About this course
This comprehensive course on machine learning explains the basic statistics and programming that are required to work on machine learning problems. The course explains the basics of Python programming and the various packages required for machine learning. It also covers statistical distributions and explains the various types of data you will need to work with. The course then teaches you a type of machine learning called reinforcement learning. Reinforcement learning has applications in game development, smart assistants, recommendation systems, and in industries as varied as finance, oil and gas, etc. The course will explain reinforcement learning using a real world case study to ensure that learning is practical and hands-on.
Machine Learning with Python
- Introduction of Python and Its Libraries
- Data frames with Pandas
- Working on Filtering and Adding Columns
- Filtering and Sorting
- Grouping the Data
- Loops and Functions
- Summarising Data
- Types of Data
- Visualization Libraries
- Basics of Statistics
- Descriptive Statistics
- Measures of Central Tendency
- Measures of Dispersion
- Introduction to Reinforcement Learning
- Framework of Reinforcement Learning
- Q - Learning
- Case Study on Smart Taxi
- Cardio Good Fitness Case Study for Descriptive Statistics
Get Machine Learning with Python 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.
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