What you’ll learn
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Describe the input and output of a classification model
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Prepare data with feature engineering techniques
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Tackle both binary and multiclass classification problems
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Implement Support Vector Machines, Naive Bayes, Decision Tree, Random Forest, K-Nearest Neighbors, Neural Networks, logistic regression models on Python
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Use a variety of performance metrics such as confusion matrix, accuracy, precision, recall, ROC curve and AUC score.
Who this course is for:
- Research scholars and college students
- Industry professionals and aspiring data scientists
- Beginners starting out to the field of Machine Learning
Can I download Supervised Machine Learning in Python: Classification Models 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 Supervised Machine Learning in Python: Classification Models 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?
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