Bayesian Machine Learning in Python: A / B Testing, is the name of a set of video tutorials in the field of data science development. This training course is specifically dedicated to A / B testing. A course that helps you do the best you can by analyzing data, marketing and online advertising and the like. By learning the concepts of the A / B test, you will actually prepare yourself for comparing elements in a project. At the end of this course you can present your choices and statistics to others in your work.
There is no additional discussion in this course. In fact, as a student of this course, you will be constantly learning practical concepts and you will never go astray throughout this course. During this course, you will become familiar with different algorithms in the A / B test. On the other hand, you will be well trained in the use of all these algorithms. Finally, by watching this course, you will go to the A / B test to do professionally with the help of Machine Learning from the basics.
Features of the Bayesian Machine Learning course in Python: A / B Testing
- Understand and understand the reason for using A / B test
- Familiarity with the types and varieties of A / B test algorithms
- Understand the types of differences between machine learning data
- Familiarity with the Bayesian method and its use in performing tests
- Duration: 10 hours and 15 minutes
- English language
- Number of chapters: 11
- Number of lessons: 78
- Teacher: Lazy Programmer Inc .
Prerequisites for Bayesian Machine Learning in Python: A / B Testing
- Probability (joint, marginal, conditional distributions, continuous and discrete random variables, PDF, PMF, CDF)
- Python coding with the Numpy stack
After Extract, watch with your favorite Player.
Version 2021/1 has increased by 2 lessons and about 50 minutes compared to 2020/8.