Description
Explore supervised and unsupervised machine learning with Python, from preparing a dataset to assessing a trained model. The course discusses feature engineering, regression, classification and clustering through examples using tools such as Scikit-Learn and Matplotlib. Its algorithm selection includes linear and logistic regression, nearest neighbours, decision trees, random forests, support vector machines and K-Means.
Further topics include hierarchical clustering, principal component analysis and recommendation systems. Neural networks introduce the deep-learning portion through activation functions and training methods. Evaluation metrics, cross-validation and the bias-variance tradeoff help learners compare approaches and interpret results, while visualization and hands-on dataset work connect the mathematical ideas with Python implementation.
Intended audience: Python learners beginning machine learning and deep learning. Aspiring data scientists seeking practical algorithm examples.
What you will learn
- Prepare data and features for machine-learning experiments.
- Implement regression, classification and clustering examples with Python tools.
- Compare model results using evaluation metrics and cross-validation.
- Explain introductory neural-network components and training concepts.
Course specifications
- Publisher
- Udemy
- Instructors
- Oak Academy, OAK Academy Team, Ali̇ CAVDAR
- Language
- English
- Level
- Beginner to Advanced
- Duration
- 18 hours and 14 minutes
- Lecture count
- 116
- Quality
- 1080p
- Edition
- 2026-4
Course topics
View course topics
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Prerequisites
- Basic Python programming knowledge.
- Ability to install and run software on a computer.
- Familiarity with Python plotting tools such as Matplotlib or Seaborn is useful for the exercises.
Pictures
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Introduction video
How to open the files
Keep all parts of the same edition together before extracting the first archive. Open the included course media with a compatible player.
Download resources
Choose one edition and keep its parts together. Alternate providers are available when listed.
2026-4 · 1080p · 1
Direct downloads
2026-4 · 1080p
2026-4 · 1080p · 2
Rapidgator
2026-4 · 1080p
Size
3.5 GB
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