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Mathematics For Machine Learning Course
I-angat ang iyong Business Intelligence skills sa aming Mathematics for Machine Learning Course. Sumisid sa data exploration, pag-master ng mga techniques para ma-detect ang outliers at ma-handle ang missing values. Pag-aralan ang data preprocessing, kasama ang normalization at outlier treatment, para mapahusay ang accuracy ng model. I-explore ang machine learning algorithms para sa time series, tulad ng decision trees at ARIMA. Magkaroon ng expertise sa feature engineering, optimization techniques, at model evaluation. Ang course na ito ay nagbibigay sa iyo ng practical at high-quality skills para sa real-world applications.
- Master ang data structures: Analyze at i-interpret ang complex data sets nang epektibo.
- Mag-detect ng outliers: Tukuyin ang anomalies para mapahusay ang accuracy at reliability ng data.
- Mag-apply ng time series models: Gamitin ang ARIMA at LSTM para sa precise forecasting.
- I-optimize ang algorithms: I-implement ang gradient descent para sa efficient na model training.
- Mag-engineer ng features: Gumawa ng polynomial features para mapabuti ang performance ng model.

flexible workload of 4 to 360h
certificate recognized by the MEC
What will I learn?
I-angat ang iyong Business Intelligence skills sa aming Mathematics for Machine Learning Course. Sumisid sa data exploration, pag-master ng mga techniques para ma-detect ang outliers at ma-handle ang missing values. Pag-aralan ang data preprocessing, kasama ang normalization at outlier treatment, para mapahusay ang accuracy ng model. I-explore ang machine learning algorithms para sa time series, tulad ng decision trees at ARIMA. Magkaroon ng expertise sa feature engineering, optimization techniques, at model evaluation. Ang course na ito ay nagbibigay sa iyo ng practical at high-quality skills para sa real-world applications.
Elevify advantages
Develop skills
- Master ang data structures: Analyze at i-interpret ang complex data sets nang epektibo.
- Mag-detect ng outliers: Tukuyin ang anomalies para mapahusay ang accuracy at reliability ng data.
- Mag-apply ng time series models: Gamitin ang ARIMA at LSTM para sa precise forecasting.
- I-optimize ang algorithms: I-implement ang gradient descent para sa efficient na model training.
- Mag-engineer ng features: Gumawa ng polynomial features para mapabuti ang performance ng model.
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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