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Mathematics For Machine Learning Course
Sharpen your Business Intelligence skills with our Mathematics for Machine Learning Course. Enter inside data exploration, and become master for the techniques to spot yawa (outliers) and handle data wey dey miss. Learn how to prepare data well, including how to normalize and treat yawa, so your model go dey more accurate. Explore machine learning algorithms wey dey work with time series, like decision trees and ARIMA. Become expert for feature engineering, how to make things work better (optimization techniques), and how to check if your model dey perform well. This course go give you correct, high-quality skills wey you fit use for real life work.
- Master how data dey arranged: Analyze and understand complex data sets well.
- Detect yawa: Spot anything wey no follow (anomalies) so your data go dey more correct and reliable.
- Apply time series models: Use ARIMA and LSTM to predict things with accuracy.
- Make algorithms work better: Use gradient descent to train your model fast fast.
- Engineer features: Create polynomial features to make your model perform better.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Sharpen your Business Intelligence skills with our Mathematics for Machine Learning Course. Enter inside data exploration, and become master for the techniques to spot yawa (outliers) and handle data wey dey miss. Learn how to prepare data well, including how to normalize and treat yawa, so your model go dey more accurate. Explore machine learning algorithms wey dey work with time series, like decision trees and ARIMA. Become expert for feature engineering, how to make things work better (optimization techniques), and how to check if your model dey perform well. This course go give you correct, high-quality skills wey you fit use for real life work.
Elevify advantages
Develop skills
- Master how data dey arranged: Analyze and understand complex data sets well.
- Detect yawa: Spot anything wey no follow (anomalies) so your data go dey more correct and reliable.
- Apply time series models: Use ARIMA and LSTM to predict things with accuracy.
- Make algorithms work better: Use gradient descent to train your model fast fast.
- Engineer features: Create polynomial features to make your model perform better.
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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