Explore practical coding of basic machine learning models using Python. Gain insights into algorithms like linear regression, logistic regression, SVM, KNN, and decision trees.

Machine Learning with Python A Practical Beginners’ Guide by Oliver Theobald-01.png

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This course teaches you how to code basic machine learning models. The content is designed for beginners with general knowledge of machine learning, including common algorithms such as linear regression, logistic regression, SVM, KNN, decision trees, and more. If you need a refresher, we have summarized key concepts from machine learning, and there are overviews of specific algorithms dispersed throughout the course.

A Practical Guide to Machine Learning with Python

# Congratulations

Congratulations on completing the course! You are now equipped with some important skills that will help you achieve your goals. Give yourself a round of applause! 

Congratulations! You have covered the basics of machine learning using Python. Give yourself a pat on your back. 

What's Next?

Introduction to Course

Introduction to Machine Learning

Exploratory Data Analysis

Data Scrubbing

Pre-Model Algorithms

Customer Segmentation with K-Means Clustering

Split Validation

Model Design

Linear Regression

Logistic Regression

Support Vector Machines

K-Nearest Neighbors

Tree-Based Methods

Cardiovascular Disease Risk Prediction with Random Forest

Conclusion

Appendix

What's Next?

Congratulations