Net Course
Ntlafatsa bokgoni ba hao ba mosebetsi wa theknoloji ka Net Course, e etseditsweng ditsebi tsa theknoloji tse labalabelang ho ithuta ka botlalo mokgwa wa ho hlopha dingolwa le tshekatsheko ya datha. Kena ka botebo thupellong ya mohlala, tekolo, le ntlafatso ka boitlhakiso bo sebetsang ba cross-validation, kgetho ya karolo, le hyperparameter tuning. Ntlafatsa bokgoni ba hao ba ho lokisa datha, ho ntsha dikarolo, le mefuta ya ho ithuta ka mochini e kang Naive Bayes le SVM. Fumana lesedi mabapi le pokello ya datha e nepahetseng le ditokomane tse sebetsang, ho netefatsa hore o hlomeletsoe diphephetso tsa sebele tsa lefatshe.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Ntlafatsa bokgoni ba hao ba mosebetsi wa theknoloji ka Net Course, e etseditsweng ditsebi tsa theknoloji tse labalabelang ho ithuta ka botlalo mokgwa wa ho hlopha dingolwa le tshekatsheko ya datha. Kena ka botebo thupellong ya mohlala, tekolo, le ntlafatso ka boitlhakiso bo sebetsang ba cross-validation, kgetho ya karolo, le hyperparameter tuning. Ntlafatsa bokgoni ba hao ba ho lokisa datha, ho ntsha dikarolo, le mefuta ya ho ithuta ka mochini e kang Naive Bayes le SVM. Fumana lesedi mabapi le pokello ya datha e nepahetseng le ditokomane tse sebetsang, ho netefatsa hore o hlomeletsoe diphephetso tsa sebele tsa lefatshe.
Elevify advantages
Develop skills
- Tseba ho lokisa datha: Hlakisa, o lokise, o hloekise datha ya dingolwa ka bokgabane.
- Ntlafatsa mehlala: Sebedisa kgetho ya karolo le hyperparameter tuning.
- Lekola tshebetso: Sebedisa metjha ya nepahalo, botsitso, kgutliso, le F1-score.
- Ntsha dikarolo: Sebedisa mekgwa ya TF-IDF, Word2Vec, le Bag of Words.
- Aha dihlophisi: Hlahisa mefuta ya Naive Bayes, SVM, le neural network.
Suggested summary
Before starting, you can change the chapters and the 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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