What you’ll learn
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Understand and derive the bias-variance decomposition
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Understand the bootstrap method and its application to bagging
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Understand why bagging improves classification and regression performance
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Understand and implement Random Forest
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Understand and implement AdaBoost
Who this course is for:
- Understand the types of models that win machine learning contests (Netflix prize, Kaggle)
- Students studying machine learning
- Professionals who want to apply data science and machine learning to their work
- Entrepreneurs who want to apply data science and machine learning to optimize their business
- Students in computer science who want to learn more about data science and machine learning
- Those who know some basic machine learning models but want to know how today’s most powerful models (Random Forest, AdaBoost, and other ensemble methods) are built.
Can I download Ensemble Machine Learning in Python: Random Forest, AdaBoost course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Ensemble Machine Learning in Python: Random Forest, AdaBoost course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
You can check out for more Udemy coupons @ www.coursecouponclub.com
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Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.