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Machine Learning Course
I-unlock ang power ng machine learning sa aming comprehensive course na dinisenyo para sa mga technology professionals. Sumisid sa data collection at exploration gamit ang Pandas at NumPy, i-master ang mga dataset splitting strategies, at i-evaluate ang models nang may precision. Pag-aralan ang essential preprocessing techniques, i-explore ang advanced model selection, at magkaroon ng insights sa regression models tulad ng Decision Trees at Random Forests. Paghusayin ang iyong skills sa practical at high-quality content na sisiguraduhin na handa kang harapin ang real-world challenges. Sumali na at i-transform ang iyong career!
- I-master ang data handling: Mag-load, mag-inspect, at pumili ng datasets gamit ang Pandas at NumPy.
- I-implement ang dataset splitting: Mag-apply ng cross-validation at stratified sampling techniques.
- I-evaluate ang model performance: Unawain ang MAE, MSE, at R-squared metrics.
- I-preprocess ang data nang epektibo: I-handle ang missing values at i-encode ang categorical variables.
- I-optimize ang models: I-tune ang hyperparameters at gumamit ng ensemble methods.
flexible workload of 4 to 360h
certificate recognized by the MEC
What will I learn?
I-unlock ang power ng machine learning sa aming comprehensive course na dinisenyo para sa mga technology professionals. Sumisid sa data collection at exploration gamit ang Pandas at NumPy, i-master ang mga dataset splitting strategies, at i-evaluate ang models nang may precision. Pag-aralan ang essential preprocessing techniques, i-explore ang advanced model selection, at magkaroon ng insights sa regression models tulad ng Decision Trees at Random Forests. Paghusayin ang iyong skills sa practical at high-quality content na sisiguraduhin na handa kang harapin ang real-world challenges. Sumali na at i-transform ang iyong career!
Elevify advantages
Develop skills
- I-master ang data handling: Mag-load, mag-inspect, at pumili ng datasets gamit ang Pandas at NumPy.
- I-implement ang dataset splitting: Mag-apply ng cross-validation at stratified sampling techniques.
- I-evaluate ang model performance: Unawain ang MAE, MSE, at R-squared metrics.
- I-preprocess ang data nang epektibo: I-handle ang missing values at i-encode ang categorical variables.
- I-optimize ang models: I-tune ang hyperparameters at gumamit ng ensemble methods.
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 workloadWhat our students say
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