Lab File
  • Usecase : Startup Profit Prediction(Multiple Linear Regression)
  • Metrics - Understanding R2 Score and Linear regression Assumptions
  • Assumption of Linear Regression and Metrics
  • Machine Learning - Equation for Hyper plane. PDF
  • Assumption of Linear Regression PDF
  • Metrics - Regression PDF
  • Multiple Linear Regression - Assumption and Metrics updated Lab File
  • Logistics Regression -Geometric Interpretation Part I
  • Logistics Regression PDF
  • Logistic Regression- Geometric Interpretation - Part 2
  • Logistic Regression Lab
  • Logistic Regression -- Lab File
  • Logistic Regression -- Lab, Confusion Matrix, Polynomial Features
  • Polynomial Regression Lab Files
  • Polynomial Features, Sk-Learn Pipeline
  • kNN Algorithm
  • kNN - Part 2
  • kNN - Part 3
  • kNN Files Lab
  • SVM
  • SVM _ Part 2
  • SVM - Part 3
  • SVM Lab File
  • SVM PDF
  • Metrics PDF
  • Naiva Bayes
  • Naives Bayes PDF
  • Bayes Theorem PDF
  • Naive Bayes - Part 2

  Assignments

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  Projects

  • NLP _ Text Preprocessing Sprint 1 & Sprint 2