A Layman’s Guide to Data Science

Topics covered by this book：

• Python basics

• Pandas basics

• Machine learning basics

• useful tools for data scientists

  • shell

  • git & github

  • IDE & virtual environment

  • Markdown

• useful knowledge for data scientists

  • causal inference

  • software engineering principles in python

Python basics

• 0.資料型態：bool, int, float, str
• 1.資料型態：list與tuple
• 2.資料型態：dict與set
• 3.資料型態：進階主題
• 4.流程控制
• 5.function
• 6.進階主題

Pandas basics

• Intro to Pandas
• Pandas常用操作
• Pandas資料分析

Intro to machine learning

• Introduction to machine learning
• Gradient Descent
• Lasso regression, Ridge regression, Elastic-Net
• Hyperparameter Tuning Methods & Cross validation
• Logistic Regression & classification metrics
• Tree-based models

Intro to causal inference

• Introduction to Causal Inference

Environment setup

• Shell & IDE 介紹
• Python安裝與虛擬環境

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