Description
Course Machine Learning with Python for Everyone Part 2: Measuring Models. In this course, you will get to know the basic criteria used to evaluate machine learning systems and specific criteria used in classification and regression. You will also learn techniques to accurately measure machine learning performance from your data. This course allows you to gain a solid knowledge of numerical and graphical techniques to understand how learning systems work. This course is suitable for anyone who needs to improve their basic understanding of machine learning concepts and become familiar with ML code. You may be a data scientist, a data analyst looking to add machine learning techniques to your classic statistical training, this course will definitely help you achieve that goal.
To participate in this course, students must have a basic understanding of programming in Python (variables, flow control, simple scripts). They should also be familiar with machine learning vocabulary (dataset, training set, test set, model), but no high level of knowledge is required. Also, in order to run the codes of this course, students must have a version of Python installed on their system that is compatible with the scikit-learn and matplotlib libraries.
What you will learn in the course
- Distinguish underfitting and overfitting graphically.
- Use resampling techniques like cross-validation to get the most information from your data.
- Graphical evaluation of system learning performance
- Construction and evaluation of confusion matrices and ROC curves
- Apply classification criteria to multi-class learning problems
Course specifications Machine Learning with Python for Everyone Part 2: Measuring Models
- Publisher: Oreilly
- teacher: Mark Fenner
- Training level: beginner to advanced
- Training duration: 5 hours 34 minutes
Course headings
Course images
Sample video of the course
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
1.6 GB
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