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numpy, pandas, scikit-learn cheat sheet (速查表) 1. scikit-learn cheat sheet2. numpy cheat sheet3. pandas cheat sheethttps://www.dataquest.io/blog/pandas-cheat-sheet/

1. scikit-learn cheat sheet

官方連結如下:http://scikit-learn.org/stable/tutorial/machine_learning_map/

Often the hardest part of solving a machine learning problem can be finding the right estimator for the job.

Different estimators are better suited for different types of data and different problems.

The flowchart below is designed to give users a bit of a rough guide on how to approach problems with regard to which estimators to try on your data.

Click on any estimator in the chart below to see its documentation.

下面是其速查表,中文版以及英文版:

numpy, pandas, scikit-learn cheat sheet (速查表) 1. scikit-learn cheat sheet2. numpy cheat sheet3. pandas cheat sheethttps://www.dataquest.io/blog/pandas-cheat-sheet/
numpy, pandas, scikit-learn cheat sheet (速查表) 1. scikit-learn cheat sheet2. numpy cheat sheet3. pandas cheat sheethttps://www.dataquest.io/blog/pandas-cheat-sheet/

2. numpy cheat sheet

NumPy is the library that gives Python its ability to work with data at speed. Originally, launched in 1995 as 'Numeric,' NumPy is the foundation on which many important Python data science libraries are built, including Pandas, SciPy and scikit-learn.

It's common when first learning NumPy to have trouble remembering all the functions and methods that you need, and while at Dataquest we advocate getting used to consulting the NumPy documentation, sometimes it's nice to have a handy reference, so we've put together this cheat sheet to help you out!

If you're interested in learning NumPy, you can consult our NumPy tutorial blog post, or you can signup for free and start learning NumPy through our interactive Python data science course.

Download a Printable PDF of this Cheat Sheet

https://www.dataquest.io/blog/numpy-cheat-sheet/

3. pandas cheat sheet

Pandas is arguably the most important Python package for data science. Not only does it give you lots of methods and functions that make working with data easier, but it has been optimized for speed which gives you a significant advantage compared with working with numeric data using Python's built-in functions.

It's common when first learning pandas to have trouble remembering all the functions and methods that you need, and while at Dataquest we advocate getting used to consulting the pandas documentation, sometimes it's nice to have a handy reference, so we've put together this cheat sheet to help you out!

If you're interested in learning pandas, you can consult our two-part pandas tutorialblog post, or you can signup for free and start learning pandas through our interactive pandas for data science course.

Download a Printable PDF of this Cheat Sheet

https://www.dataquest.io/blog/pandas-cheat-sheet/

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