good course , some part is typical more statistical part shown, even i have good understanding of ML , so new learner will find little typical. rest tutor voice and language is understandable.
Machine Learning with Python
Machine Learning with Python
This course is part of multiple programs.
Instructors: Joseph Santarcangelo
Access provided by Iran University of Science and Technology
615,953 already enrolled
4.7
(17,941 reviews)
Intermediate level
Recommended experience
Flexible schedule
1 hour to complete
Learn at your own pace
94%
Most learners liked this course
What you'll learn
Explain key concepts, tools, and roles involved in machine learning, including supervised and unsupervised learning techniques.
Apply core machine learning algorithms such as regression, classification, clustering, and dimensionality reduction using Python and scikit-learn.
Evaluate model performance using appropriate metrics, validation strategies, and optimization techniques.
Build and assess end-to-end machine learning solutions on real-world datasets through hands-on labs, projects, and practical evaluations.
Skills you'll gain
- Unsupervised Learning
- Applied Machine Learning
- Python Programming
- Regression Analysis
- Dimensionality Reduction
- Feature Engineering
- Machine Learning Algorithms
- Supervised Learning
- Scikit Learn (Machine Learning Library)
- Predictive Modeling
- Classification And Regression Tree (CART)
- Machine Learning
- Statistical Analysis
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
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Learner reviews
4.7
17,941 reviews
- 5 stars
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Showing 3 of 17941
RV
5
Reviewed on Jan 14, 2025
FO
5
Reviewed on Oct 8, 2020
I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.
JT
5
Reviewed on Apr 17, 2020
This course was a great taster for machine learning techniques. My only recommendation would be to add more explanation on tuning techniques for models and cover more of the supporting mathematics.
