TPOTによる分類モデル作成講座 : 【AutoML/Python/Kaggle/SIGNATE】1

Learn to automate machine learning with TPOT! This course dives into the world of Automated Machine Learning (AutoML) using the powerful TPOT library. We'll explore the TPOTClassifier in detail, covering its parameters, attributes, and functions, all while referencing the official documentation. You'll gain hands-on experience building classification models from scratch, without needing extensive coding expertise.

A key highlight is participation in the SIGANTE analysis competition, allowing you to witness firsthand the predictive power of machine learning model automation. This course is perfect for anyone who feels intimidated by machine learning – TPOT is a surprisingly easy-to-use and practical tool.

Here's a breakdown of what you'll learn:

• Section 1: Introduction - Get acquainted with AutoML and TPOT.
• Section 2: Binary Classification [Titanic Dataset] - Apply TPOT to a classic dataset for predicting passenger survival.
• Section 3: Binary Classification [Breast Cancer Dataset] - Build a model to classify breast cancer based on various features.
• Section 4: Multi-class Classification [Iris Dataset] - Learn to classify iris flowers into different species.
• Section 5: Multi-class Classification [Wine Dataset] - Predict the type of wine based on its chemical properties.
• Section 6: Challenge for SIGNATE [Scales Balancing Classification] - Participate in a real-world competition using TPOT to solve a classification problem.
• Section 7: Practice in Kaggle [Abalone Age Classification] - Apply your newly acquired skills to a Kaggle competition focused on classifying abalone age.

This course provides a practical introduction to machine learning automation and empowers you to quickly build and deploy effective classification models.