Beginner
98 Lessons
24h
Certificate of Completion
AI-POWERED
This course includes
This course includes
Course Overview
As businesses gather vast amounts of data, machine learning is becoming an increasingly valuable tool for utilizing data to deliver cutting-edge predictive models that support informed decision-making. In this course, you will work on a data science project with a realistic dataset to create actionable insights for a business. You’ll begin by exploring the dataset and cleaning it using pandas. Next, you will learn to build and evaluate logistic regression classification models using scikit-learn. You will...Show More
What You'll Learn
Hands-on experience in data exploration, data processing, data modeling and data visualization using pandas, scikit-learn, and Matplotlib
The ability to evaluate model performance and interpret model predictions
A working knowledge of how predictive models can support business decision-making
An understanding of the mathematical foundations of machine learning models
Course Content
Introduction
Data Exploration and Cleaning
(Challenge) Exploring Remaining Financial Features in Dataset
Project
Introduction to scikit-learn and Model Evaluation
(Challenge) Logistic Regression and Precision-Recall Curve
Project
Details of Logistic Regression and Feature Extraction
(Challenge) Logistic Regression Model and Coefficients
Project
The Bias-Variance Trade-Off
(Challenge) Cross-Validation and Feature Engineering
Project
Decision Trees and Random Forests
13 Lessons
(Challenge) Cross-Validation Grid Search with Random Forest
Project
Gradient Boosting, XGBoost, and SHAP Values
12 Lessons
(Challenge) XGBoost and SHAP Explanation for Case Study Data
Project
Test Set Analysis, Financial Insights, and Delivery to the Client
10 Lessons
(Challenge) Deriving Financial Insights
Project
Appendix
1 Lesson
How You'll Learn
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