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Mathematics For Machine Learning Course
Boost your Business Intelligence skills with our Mathematics for Machine Learning Course. Get stuck into data exploration, mastering techniques to spot outliers and deal with missing values. Learn data preprocessing, including normalisation and outlier treatment, to enhance model accuracy. Explore machine learning algorithms for time series data, such as decision trees and ARIMA. Gain expertise in feature engineering, optimisation techniques, and model evaluation. This course gives you practical, high-quality skills for real-world applications.
- Master data structures: Analyse and interpret complex data sets effectively.
- Detect outliers: Identify anomalies to enhance data accuracy and reliability.
- Apply time series models: Use ARIMA and LSTM for precise forecasting.
- Optimise algorithms: Implement gradient descent for efficient model training.
- Engineer features: Create polynomial features to improve model performance.

4 to 360 hours flexible workload
certificate recognised by the NZQA
What will I learn?
Boost your Business Intelligence skills with our Mathematics for Machine Learning Course. Get stuck into data exploration, mastering techniques to spot outliers and deal with missing values. Learn data preprocessing, including normalisation and outlier treatment, to enhance model accuracy. Explore machine learning algorithms for time series data, such as decision trees and ARIMA. Gain expertise in feature engineering, optimisation techniques, and model evaluation. This course gives you practical, high-quality skills for real-world applications.
Elevify advantages
Develop skills
- Master data structures: Analyse and interpret complex data sets effectively.
- Detect outliers: Identify anomalies to enhance data accuracy and reliability.
- Apply time series models: Use ARIMA and LSTM for precise forecasting.
- Optimise algorithms: Implement gradient descent for efficient model training.
- Engineer features: Create polynomial features to improve model performance.
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 workload.What our students say
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