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ep:labs:05 [2020/11/10 16:40] ioan_adrian.cosma [Tutorial] |
ep:labs:05 [2020/11/10 16:44] (current) ioan_adrian.cosma [Python Scientific Computing Resources] |
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- | ===== Contents ===== | ||

- | {{page>:ep:labs:05:meta:nav&nofooter&noeditbutton}} | ||

- | ===== Python Scientific Computing ===== | + | ===== Python Scientific Computing Resources ===== |

In this lab, we will study a new library in python that offers fast, memory efficient manipulation of vectors, matrices and tensors: **numpy**. We will also study basic plotting of data using the most popular data visualization libraries in the python ecosystem: **matplotlib**. | In this lab, we will study a new library in python that offers fast, memory efficient manipulation of vectors, matrices and tensors: **numpy**. We will also study basic plotting of data using the most popular data visualization libraries in the python ecosystem: **matplotlib**. | ||

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Python is very easy to use, but the downside is that it's not fast at numerical computing. Luckily, we have very eficient libraries for all our use-cases. | Python is very easy to use, but the downside is that it's not fast at numerical computing. Luckily, we have very eficient libraries for all our use-cases. | ||

- | Core computing libraries | + | **Core computing libraries** |

* numpy and scipy: scientific computing | * numpy and scipy: scientific computing | ||

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We also have advanced interactive environments: | We also have advanced interactive environments: | ||

- | * Ipython: advanced python console | + | * IPython: advanced python console |

* Jupyter: notebooks in the browser | * Jupyter: notebooks in the browser | ||

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- [[https://stanford.edu/~shervine/teaching/cs-229/refresher-probabilities-statistics|Probabilities & Stats Refresher]] | - [[https://stanford.edu/~shervine/teaching/cs-229/refresher-probabilities-statistics|Probabilities & Stats Refresher]] | ||

- [[https://stanford.edu/~shervine/teaching/cs-229/refresher-algebra-calculus|Algebra]] | - [[https://stanford.edu/~shervine/teaching/cs-229/refresher-algebra-calculus|Algebra]] | ||

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+ | <note>This lab is organized in a Jupyer Notebook hosted on Google Colab. You will find there some intuitions and applications for numpy and matplotlib. Check out the Tasks section below.</note> | ||

===== Tasks ===== | ===== Tasks ===== |