Net Course
Open di doa fo how fahn ya tech wok goh be oredi wit di Net Kos. Dis kos ya fo tech people dem weh wan sabi how fo sort text ahn how fo look pan data. Enter inside how fo train model, how fo check if e gud, ahn how fo make am betta wit han-on practice. We goh look pan cross-validation, how fo pick di betta features, ahn how fo tune di parameters dem. Make ya skill dem strong pan how fo clean data, how fo pull out features, ahn how fo yuz machine learning model like Naive Bayes ahn SVM. Get sense pan how fo collect data righteously ahn how fo write things down good, so dat ya ready fo anytin weh goh happen inside di real world.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Open di doa fo how fahn ya tech wok goh be oredi wit di Net Kos. Dis kos ya fo tech people dem weh wan sabi how fo sort text ahn how fo look pan data. Enter inside how fo train model, how fo check if e gud, ahn how fo make am betta wit han-on practice. We goh look pan cross-validation, how fo pick di betta features, ahn how fo tune di parameters dem. Make ya skill dem strong pan how fo clean data, how fo pull out features, ahn how fo yuz machine learning model like Naive Bayes ahn SVM. Get sense pan how fo collect data righteously ahn how fo write things down good, so dat ya ready fo anytin weh goh happen inside di real world.
Elevify advantages
Develop skills
- Master how fo clean data: Cut up di text, put am pan di right level, ahn clean am good good.
- Make model dem betta: Put in how fo pick betta features ahn how fo tune parameters dem.
- Check how e dey perform: Yuz accuracy, precision, recall, ahn F1-score fo check.
- Pull out features: Yuz TF-IDF, Word2Vec, ahn Bag of Words techniques dem.
- Build classifiers: Make Naive Bayes, SVM, ahn neural network model dem.
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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