One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.
Practical Machine Learning
Practical Machine Learning
This course is part of multiple programs.
Instructors: Jeff Leek, PhD
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3,268 reviews
8 hours to complete
Flexible schedule
Learn at your own pace
89%
Most learners liked this course
What you'll learn
Use the basic components of building and applying prediction functions
Understand concepts such as training and tests sets, overfitting, and error rates
Describe machine learning methods such as regression or classification trees
Explain the complete process of building prediction functions
Skills you'll gain
- Model Training
- Model Evaluation
- Feature Engineering
- Regression Analysis
- Random Forest Algorithm
- Machine Learning
- Predictive Analytics
- Supervised Learning
- Classification And Regression Tree (CART)
- Machine Learning Algorithms
- Machine Learning Methods
- Applied Machine Learning
- Data Preprocessing
- Predictive Modeling
- Machine Learning Software
Tools you'll learn
Details to know
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Assessments
5 assignments
Taught in English
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Showing 3 of 3268
NK
Reviewed on Feb 18, 2016
Some of the terms used here vary from the terms used in the industry. For example recall, precision etc. Overall this is a very good course with provides basics of machine learning.
UY
Reviewed on Nov 16, 2016
Great course. Only missing piece is the working information / maths behind the models. But as the name suggests it teaches practical approach towards machine learning.
JF
Reviewed on Feb 13, 2019
Very good course. Clear explanations and examples give a good overview of the foundations of Machine Learning. After this course the student can build Machine Learning models.
