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Data Science in Python: Classification Modeling

https://www.udemy.com/course/data-science-in-python-classification/

Learn Python for Data Science & Supervised Machine Learning, and build classification models with fun, hands-on projects


What you'll learn


Master the foundations of supervised Machine Learning & classification modeling in Python


Perform exploratory data analysis on model features and targets


Apply feature engineering techniques and split the data into training, test and validation sets


Build and interpret k-nearest neighbors and logistic regression models using scikit-learn


Evaluate model performance using tools like confusion matrices and metrics like accuracy, precision, recall, and F1


Learn techniques for modeling imbalanced data, including threshold tuning, sampling methods, and adjusting class weights


Build, tune, and evaluate decision tree models for classification, including advanced ensemble models like random forests and gradient boosted machines


 



Data Science in Python: Classification Modeling



Data_Science_in_Python_Classification_Modeling.part1.rar - 995.0 MB


Data_Science_in_Python_Classification_Modeling.part2.rar - 995.0 MB


Data_Science_in_Python_Classification_Modeling.part3.rar - 995.0 MB


Data_Science_in_Python_Classification_Modeling.part4.rar - 592.3 MB


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