Free download » Free download video courses » Udemy - Machine Learning on R 2021
| view 👀:39 | 🙍 oneddl | redaktor: FreshWap.CC | Rating👍:

Udemy - Machine Learning on R 2021



Udemy - Machine Learning on R 2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 13 lectures (2h) | Size: 706.8 MB
A clear understanding about the machine learning theory, techniques and its application in R Studio platform


What you'll learn:
The program builds a solid foundation by covering the most popular and widely used machine learning technologies and its applications.
Students will have a good working knowledge on Machine Learning on R and can use it for their Educational as well as Business projects and assignments.
Most professionals opting for only this module generally are looking at automation techniques and applications for some daily work they are doing.
The Course Includes Naive Bayes theory, K Nearest Neighbors (KNN) theory and application, Random forest theory and application, Gradient Boosting Theory.
Requirements
Prior knowledge of R programming and Data Science on R is recommended
Description
There are people who are eager to move to Analytics careers but do not have the requisite skill sets. As we move into our 12th year in the Analytics Industry, OrangeTree Global has designed specific courses for freshers and working professionals who are looking at moving to Data Science, Machine Learning and Big Data Careers.
Since 2009, OrangeTree Global has embarked on an ambitious vision of providing affordable and effective Analytics Training and Education across the country.
OrangeTree Global has over a decade's experience in upskilling professionals and helping them move to analytics jobs and careers within and outside India. If you are reading this, we hope to be a part of your journey too.The program builds a solid foundation by covering the most popular and widely used machine learning technologies and its applications, including Naive Bayes theory and application, K Nearest Neighbors (KNN) theory and application, Random forest theory and application, Gradient Boosting Theory and Application and also Support Vector Machine Theory and Application-laying the building blocks for truly expanded analytical abilities.
The program builds a solid foundation by covering the most popular and widely used machine learning technologies and its applications, including Naive Bayes theory and application, K Nearest Neighbors (KNN) theory and application, Random forest theory and application, Gradient Boosting Theory and Application and also Support Vector Machine Theory and Application-laying the building blocks for truly expanded analytical abilities.
Who this course is for
For Students and Business Professionals
Homepage
https://www.udemy.com/course/machine-learning-on-r-2021/


Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me


.html


rapidgator
https://rapidgator.net/file/6249c637f70e0bb2fa905be12d758ada/vpaqa.Machine.Learning.on.R.2021.rar.html

Links are Interchangeable - No Password - Single Extraction

⚠️ Dead Link ?
You may submit a re-upload request using the search feature. All requests are reviewed in accordance with our Content Policy.

Request Re-upload
📌🔥Contract Support Link FileHost🔥📌
✅💰Contract Email: [email protected]

Help Us Grow – Share, Support

We need your support to keep providing high-quality content and services. Here’s how you can help:

  1. Share Our Website on Social Media! 📱
    Spread the word by sharing our website on your social media profiles. The more people who know about us, the better we can serve you with even more premium content!
  2. Get a Premium Filehost Account from Website! 🚀
    Tired of slow download speeds and waiting times? Upgrade to a Premium Filehost Account for faster downloads and priority access. Your purchase helps us maintain the site and continue providing excellent service.

Thank you for your continued support! Together, we can grow and improve the site for everyone. 🌐

Comments (0)

Information
Users of Guests are not allowed to comment this publication.