By now, you will have already learned that NumPy, one of the fundamental packages for scientific computing, forms at least for a partthe fundament of other importantpackages that you might use used for data manipulation and machine learning with python. One of those packages is SciPy, another oneof the core packages for scientific computing in Python that provides mathematical algorithms and convenience functions built on theNumPy extension of Python.

You might now wonder why this library might come in handy for data science.

Well, SciPy has many modules that will help you to understand some of the basic components that you need to master when you're learning data science, namely, math, stats and machine learning. You can find out what other things you need to tackle to learn data sciencehere. You'll see that for statistics, for example, a module like scipy.stats , etc. will definitely be of interest to you.

The other topic that was mentioned was machine learning: here, the scipy.linalg and scipy.sparse modules will offer everything that you're looking for to understand machine learning concepts such as eigenvalues, regression, and matrix multiplication...

But, what is maybe the most obvious is that most machine learning techniques deal with high-dimensional data and that data is often represented as matrices. What's more, you'll need to understand how to manipulate these matrices.

That is why DataCamp has made a SciPy cheat sheet that will help you to master linear algebra with Python.

Take a look by clicking on the button below:

You'll see that this SciPy cheat sheet covers the basics of linear algebrathat you need to get started: it provides a brief explanation of what thelibrary has to offer and how you can use it to interact with NumPy, and goes on to summarize topics in linear algebra, such as matrix creation, matrix functions,basic routines that you can perform with matrices, and matrix decompositions from scipy.linalg . Sparse matrices are also included, with their own routines, functions, and decompositions from the scipy.sparse module.

PS.Don't miss our other Python cheat sheets for data science that coverNumpy, Scikit-Learn , Bokeh ,Pandasand thePython basics.

tags: data,learning,Python,scipy,SciPy,will

1.凡CodeSecTeam转载的文章,均出自其它媒体或其他官网介绍,目的在于传递更多的信息,并不代表本站赞同其观点和其真实性负责；
2.转载的文章仅代表原创作者观点,与本站无关。其原创性以及文中陈述文字和内容未经本站证实,本站对该文以及其中全部或者部分内容、文字的真实性、完整性、及时性，不作出任何保证或承若；
3.如本站转载稿涉及版权等问题,请作者及时联系本站,我们会及时处理。