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 VodafoneZiggo
599,407 already enrolled
4.7
(17,807 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
- Predictive Modeling
- Regression Analysis
- Machine Learning
- Supervised Learning
- Feature Engineering
- Classification And Regression Tree (CART)
- Python Programming
- Applied Machine Learning
- Statistical Analysis
- Scikit Learn (Machine Learning Library)
- Machine Learning Algorithms
- Dimensionality Reduction
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
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Learner reviews
4.7
17,807 reviews
- 5 stars
75.89%
- 4 stars
18.64%
- 3 stars
3.44%
- 2 stars
0.99%
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1.01%
Showing 3 of 17807
RV
5
Reviewed on Jan 14, 2025
HR
5
Reviewed on Sep 5, 2021
This course just gave me substantial and valuable knowledge on ml algorithms and how to apply it using python. As a result, it was a benefiting journey for me. Thanks a lot for such a course.
AJ
5
Reviewed on Jul 8, 2019
This was a very informative course. The videos provided a good background on the concepts and I found the labs especially helpful for learning to implement Python code for each technique covered.
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