Machine Learning in R & Predictive Models | 3 Courses in 1

سرفصل های دوره

Supervised & unsupervised machine learning in R, clustering in R, predictive models in R by many labs, understand theory

01 - Introduction

001 Introduction

002 Motivation for the course Why to use Machine Learning for Predictions

003 What is Machine Leraning and its main types

004 Overview of Machine Leraning in R

02 - Software used in this course R-Studio and Introduction to R

001 Introduction to Section 2

002 What is R and RStudio

003 How to install R and RStudio in 2021

004 Lab Install R and RStudio in 2021

005 Introduction to RStudio Interface

006 Lab Get started with R in RStudio

03 - R Crash Course - get started with R-programming in R-Studio

001 Introduction to Section 3

002 Lab Installing Packages and Package Management in R

003 Variables in R and assigning Variables in R

004 Lab Variables in R and assigning Variables in R

005 Overview of data types and data structures in R

006 Lab data types and data structures in R

007 Vectors operations in R

008 Data types and data structures Factors

009 Dataframes overview

010 Functions in R - overview

011 Lab For Loops in R

012 Read Data into R

Files.zip

04 - Fundamentals of predictive modelling with Machine Learning Thoery

001 Overview of prediction process

002 Components of the prediction models and trade-offs in prediction

003 Lab your first prediction model in R

004 Overfitting, sample errors in Machine Learning modelling in R

005 Lab Overfitting, sample errors in Machine Learning modelling in R

006 Study design for predictive modelling with Machine Learning

007 Type of Errors and how to measure them

008 Cross Validation in Machine Learning Models

009 Data Selection for Machine Learning models

Files.zip

05 - Unsupervised Machine Learning and Cluster Analysis in R

001 Unsupervised Learning & Clustering theory

002 Hierarchical Clustering Example

003 Hierarchical Clustering Lab

004 Hierarchical Clustering Merging points

005 Heat Maps theory

006 Heat Maps Lab

007 Example K-Means Clustering in R Lab

008 K-means clustering Application to email marketing

009 Heatmaps to visualize K-Means Results in R Examplery Lab

010 Selecting the number of clusters for unsupervised Clustering methods (K-Means)

011 How to assess a Clustering Tendency of the dataset

012 Assessing the performance of unsupervised learning (clustering) algorithms

Files.zip

06 - Supervised Machine Learning in R Classification in R

001 Overview of functionality of Caret R-package

002 Supervised Machine Learning & KNN Overview

003 Lab Supervised classification with K Nearest Neighbours algorithm in R

005 Theory Confusion Matrix

006 Lab Calculating Classification Accuray for logistic regression model

007 Lab Receiver operating characteristic (ROC) curve and AUC

Files.zip

07 - Supervised Machine Learning in R Linear Regression Analysis

001 Overview of Regression Analysis

002 Graphical Analysis of Regression Models

003 Lab your first linear regression model

004 Correlation in Regression Analysis in R Lab

005 How to know if the model is best fit for your data - An overview

006 Linear Regression Diagnostics

007 AIC and BIC

008 Evaluation of Prediction Model Performance in Supervised Learning Regression

009 Lab Predict with linear regression model & RMSE as in-sample error

010 Prediction model evaluation with data split out-of-sample RMSE

Files.zip

08 - More types of regression models in R

001 Lab Multiple linear regression - model estimation

002 Lab Multiple linear regression - prediction

003 Non-linear Regression Essentials in R Polynomial and Spline Regression Models

004 Lab Polynomial regression in R

005 Lab Log transformation in R

006 Lab Spline regression in R

007 Lab Generalized additive models in R

Files.zip

09 - Working With Non-Parametric and Non-Linear Data (Supervised Machine Learning)

001 Classification and Decision Trees (CART) Theory

002 Lab Decision Trees in R

003 Random Forest Theory

004 Lab Random Forest in R

006 Lab Machine Learning Models' Comparison & Best Model Selection

008 Introduction to Model Selection Essentials in R

009 Final Project Assignment

Files.zip

10 - BONUS

001 BONUS

139,000 تومان

افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: Udemy