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‎INSTALL.md‎

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# How to Install Python
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If you don't already have Python, I strongly recommend you install the Anaconda version,
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which includes many of the libraries needed for data science:
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which includes many of the libraries needed for data science. Get the Python 3 version, not the Python 2 version.
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https://www.anaconda.com/distribution/#download-section
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‎README.md‎

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Data Science from Scratch
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=========================
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Here's all the code and examples from the second edition of my book _Data Science from Scratch_.
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Here's all the code and examples from the second edition of my book _Data Science from Scratch_. They require at least Python 3.6.
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(If you're looking for the code and examples from the first edition, that's in the `first-edition` folder.)
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If you want to use the code, you should be able to clone the repo and just do things like
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```
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In [1]: from scratch.linear_algebra import dot
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In [2]: dot([1, 2, 3], [4, 5, 6])
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Out[2]: 32
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```
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and so on and so forth.
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## Table of Contents
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1. Introduction
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2. A Crash Course in Python
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3. [Visualizing Data](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/visualizing_data.py)
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4. [Linear Algebra](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/linear_algebra.py)
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5. [Statistics](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/statistics.py)
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6. [Probability](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/probability.py)
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7. [Hypothesis and Inference](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/hypothesis_and_inference.py)
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8. [Gradient Descent](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/gradient_descent.py)
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9. [Getting Data](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/getting_data.py)
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10. [Working With Data](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/working_with_data.py)
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11. [Machine Learning](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/machine_learning.py)
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12. [k-Nearest Neighbors](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/nearest_neighbors.py)
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13. [Naive Bayes](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/naive_bayes.py)
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14. [Simple Linear Regression](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/simple_linear_regression.py)
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15. [Multiple Regression](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/multiple_regression.py)
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16. [Logistic Regression](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/logistic_regression.py)
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17. [Decision Trees](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/decision_trees.py)
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18. [Neural Networks](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/neural_networks.py)
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3. [Visualizing Data](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/visualizing_data.py)
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4. [Linear Algebra](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/linear_algebra.py)
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5. [Statistics](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/statistics.py)
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6. [Probability](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/probability.py)
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7. [Hypothesis and Inference](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/hypothesis_and_inference.py)
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8. [Gradient Descent](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/gradient_descent.py)
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9. [Getting Data](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/getting_data.py)
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10. [Working With Data](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/working_with_data.py)
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11. [Machine Learning](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/machine_learning.py)
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12. [k-Nearest Neighbors](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/nearest_neighbors.py)
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13. [Naive Bayes](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/naive_bayes.py)
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14. [Simple Linear Regression](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/simple_linear_regression.py)
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15. [Multiple Regression](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/multiple_regression.py)
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16. [Logistic Regression](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/logistic_regression.py)
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17. [Decision Trees](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/decision_trees.py)
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18. [Neural Networks](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/neural_networks.py)
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19. [Deep Learning]
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20. [Clustering](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/clustering.py)
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21. [Natural Language Processing](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/natural_language_processing.py)
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22. [Network Analysis](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/network_analysis.py)
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23. [Recommender Systems](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/recommender_systems.py)
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24. [Databases and SQL](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/databases.py)
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25. [MapReduce](https://github.com/joelgrus/data-science-from-scratch/blob/master/code/mapreduce.py)
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20. [Clustering](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/clustering.py)
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21. [Natural Language Processing](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/natural_language_processing.py)
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22. [Network Analysis](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/network_analysis.py)
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23. [Recommender Systems](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/recommender_systems.py)
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24. [Databases and SQL](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/databases.py)
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25. [MapReduce](https://github.com/joelgrus/data-science-from-scratch/blob/master/scratch/mapreduce.py)
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26. Data Ethics
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27. Go Forth And Do Data Science

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