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Python For Machine Learning Course
Unlock di power of Python for machine learning wit dis complete course wey dem design for tech professionals like you. Dig deep inside regression algorithms like Random Forests and Decision Trees, master di model evaluation metrics like RMSE and MAE, and check out data preprocessing techniques wey include feature scaling and encoding. Make your skills betta wit feature selection methods, project documentation, and Python libraries like NumPy and Pandas. Fine-tune your models wit hyperparameter tuning and ensemble methods. Join us now so you go sabi machine learning well well.
- Master regression: Implement Random Forests, Decision Trees, and Linear Regression (Understand how to use Random Forests, Decision Trees, and Linear Regression well well).
- Evaluate models: Use RMSE, MAE, and cross-validation for performance metrics (Learn how to use RMSE, MAE, and cross-validation to check how your model dey perform).
- Preprocess data: Scale features, handle missing data, and encode categorical variables (Learn how to prepare your data by scaling features, handling missing data, and encoding different types of data).
- Optimize models: Apply hyperparameter tuning, ensemble methods, and search strategies (Learn how to make your model betta by fine-tuning hyperparameters, using ensemble methods, and trying different search strategies).
- Analyze data: Utilize NumPy, Pandas, Matplotlib, and Seaborn for data insights (Learn how to use NumPy, Pandas, Matplotlib, and Seaborn to understand your data well).
flexible workload from 4 to 360h
certificate recognized by MEC
What will I learn?
Unlock di power of Python for machine learning wit dis complete course wey dem design for tech professionals like you. Dig deep inside regression algorithms like Random Forests and Decision Trees, master di model evaluation metrics like RMSE and MAE, and check out data preprocessing techniques wey include feature scaling and encoding. Make your skills betta wit feature selection methods, project documentation, and Python libraries like NumPy and Pandas. Fine-tune your models wit hyperparameter tuning and ensemble methods. Join us now so you go sabi machine learning well well.
Elevify advantages
Develop skills
- Master regression: Implement Random Forests, Decision Trees, and Linear Regression (Understand how to use Random Forests, Decision Trees, and Linear Regression well well).
- Evaluate models: Use RMSE, MAE, and cross-validation for performance metrics (Learn how to use RMSE, MAE, and cross-validation to check how your model dey perform).
- Preprocess data: Scale features, handle missing data, and encode categorical variables (Learn how to prepare your data by scaling features, handling missing data, and encoding different types of data).
- Optimize models: Apply hyperparameter tuning, ensemble methods, and search strategies (Learn how to make your model betta by fine-tuning hyperparameters, using ensemble methods, and trying different search strategies).
- Analyze data: Utilize NumPy, Pandas, Matplotlib, and Seaborn for data insights (Learn how to use NumPy, Pandas, Matplotlib, and Seaborn to understand your data well).
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