Machine Learning

Statistics for Machine Learning

4.6 (257 Ratings)


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About this course

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

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

Course Syllabus

Statistics for Machine Learning

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

GL Academy Sample Certificate
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