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Mathematics For Machine Learning Course
Level up yoh Business Intelligence skills wit wi Mathematics foh Machine Learning Course. Dive inside data exploration, fo master di ways fo spot weti nor correct (outliers) ahn fo manage data weh loss. Learn how fo fix data weh deh prepare am, like normalization ahn treatin outliers, so dat di model kin wuk fine fine. Explore machine learning ways foh time series data, like decision trees ahn ARIMA. Get plenty skill inside feature engineering, di ways fo mek am betta, ahn how fo judge di model. Dis course go give yu real, proper skills weh yu kin use am foh wok weh man kin see.
- Master data structures: Fo check ahn understand data weh big big proper proper.
- Detect outliers: Fo find weti nor correct so dat di data correct fine fine.
- Apply time series models: Fo use ARIMA ahn LSTM fo tell weti go happen in di future correct.
- Optimize algorithms: Fo use gradient descent fo train di model quick.
- Engineer features: Fo mek polynomial features fo mek di model wuk betta.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Level up yoh Business Intelligence skills wit wi Mathematics foh Machine Learning Course. Dive inside data exploration, fo master di ways fo spot weti nor correct (outliers) ahn fo manage data weh loss. Learn how fo fix data weh deh prepare am, like normalization ahn treatin outliers, so dat di model kin wuk fine fine. Explore machine learning ways foh time series data, like decision trees ahn ARIMA. Get plenty skill inside feature engineering, di ways fo mek am betta, ahn how fo judge di model. Dis course go give yu real, proper skills weh yu kin use am foh wok weh man kin see.
Elevify advantages
Develop skills
- Master data structures: Fo check ahn understand data weh big big proper proper.
- Detect outliers: Fo find weti nor correct so dat di data correct fine fine.
- Apply time series models: Fo use ARIMA ahn LSTM fo tell weti go happen in di future correct.
- Optimize algorithms: Fo use gradient descent fo train di model quick.
- Engineer features: Fo mek polynomial features fo mek di model wuk betta.
Suggested summary
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