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
What You'll Learn
Hands-on experience in data exploration, data processing, data modeling and data visualization using pandas, scikit-learn, and Matplotlib
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Course Content
Introduction
Data Exploration and Cleaning
Introduction to scikit-learn and Model Evaluation
Details of Logistic Regression and Feature Extraction
The Bias-Variance Trade-Off
Decision Trees and Random Forests
13 Lessons
Gradient Boosting, XGBoost, and SHAP Values
12 Lessons
Test Set Analysis, Financial Insights, and Delivery to the Client
10 Lessons
Appendix
1 Lesson
Course Author
Trusted by 1.4 million developers working at companies
Anthony Walker
@_webarchitect_
Evan Dunbar
ML Engineer
Carlos Matias La Borde
Software Developer
Souvik Kundu
Front-end Developer
Vinay Krishnaiah
Software Developer
Eric Downs
Musician/Entrepeneur
Kenan Eyvazov
DevOps Engineer
Souvik Kundu
Front-end Developer
Eric Downs
Musician/Entrepeneur
Anthony Walker
@_webarchitect_
Evan Dunbar
ML Engineer
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