Corporate Finance Institute – Classification: Fundamentals & Practical Applications

This course provides a comprehensive overview of classification problems, solutions, and interpretations along with walkthroughs of real-world scenarios.

Classification problems are one of the most common scenarios we face in data science. This course will help you understand and apply common algorithms to make predictions and drive decision-making in business.

Whether you’re an aspiring data scientist, studying analytics, or have a focus on business intelligence, this course will give you a comprehensive overview of problems, solutions, and interpretations.

From Logistic Regression to KNN and SVM models, you’ll learn how to implement techniques in Excel and Python and how to create loops to run models in parallel.

Since model evaluation is so important, we’ll dedicate a whole chapter to interpreting model outputs with evaluation metrics and the confusion matrix. With this, you’ll learn about false negatives, and false positives, and consider the impacts these may have on specific business scenarios.

Finally, we’ll give you a brief insight into more advanced classification techniques such as feature importance, SHAP values, and PDP plots.

Whether you’re an aspiring data scientist, studying analytics, or have a focus on business intelligence, this course will serve as your comprehensive introduction to this fascinating subject.

You’ll learn all the key terminology to allow you to talk data science with your teams, benign implementing analysis, and understand how data science can help your business.

What You’ll Learn In Classification: Fundamentals & Practical Applications

• Distinguish between classic techniques including their implicit assumptions and practical use-cases
• Perform simple logistic regression calculations in Excel & RegressIt
• Create basic models in Python using statsmodels and sklearn modules
• Evaluate and interpret the performance of model outputs and parameters

Sale Page: Corporate Finance Institute – Classification – Fundamentals & Practical Applications

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