Description
Course “Machine learning with Python for everyone. Part 1: Fundamentals of Learning, 2nd Edition.” Machine learning is moving from futuristic AI projects to data analytics on your desk. You need to go beyond nodding during discussions and move on to coding machine learning problems. These videos avoid complex math and focus on showing you how to turn introductory machine learning concepts into concrete code using Python, scikit-learn, and other tools. Our focus is on stories, graphics, and code that will help you better understand machine learning. We minimize pure mathematics. You’ll learn how to load and explore simple data sets. Build, train, and perform basic training evaluation on multiple models. Comparing resource usage of different models in code snippets and scripts. And let’s briefly look at some of the software and mathematical methods that underlie these methods. If you are familiar with the basic concepts of machine learning and want an experienced person to help you turn those concepts into working code, this course is for you. If you have some coding knowledge but want to see how Python can manage and train basic machine learning models, this course is for you. A prerequisite for the course is a basic understanding of Python programming (variables, basic control flow, simple scripts).
What will you learn on the course?
- Construction and application of classification and simple regression models.
- Evaluate training effectiveness by splitting test trains
- Evaluate training performance using relevant metrics for classification and regression.
- Evaluate the resource usage of your learning models
Course Specifications: Machine Learning with Python for Everyone. Part 3. Basic set of tools
- Publisher: Oreily
- Instructor: Mark Fenner
- Level of training: from beginner to advanced
- Duration of training: 5 hours 54 minutes
Course headings
Images from the course “Machine Learning with Python for Everyone, Part 1: Learning Essentials, 2nd Edition”
Example video course
installation instructions
Once extracted, watch using your favorite player.
subtitles: No
Quality: 720p
Download link
Password for file(s): www.downloadly.ir
size
1.5 GB