What you’ll learn
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Understand and implement K-Nearest Neighbors in Python
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Understand the limitations of KNN
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User KNN to solve several binary and multiclass classification problems
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Understand and implement Naive Bayes and General Bayes Classifiers in Python
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Understand the limitations of Bayes Classifiers
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Understand and implement a Decision Tree in Python
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Understand and implement the Perceptron in Python
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Understand the limitations of the Perceptron
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Understand hyperparameters and how to apply cross-validation
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Understand the concepts of feature extraction and feature selection
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Understand the pros and cons between classic machine learning methods and deep learning
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Use Sci-Kit Learn
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Implement a machine learning web service
Who this course is for:
- Students and professionals who want to apply machine learning techniques to their datasets
- Students and professionals who want to apply machine learning techniques to real world problems
- Anyone who wants to learn classic data science and machine learning algorithms
- Anyone looking for an introduction to artificial intelligence (AI)
Can I download Data Science: Supervised Machine Learning in Python 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 Data Science: Supervised Machine Learning in Python 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.