Python For Machine Learning Course
Open your eye to the power of Python for machine learning with our well-organised training programme wey be dey design for technology people. Enter inside regression algorithms like Random Forests and Decision Trees, become master for model evaluation metrics like RMSE and MAE, and learn data preprocessing techniques including feature scaling and encoding. Sharpen your skills with feature selection methods, project documentation, and Python libraries like NumPy and Pandas. Make your models better with hyperparameter tuning and ensemble methods. Join now so you go fit grow your knowledge for inside machine learning.
flexible workload of 4 to 360h
certificate recognized by the MEC
What will I learn?
Open your eye to the power of Python for machine learning with our well-organised training programme wey be dey design for technology people. Enter inside regression algorithms like Random Forests and Decision Trees, become master for model evaluation metrics like RMSE and MAE, and learn data preprocessing techniques including feature scaling and encoding. Sharpen your skills with feature selection methods, project documentation, and Python libraries like NumPy and Pandas. Make your models better with hyperparameter tuning and ensemble methods. Join now so you go fit grow your knowledge for inside machine learning.
Elevify advantages
Develop skills
- Become a master for regression: Use Random Forests, Decision Trees, and Linear Regression well-well.
- Check models well: Use RMSE, MAE, and cross-validation to know if the model dey perform well.
- Prepare data well: Scale features, manage data wey dey miss, and encode categorical variables.
- Make models perform better: Apply hyperparameter tuning, ensemble methods, and search strategies.
- Look inside data well-well: Use NumPy, Pandas, Matplotlib, and Seaborn to understand wetin the data dey talk.
Suggested summary
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 workloadWhat our students say
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