Complete Machine Learning & Data Science with R-2019 (Updated)
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 6.39 GB
Genre: eLearning Video | Duration: 13 hours | Language: English

Learn Machine learning & Data Science with R programming, rstudio, statistics, data wrangling, mining & visualization.
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What you'll learn
Fundamentals of Machine learning
Data science
R programming
Data visualization with base R & libraries like ggDescription2, lattice, scatter3d Description & 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
Real life projects to help you understand industry application
Tips & Tools to create your online portfolio to promote your skills
Tutorial on job searching strategy to find appropriate jobs in machine learning, data science or any other industry.
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
When you sign up for the course, you also:
Get career guidance to help you get into data science
Learn how to build your portfolio
Create over 10 projects to add to your portfolio
Carry out the course at your own pace with lifetime access
Who this course is for:
Students
Working professionals looking to move into data science & machine learning career
Statisticians interested in machine learning





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