Statistics for Machine Learning
5.0 /5
- Offered byGreat Learning
Statistics for Machine Learning at Great Learning Overview
Statistics for Machine Learning
at Great Learning
Duration | 2 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course |
Credential | Certificate |
Statistics for Machine Learning at Great Learning Highlights
Statistics for Machine Learning
at Great Learning
- Earn a certificate of completion
Statistics for Machine Learning at Great Learning Course details
Statistics for Machine Learning
at Great Learning
What are the course deliverables?
- Descriptive Statistics
- Measures of Dispersion Range and IQR
- Central Tendency and 3 Ms
- The Empirical Rule and Chebyshev Rule
- Correlation Analysis
More about this course
- This free online statistics in machine learning course covers the basics of descriptive statistics and data visualizations
- You will be learning about the importance of this functional concept called statistics in this vast domain
- Statistics is a key requirement which acts as a foundation to build up for further concepts down the line, hence it makes it very vital that you understand this
- It also explains the various kinds of statistical distributions and how to apply them to business problems in a simple manner
- An understanding of basic statistics for machine learning concepts provides a strong foundation for further learning in the fields of data analysis, data science, and even some areas of machine learning
Statistics for Machine Learning at Great Learning Curriculum
Statistics for Machine Learning
at Great Learning
Outline - Descriptive statistics
Data and Histogram
Central Tendency and 3 Ms
Measures of Dispersion Range and IQR
Standard Deviation
Coefficient of Variation
The Empirical Rule and Chebyshev Rule
Five Number Summary Boxplot and other plots
Data Visualizations
Correlation Analysis
Summary - Descriptive statistics
Exercise on Descriptive Statistics using Python
Statistics for Machine Learning at Great Learning Faculty details
Statistics for Machine Learning
at Great Learning
Dr. Abhinanda Sarkar
Designation : Faculty Director, Great Learning
Description : Dr. Abhinanda Sarkar is the Academic Director at Great Learning for Data Science and Machine Learning Programs. Dr. Sarkar received his B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He has taught applied mathematics at the Massachusetts Institute of Technology (MIT); been on the research staff at IBM; led Quality, Engineering Development, and Analytics functions at General Electric (GE); served as Associate Dean at the MYRA School of Business; and co-founded OmiX Labs.
Dr. Sarkar’s publications, patents, and technical leadership have been in applying probabilistic models, statistical data analysis, and machine learning to diverse areas such as experimental physics, computer vision, text mining, wireless networks, e-commerce, credit risk, retail finance, engineering reliability, renewable energy, and infectious diseases, His teaching has mostly been on statistical theory, methods, and algorithms; together with application topics such as financial modeling, quality management, and data mining.
Dr. Sarkar is a certified Master Black Belt in Lean Six Sigma and Design for Six Sigma. He has been visiting faculty at Stanford and ISI and continues to teach at the Indian Institute of Management (IIM-Bangalore) and the Indian Institute of Science (IISc). Over the years, he has designed and conducted numerous corporate training sessions for
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Statistics for Machine Learning at Great Learning Students Ratings & Reviews
Statistics for Machine Learning
at Great Learning
5/5
2 Ratings- 4-52
S
SARAT KUMAR PRADHAN
Statistics for Machine Learning
Offered by Great Learning
5
Learning Experience: It was super
Faculty: Nice faculty
Its lectures & agenda
Reviewed on 17 Mar 2023Read More
View 1 Review
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at Great Learning
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