Machine Learning

# Statistics for Machine Learning

4.6 (257 Ratings)

Beginner

Skill level

Free

Course cost

An understanding of basic statistical concepts provides a strong foundation for further learning in the fields of data analysis, data science and even some areas of machine learning. This course covers the basics of descriptive statistics, and teaches you more advanced concepts such as hypothesis testing and Bayes’ theorem. The course also explains in a simple manner the various kinds of statistical distributions and how to apply them to business problems.

#### Skills covered

• Basic Statistics
• Hypothesis Testing
• Bayes' Theorem
• Binomial Distribution
• Poisson Distribution
• Normal Distribution

## Course Syllabus

#### Statistics for Machine Learning

• Introduction to Statistics
• Why statistics is so important
• Big Data
• The four pillars of Business Analytics in details
• Data Vs information
• Frequency distribution and plots
• Central tendency_Mean_Median and Mode
• Measures of Dispersion and Range_Standard Deviation
• The five number summary and boxplots
• Probability concepts Uncertainty and Volatility
• Example for Rules Addition Multiplication Marginal
• Bayes Theorem
• Probability Distributions
• Binomial Distribution using Python
• Poisson Distribution
• Poisson Distribution using Python
• Normal Distribution and its exercises in Excel
• Normal Distribution using Python
• Hypothesis Testing

## Course Certificate

Get Statistics for Machine Learning course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

## Discussion on Statistics for Machine Learning

When I joined this course there were Hypothesis testing but now it’s not showing. 