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AI Engineering Course
Tek yuh tech career go a next level wid wi AI Engineering Course, weh design fi technology professional dem weh eager fi master AI. Dive deep inna model evaluation technique dem like Recall, F1-Score, an' cross-validation. Sharpen yuh skill dem inna effective documentation an' explore machine learning algorithm dem fi churn prediction, including decision tree dem an' logistic regression. Get di expertise fi explore data, encode features, an' use strategies fi optimize model dem. Come join wi fi tun data inta actionable insight an' drive innovation inna yuh field.
- Master model evaluation: Mek accuracy betta wid Recall, F1-Score, an' Precision.
- Document effectively: Justify decision dem an' explain result dem wid clarity.
- Predict churn: Use Decision Tree dem, Random Forest dem, an' Logistic Regression.
- Prepare data: Do exploratory analysis an' manage missing data efficiently.
- Optimize models: Implement ensemble method dem an' fine-tune hyperparameter dem.
from 4 to 360h flexible workload
certificate recognized by the MEC
What will I learn?
Tek yuh tech career go a next level wid wi AI Engineering Course, weh design fi technology professional dem weh eager fi master AI. Dive deep inna model evaluation technique dem like Recall, F1-Score, an' cross-validation. Sharpen yuh skill dem inna effective documentation an' explore machine learning algorithm dem fi churn prediction, including decision tree dem an' logistic regression. Get di expertise fi explore data, encode features, an' use strategies fi optimize model dem. Come join wi fi tun data inta actionable insight an' drive innovation inna yuh field.
Elevify advantages
Develop skills
- Master model evaluation: Mek accuracy betta wid Recall, F1-Score, an' Precision.
- Document effectively: Justify decision dem an' explain result dem wid clarity.
- Predict churn: Use Decision Tree dem, Random Forest dem, an' Logistic Regression.
- Prepare data: Do exploratory analysis an' manage missing data efficiently.
- Optimize models: Implement ensemble method dem an' fine-tune hyperparameter dem.
Suggested summary
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