data-science-from-scratch

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code for Data Science From Scratch book

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- - __init__.py
  - charts.py
  - clustering.py
  - colon_delimited_stock_prices.txt
  - comma_delimited_stock_prices.csv
  - comma_delimited_stock_prices.txt
  - databases.py
  - decision_trees.py
  - egrep.py
  - getting_data.py
  - gradient_descent.py
  - hypothesis_and_inference.py
  - introduction.py
  - line_count.py
  - linear_algebra.py
  - logistic_regression.py
  - machine_learning.py
  - mapreduce.py
  - most_common_words.py
  - multiple_regression.py
  - naive_bayes.py
  - natural_language_processing.py
  - nearest_neighbors.py
  - network_analysis.py
  - neural_networks.py
  - plot_state_borders.py
  - probability.py
  - recommender_systems.py
  - simple_linear_regression.py
  - states.txt
  - statistics.py
  - stocks.txt
  - tab_delimited_stock_prices.txt
  - visualizing_data.py
  - working_with_data.py
- - __init__.py
  - charts.py
  - clustering.py
  - colon_delimited_stock_prices.txt
  - comma_delimited_stock_prices.csv
  - comma_delimited_stock_prices.txt
  - databases.py
  - decision_trees.py
  - egrep.py
  - getting_data.py
  - gradient_descent.py
  - hypothesis_and_inference.py
  - introduction.py
  - line_count.py
  - linear_algebra.py
  - logistic_regression.py
  - machine_learning.py
  - mapreduce.py
  - most_common_words.py
  - multiple_regression.py
  - naive_bayes.py
  - natural_language_processing.py
  - nearest_neighbors.py
  - network_analysis.py
  - neural_networks.py
  - plot_state_borders.py
  - probability.py
  - README.md
  - recommender_systems.py
  - simple_linear_regression.py
  - states.txt
  - stats.py
  - stocks.txt
  - tab_delimited_stock_prices.txt
  - visualizing_data.py
  - working_with_data.py
- README.md
- README.md
- __init__.py
- clustering.py
- crash_course_in_python.py
- databases.py
- decision_trees.py
- deep_learning.py
- getting_data.py
- gradient_descent.py
- inference.py
- introduction.py
- k_nearest_neighbors.py
- linear_algebra.py
- logistic_regression.py
- machine_learning.py
- mapreduce.py
- multiple_regression.py
- naive_bayes.py
- network_analysis.py
- neural_networks.py
- nlp.py
- nlp_advanced.py
- probability.py
- recommender_systems.py
- simple_linear_regression.py
- statistics.py
- visualization.py
- working_with_data.py
.gitignore
comma_delimited_stock_prices.csv
INSTALL.md
LICENSE
links.md
README.md
requirements.txt
stocks.csv

# Installation Guide

1. Get the code

git clone https://github.com/joelgrus/data-science-from-scratch

Downloads the entire project code from GitHub to your computer.

cd data-science-from-scratch

Moves into the project folder you just downloaded.

2. Python

Easy Recommended

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install -r requirements.txt

Installs the Python libraries listed in requirements.txt (or similar).

python <실행할 파일명>.py # README에서 정확한 실행 파일명을 확인하세요

Runs the Python script (or module).

✅ If it runs without errors and prints output in the terminal, it worked.