Python For Machine Learning Course
What will I learn?
Unlock the power of Python for machine learning with our comprehensive course designed for technology professionals. Dive into regression algorithms like Random Forests and Decision Trees, master model evaluation metrics such as RMSE and MAE, and explore data pre-processing techniques including feature scaling and encoding. Enhance your skills with feature selection methods, project documentation, and Python libraries like NumPy and Pandas. Optimize models with hyperparameter tuning and ensemble methods. Join now to elevate your expertise in machine learning.
Apoia's Unique Features
Develop skills
Strengthen the development of the practical skills listed below
Master regression: Implement Random Forests, Decision Trees, and Linear Regression.
Evaluate models: Use RMSE, MAE, and cross-validation for performance metrics.
Pre-process data: Scale features, handle missing data, and encode categorical variables.
Optimize models: Apply hyperparameter tuning, ensemble methods, and search strategies.
Analyze data: Utilize 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 offers practical and relevant knowledge for your professional journey.