Learn Data Science With R Part 4 of 10
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Learn Data Science With R Part 4 of 10

Machine Learning
New
0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
6 students enrolled
Created by Ram Reddy
Last updated 8/2017
English
Price: $200
30-Day Money-Back Guarantee
Includes:
  • 6 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Machine Learning
View Curriculum
Requirements
  • Complete Learn Data Science With R Part 1/2/3 of 10
Description

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.


Who is the target audience?
  • Data Science basic understanding with R
Compare to Other Data Science Courses
Curriculum For This Course
5 Lectures
06:05:40
+
Machine Learning
5 Lectures 06:05:40

Data Science Tutorial Part 25 Machine Learning Linear Regression Part 1
02:58:02

Data Science Tutorial Part 26 Machine Learning Linear Regression Part 2
01:02:52

Data Science Tutorial Part 27 Machine Learning Linear Regression Part 3
52:47

Power BI Introduction
20:03
About the Instructor
Ram Reddy
4.4 Average rating
58 Reviews
5,097 Students
9 Courses
Data Scientist

Data scientist and founder of RRITEC, a company dedicated to helping scientists better understand and visualize their data. Ram Has hands-on exposure to a wide variety of datasets has informed him of the many problems scientists face when trying to visualize their data.

Some of the main roles are 

Develop and improve robust predictive algorithms that are the core of the product 

Combine an understanding of business goals with data analysis and machine learning 

Investigate new data sources; acquire, analyze, clean and structure data 

Utilize state of the art machine learning techniques to improve and expand existing models