Practical Machine Learning Learning Path ( Updated 8/2020)
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Difficulty: Intermediate | Genre: eLearning | Language: English | Duration: 6 Modules (15h) | Size: 10.5 GB

Update Courses:
Module 0 - What is Machine Learning - Part Two
Module 2 - Maths for Machine Learning - Part Two
Module 3 - Supervised Learning - Part Two

Description
QA's Practical Machine Learning learning path is an intense deep dive into the world of machine learning. In it you'll learn how to implement different machine learning models, validate their quality, and how to implement them practically. This course is being iterated, and we are looking to flesh out the scope and learning activities within it. As such, if you have any feedback, please don't hesitate to get in touch and let us know what you think we could do to improve this course.

Learning Objectives
This learning path is aimed at fledging data scientists and analysts who wish to gain more in-depth knowledge of Machine Learning.

Intended Audience
GCSE Mathematics or above.
Must be comfortable with analytical and mathematical thinking.
Familiar with basic python programming: variables, control flow, scope, data structures and functions. Must be comfortable with algorithmic thinking.
Familiar with basics of data analysis including databases, descriptive statistics, and typical business use cases.

Prerequisites
After completing Practical Machine Learning, you will know how to:

Explore and prepare data
Develop ML models
Pick ML algorithms for a given task
Understand techniques and metrics used to determine the quality of ML models



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[Only registered and activated users can see links. ]
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[Only registered and activated users can see links. ]
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