Data Science - Supervised Machine Learning in Python
Master Supervised Machine Learning Techniques in Python with KNN, Naive Bayes, and Decision Trees
Explore the world of supervised machine learning using Python by working with real datasets and popular algorithms like KNN, Naive Bayes, and Decision Trees. Gain hands-on experience building and optimizing models, and learn how to deploy them for real-world use.
Packt | Apr 2026 | 231 min
What You Will Learn
You will start by learning the theory behind each algorithm and then immediately apply your knowledge through hands-on coding exercises. By working with real datasets and practical examples, you will develop the confidence to build, evaluate, and deploy your own machine learning models.
Key Features
- Build and tune machine learning models with KNN, Naive Bayes, and Decision Trees
- Practice with real datasets to develop practical data science skills
- Deploy machine learning models as web services for real-world applications
Target Audience
Designed for aspiring data scientists, machine learning engineers, and developers familiar with Python, this course is perfect if you want to deepen your understanding of supervised learning. If you are looking to transition into data science or strengthen your practical skills, you will find this course valuable.
