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--- supp:python:scientific_python [2019/11/18 10:27] – [Jupyter Notebook and JupyterLab] admin
+++ supp:python:scientific_python [2020/04/21 06:05] (current) – [Python Numpy Tutorial (with Jupyter and Colab)] admin
@@ Line 1: / Line 1: @@
 ====== Scientific Python ======
-===== Jupyter Notebook and JupyterLab =====
+===== Python Numpy Tutorial (with Jupyter and Colab) =====
+This great interactive [[https://cs231n.github.io/python-numpy-tutorial/|Python Numpy Tutorial]] \\ is part of the Stanford class [[https://cs231n.github.io/|CS231n: Convolutional Neural Networks for Visual Recognition]]
+The course is also provided on in interactive **[[https://colab.research.google.com/github/cs231n/cs231n.github.io/blob/master/python-colab.ipynb|Google Colab]]** session.
-We often use [[https://jupyterlab.readthedocs.io/en/stable/user/notebook.html|Jupyter Notebooks]] in several of my courses together with [[https://jupyterlab.readthedocs.io/en/stable/|JupyterLab]] being the current user interface of choice.
-In my view this interactive development environment maps the workflow of developing ideas and software for data analysis best. I especially appreciate the mixture of code cells and formatted text cells, the latter using Markdown (a lightweight markup language) and MathJax (special markup language for pretty math printing) for producing well formatted text including mathematical expressions.
-This environment allows me to develop, describe and implement ideas to solve certain problems in a highly dynamic manner. Starting with an assumption on how a particular problem can be solved, I implement it (usually in Python) and test.
 ===== Think Python =====