Net Course
What will I learn?
Dindi sa bopp ci yoonu tek ci Net Course bi, ñu ko defar ngir jàngalekat yu bëgg a xam xam-xamu tënk mbind ak seetaan njurum-data. Dugal ci njàngal, xamle, ak yëngu-yëngal model ak jëfe ci loxo ci cross-validation, tànn mbir yi, ak hyperparameter tuning. Gënal sa xam-xam ci njurum-data, xeeñu mbir yi, ak model yu Machine Learning niki Naive Bayes ak SVM. Am xam-xam ci wàllu jëf yu yoon ci njurum-data ak mbir yu leer, ngir sa bopp àgg ci jafe-jafe yu dëgg-dëgg.
Apoia's Unique Features
Develop skills
Enhance the development of the practical skills listed below
Xam njurum-data: Tënk, yeesal, ak sëtël mbind mi ci barke.
Rafetal model yi: Defar tànn mbir yi ak hyperparameter tuning.
Seetaan doxal gi: Jëfandiko accuracy, precision, recall, ak F1-score.
Xeeñu mbir yi: Jëfandiko TF-IDF, Word2Vec, ak Bag of Words.
Tabax classificateur yi: Defar Naive Bayes, SVM, ak model yu neural network.
Suggested overview
Workload: between 4 and 360 hours
Before getting started, you can adjust the chapters and the workload.
- Choose which chapter to begin with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can include
You'll be able to create more chapters like the examples below
This is a free course, focused on personal and professional growth. It is not equivalent to a technical, undergraduate, or postgraduate course, but offers practical and relevant knowledge for your professional journey.