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Overview
Linear & Logistic Regression, Decision Trees, XGBoost, SVM & other ML models in R programming language - R studio What you'll learn: Learn how to solve real life problem using the Machine learning techniques Machine Learning models such as Linear Regression, Logistic Regression, KNN etc. Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM etc. Understanding of basics of statistics and concepts of Machine Learning How to do basic statistical operations and run ML models in RIndepth...
Syllabus
- Welcome to the course
- Setting up R Studio and R crash course
- Basics of Statistics
- Intorduction to Machine Learning
- Data Preprocessing for Regression Analysis
- Linear Regression Model
- Regression models other than OLS
- Introduction to the classification Models
- Logistic Regression
- Linear Discriminant Analysis
- K-Nearest Neighbors
- Comparing results from 3 models
- Simple Decision Trees
- Simple Classification Tree
- Ensemble technique 1 - Bagging
- Ensemble technique 2 - Random Forest
- Ensemble technique 3 - GBM, AdaBoost and XGBoost
- Support Vector Machines
- Support Vector Classifier
- Support Vector Machines
- Creating Support Vector Machine Model in R
- Congratulations & about your certificate
Instructor
Start-Tech Academy
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