Complete Machine Learning & Data Science with R-2019

Bo0mB0oma · February 3, 2019

Complete Machine Learning & Data Science with R-2019

.MP4 | Video: 1280x720, 30 fps® | Audio: AAC, 44100 Hz, 2ch | 5.93 GB

Duration: 12 hours | Genre: eLearning | Language: English

Learn complete Machine learning & Data Science with R covering applied statistics, R programming & data visualization.

Fundamentals of Machine learning

R programming

Applied statistics for machine learning covering important topics like standard error, variance, p value, t-test etc.

Learn complete Machine learning & Data Science with R covering applied statistics, R programming & data visualization.

What you'll learn

Fundamentals of Machine learning

Data science

R programming

Data visualization with base R & libraries like ggplot2, lattice, scatter3d plot & more

Applied statistics for machine learning covering important topics like standard error, variance, p value, t-test etc.

Machine learning models like Neural network, linear regression, logistic regression & more.

Handle advance concepts like dimension reduction & data reduction techniques with PCA & K-Means

Classification & Regression Tree with Random Forest machine learning model

Requirements

Laptop/desktop/phone with internet connection

Desire to learn machine learning & data science

Description

Learn complete Machine learning & Data Science with R covering applied statistics, R programming, data visualization & machine learning models like neural network, CART, Logistic regression & more.

Unlike most machine learning courses out there, the Complete Machine Learning & Data Science with R-2019 is comprehensive. We are not only covering popular machine learning techniques but also additional techniques like ANOVA & CART techniques.

Course is structured into various parts like R programming, data selection & manipulation, applied statistics & data visualization. This will help you with the structure of data science and machine learning.

Here are some highlights of the program:

Visualization with R for machine learning

Applied statistics for machine learning

Machine learning fundamentals

ANOVA Implementation with R

Linear regression with R

Logistic Regression

Dimension Reduction Technique

Tree-based machine learning techniques

KNN Implementation

Naïve Bayes

Neural network machine learning technique