Python For Machine Learning Course
Unlock the potential of Python for machine learning with our detailed course, specifically designed for technology professionals in Pakistan. Delve into regression algorithms like Random Forests and Decision Trees, gain expertise in model evaluation metrics such as RMSE and MAE, and explore essential data preprocessing techniques including feature scaling and encoding. Sharpen your skills with feature selection methods, project documentation best practices, and widely-used Python libraries such as NumPy and Pandas. Fine-tune your models with hyperparameter tuning and powerful ensemble methods. Enrol now to boost your machine learning proficiency.
flexible workload from 4 to 360h
certificate recognized by the MEC
What will I learn?
Unlock the potential of Python for machine learning with our detailed course, specifically designed for technology professionals in Pakistan. Delve into regression algorithms like Random Forests and Decision Trees, gain expertise in model evaluation metrics such as RMSE and MAE, and explore essential data preprocessing techniques including feature scaling and encoding. Sharpen your skills with feature selection methods, project documentation best practices, and widely-used Python libraries such as NumPy and Pandas. Fine-tune your models with hyperparameter tuning and powerful ensemble methods. Enrol now to boost your machine learning proficiency.
Elevify advantages
Develop skills
- Master regression techniques: Implement Random Forests, Decision Trees, and Linear Regression.
- Evaluate model performance: Use RMSE, MAE, and cross-validation to assess and improve models.
- Preprocess data effectively: Scale features, manage missing data, and encode categorical variables appropriately.
- Optimize models expertly: Apply hyperparameter tuning, ensemble methods, and efficient search strategies.
- Analyse data thoroughly: Utilize NumPy, Pandas, Matplotlib, and Seaborn to extract valuable data insights.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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