Python For Machine Learning Course
What will I learn?
Unleash the power of Python for machine learning with our comprehensive course tailored for tech professionals. Dive into regression algorithms like Random Forests and Decision Trees, master model evaluation metrics such as RMSE and MAE, and explore data preprocessing techniques, including feature scaling and encoding. Level up your skills with feature selection methods, project documentation, and Python libraries like NumPy and Pandas. Optimise models with hyperparameter tuning and ensemble methods. Sign up now to boost your expertise in machine learning.
Apoia's Unique Benefits
Build skills
Enhance your practical skills in the areas listed below
Master regression: Implement Random Forests, Decision Trees, and Linear Regression.
Evaluate models: Use RMSE, MAE, and cross-validation for performance metrics.
Preprocess data: Scale features, handle missing data, and encode categorical variables.
Optimise models: Apply hyperparameter tuning, ensemble methods, and search strategies.
Analyse data: Utilise NumPy, Pandas, Matplotlib, and Seaborn for data insights.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can change the chapters and the workload.
- Choose which chapter to start with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can add
You will be able to generate more chapters like the examples below
This is a free course, focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but it offers practical and relevant knowledge for your professional journey.