What you’ll learn
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Theory and practical implementation of linear regression using sklearn
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Theory and practical implementation of logistic regression using sklearn
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Feature selection using RFECV
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Data transformation with linear and logistic regression.
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Evaluation metrics to analyze the performance of models
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Industry relevance of linear and logistic regression
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Mathematics behind KNN, SVM and Naive Bayes algorithms
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Implementation of KNN, SVM and Naive Bayes using sklearn
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Attribute selection methods- Gini Index and Entropy
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Mathematics behind Decision trees and random forest
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Boosting algorithms:- Adaboost, Gradient Boosting and XgBoost
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Different Algorithms for Clustering
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Different methods to deal with imbalanced data
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Correlation Filtering
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Variance Filtering
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PCA & LDA
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Content and Collaborative based filtering
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Singular Value Decomposition
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Different algorithms used for Time Series forecasting
Who this course is for:
- Anyone who has already started their data science journey and now wanting to master machine learning.
- This course is for machine learning beginners as well as intermediates.
Can I download 2022 Machine Learning A to Z : 5 Machine Learning Projects 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 2022 Machine Learning A to Z : 5 Machine Learning Projects 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.