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
Access provided by Tahakom Group
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Gain insight into a topic and learn the fundamentals.
3,267 reviews
8 hours to complete
Flexible schedule
Learn at your own pace
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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
- Supervised Learning
- Predictive Modeling
- Machine Learning Algorithms
- Machine Learning
- Data Preprocessing
- Model Evaluation
- Feature Engineering
- Random Forest Algorithm
- Model Training
- Predictive Analytics
- Machine Learning Software
- Regression Analysis
- Applied Machine Learning
- Machine Learning Methods
- Classification And Regression Tree (CART)
Tools you'll learn
Details to know
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Assessments
5 assignments
Taught in English
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This course is available as part of
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There are 4 modules in this course
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Showing 3 of 3267
HP
Reviewed on Jan 15, 2017
It was like opening up a door to a whole new world. I have discovered new tools that I will thoroughly enjoy to use for the exploration of data and for predictions. Thanks Team Coursera !
HP
Reviewed on Mar 12, 2021
This is a well thought about course which focuses on familiarizing the learner on the concepts of Machine Learning and develops a love in the learner towards predictive modeling. Thank you
AM
Reviewed on Aug 30, 2017
Highly recommend this course. It makes you read a lot, do lot's of practical exercises. The final project is a must do. After finishing this course you can start playing with kaggle data sets.
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