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Introduction to Machine Learning For Data Science Course
Fungua uwezo wa data na kozi yetu ya "Utangulizi wa Machine Learning kwa Data Science," iliyoundwa mahususi kwa wataalamu wa Business Intelligence (Ujasusi wa Biashara). Ingia ndani kabisa ya mada muhimu kama vile uandaaji wa data (data preprocessing), uhandisi wa vipengele (feature engineering), na mafunzo ya modeli (model training). Jifunze kanuni (algorithms) za hali ya juu kama vile Random Forests na Gradient Boosting kwa utabiri wa mauzo. Jifunze kuboresha modeli kupitia urekebishaji wa vigezo (hyperparameter tuning) na uzitathmini kwa kutumia vipimo kama vile MAE na RMSE. Imarisha ujuzi wako wa BI na maarifa ya hali ya juu, yenye manufaa ambayo yanaendesha mafanikio ya biashara.
- Bobea katika usafishaji wa data: Hakikisha usahihi kwa kuondoa hitilafu na makosa.
- Tengeneza uhandisi wa vipengele: Unda vipengele vyenye athari kwa utendaji bora wa modeli.
- Boresha modeli: Ongeza usahihi kwa urekebishaji wa vigezo na ulinganisho wa kanuni.
- Taswira maarifa ya data: Tumia zana za taswira kufunua maarifa yanayoweza kutekelezwa.
- Tathmini modeli: Pima mafanikio kwa kutumia vipimo kama vile MAE na RMSE.
from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Fungua uwezo wa data na kozi yetu ya "Utangulizi wa Machine Learning kwa Data Science," iliyoundwa mahususi kwa wataalamu wa Business Intelligence (Ujasusi wa Biashara). Ingia ndani kabisa ya mada muhimu kama vile uandaaji wa data (data preprocessing), uhandisi wa vipengele (feature engineering), na mafunzo ya modeli (model training). Jifunze kanuni (algorithms) za hali ya juu kama vile Random Forests na Gradient Boosting kwa utabiri wa mauzo. Jifunze kuboresha modeli kupitia urekebishaji wa vigezo (hyperparameter tuning) na uzitathmini kwa kutumia vipimo kama vile MAE na RMSE. Imarisha ujuzi wako wa BI na maarifa ya hali ya juu, yenye manufaa ambayo yanaendesha mafanikio ya biashara.
Elevify advantages
Develop skills
- Bobea katika usafishaji wa data: Hakikisha usahihi kwa kuondoa hitilafu na makosa.
- Tengeneza uhandisi wa vipengele: Unda vipengele vyenye athari kwa utendaji bora wa modeli.
- Boresha modeli: Ongeza usahihi kwa urekebishaji wa vigezo na ulinganisho wa kanuni.
- Taswira maarifa ya data: Tumia zana za taswira kufunua maarifa yanayoweza kutekelezwa.
- Tathmini modeli: Pima mafanikio kwa kutumia vipimo kama vile MAE na RMSE.
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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