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Machine Learning Foundations: Statistics [Repost]
![Machine Learning Foundations: Statistics [Repost]](https://pixhost.icu/avaxhome/1b/1bc1/1bc1c752f0ce4b54a4c11042fad3279e-7219790323930908488.webp)
Machine Learning Foundations: Statistics
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 20m | 200 MB
Instructor: Terezija Semenski
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 20m | 200 MB
Instructor: Terezija Semenski
Machine learning models have revolutionized how we work, across a multitude of industries. But going deeper with ML models and actually understanding how they work will allow you to optimize performance, innovate, troubleshoot issues, and create new and more efficient ML models.
In this course, the fourth part of the Machine Learning Foundations series, Terezija Semenski explains how a deep understanding of statistics can help you excel when it comes to machine learning projects. Terezija shows how statistics plays a large role in machine learning —beyond just crunching numbers—and shows you how to use statistics to gain insights into the data, understand the uncertainties associated with predictions, and make data-driven decisions with confidence.
Learning objectives
- Apply measures of central tendency and variability in a dataset.
- Interpret the purpose of standard error from sample data.
- Analyze the meaning of negative correlation.
- Recognize correlation coefficient values and relationships.
- Identify probability and distributions in statistical analysis.
- Evaluate the purpose of bootstrapping in statistical analysis.
![Machine Learning Foundations: Statistics [Repost]](https://pixhost.icu/avaxhome/1b/1bc1/1bc1c752f0ce4b54a4c11042fad3279e-10704459722276818937_medium.webp)
Machine Learning Foundations: Statistics [Repost]
![Machine Learning Foundations: Statistics [Repost]](https://pixhost.icu/avaxhome/1b/1bc1/1bc1c752f0ce4b54a4c11042fad3279e-10704459722276818937.webp)