【作者(必填)】jason brownlee

【文题(必填)】Deep Learning for Time Series

【年份(必填)】2016

【全文链接或数据库名称(选填)】1. Lessons
Here is an overview of the 16 step-by-step lessons you will complete:
•Lesson 1: Python Ecosystem for Machine Learning.
•Lesson 2: Python and SciPy Crash Course.
•Lesson 3: Load Datasets from CSV.
•Lesson 4: Understand Data With Descriptive Statistics.
•Lesson 5: Understand Data With Visualization.
•Lesson 6: Pre-Process Data.
•Lesson 7: Feature Selection.
•Lesson 8: Resampling Methods.
•Lesson 9: Algorithm Evaluation Metrics.
•Lesson 10: Spot-Check Classification Algorithms.
•Lesson 11: Spot-Check Regression Algorithms.
•Lesson 12: Model Selection.
•Lesson 13: Pipelines.
•Lesson 14: Ensemble Methods.
•Lesson 16: Model Finalization.


Each lesson was designed to be completed in about 30 minutes by the average developer.
2. Projects
Here is an overview of the 3 end-to-end projects you will complete:
•Project 1: Hello World Project (Iris flowers dataset).
•Project 2: Regression (Boston House Price dataset).
•Project 3: Binary Classification (Sonar dataset).


Each project was designed to be completed in about 60 minutes by the average developer