https://github.com/binakot/python3-course
https://github.com/binakot/python3-course
course data-science learning matplotlib numpy pandas python
Last synced: about 1 month ago
JSON representation
- Host: GitHub
- URL: https://github.com/binakot/python3-course
- Owner: binakot
- License: mit
- Created: 2021-02-13T19:34:11.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-02-22T12:40:27.000Z (almost 5 years ago)
- Last Synced: 2025-01-16T12:55:05.759Z (about 1 year ago)
- Topics: course, data-science, learning, matplotlib, numpy, pandas, python
- Language: Jupyter Notebook
- Homepage:
- Size: 2.18 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Python3 Course
Run [Anaconda](https://docs.anaconda.com/anaconda)
with [Jupiter Notebook](https://jupyter-notebook.readthedocs.io/en/stable/notebook.html)
via `Docker` container:
```bash
$ docker pull continuumio/anaconda3
$ docker run \
--name anaconda3-jupyter-notebook \
-p 8888:8888 \
-v $(pwd)/notebooks:/opt/notebooks \
-d continuumio/anaconda3 \
/bin/bash -c "/opt/conda/bin/conda install jupyter -y --quiet && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root"
$ docker container logs anaconda3-jupyter-notebook
```
Now open [http://localhost:8888](http://localhost:8888) with a token from container logs.
---
# Useful links
## Python
* Python language:
[https://www.python.org](https://www.python.org).
* Python Package Index (PyPI):
[https://pypi.org](https://pypi.org).
* Package Installer for Python (PIP):
[https://pypi.org/project/pip](https://pypi.org/project/pip).
* Python Virtual Environment (VENV):
[https://virtualenv.pypa.io/en/latest](https://virtualenv.pypa.io/en/latest).
### Development
* Type hints:
[https://docs.python.org/3/library/typing.html](https://docs.python.org/3/library/typing.html).
* Data classes:
[https://docs.python.org/3/library/dataclasses.html](https://docs.python.org/3/library/dataclasses.html).
* Functions creating iterators for efficient looping:
[https://docs.python.org/3/library/itertools.html](https://docs.python.org/3/library/itertools.html).
### Tests & Lints
* Unit testing framework:
[https://docs.python.org/3/library/unittest.html](https://docs.python.org/3/library/unittest.html).
* Interactive documentation tests:
[https://docs.python.org/3/library/doctest.html](https://docs.python.org/3/library/doctest.html).
* Static code analysis tool:
[https://www.pylint.org](https://www.pylint.org).
* Tool that glues together pep8, pyflakes, mccabe, and third-party plugins:
[https://gitlab.com/pycqa/flake8](https://gitlab.com/pycqa/flake8).
### Dependencies
* The elegant and simple HTTP library:
[https://requests.readthedocs.io](https://requests.readthedocs.io).
* Micro web framework:
[https://flask.palletsprojects.com](https://flask.palletsprojects.com).
---
## Computer & Data Science
### Common
* Greedy algorithms:
[https://en.wikipedia.org/wiki/Greedy_algorithm](https://en.wikipedia.org/wiki/Greedy_algorithm).
* Dynamic programming:
[https://en.wikipedia.org/wiki/Dynamic_programming](https://en.wikipedia.org/wiki/Dynamic_programming).
* Machine Learning for everyone:
[https://vas3k.com/blog/machine_learning](https://vas3k.com/blog/machine_learning).
* Machine Learning for humans:
[https://medium.com/machine-learning-for-humans](https://medium.com/machine-learning-for-humans).
* The neural network zoo:
[https://www.asimovinstitute.org/neural-network-zoo](https://www.asimovinstitute.org/neural-network-zoo).
### Python
#### Libraries
* Python-based ecosystem of open-source software for mathematics, science, and engineering:
[https://www.scipy.org](https://www.scipy.org).
* Enhanced interactive interpreter:
[http://ipython.org](http://ipython.org).
* Multidimensional arrays and matrices computing:
[https://numpy.org](https://numpy.org).
* Collection of algorithms and high-level commands for manipulating and visualizing data (builds on NumPy):
[https://www.scipy.org/scipylib](https://www.scipy.org/scipylib).
* Data structures and tools for data analysis (builds on NumPy):
[https://pandas.pydata.org](https://pandas.pydata.org).
* 2D plots and graphs:
[https://matplotlib.org](https://matplotlib.org).
* Data visualization library (builds on matplotlib):
[https://seaborn.pydata.org](https://seaborn.pydata.org).
* Graphing library makes interactive, publication-quality graphs with 3D:
[https://plotly.com/python](https://plotly.com/python).
* Interactive visualization library for modern web browsers:
[https://docs.bokeh.org](https://docs.bokeh.org).
* Working with geospatial data (extends the datatypes used by pandas):
[https://geopandas.readthedocs.io](https://geopandas.readthedocs.io).
* Set of algorithms for machine learning and data mining tasks (builds on NumPy and SciPy):
[https://scikit-learn.org](https://scikit-learn.org).
* Deep learning framework:
[https://keras.io](https://keras.io).
* Classes and functions for the estimation of statistical models, as well as for conducting statistical tests, and statistical data exploration ((builds on NumPy & SciPy):
[https://www.statsmodels.org](https://www.statsmodels.org).
* Symbolic mathematics:
[https://www.sympy.org/en/index.html](https://www.sympy.org/en/index.html).
* Flexible library for parallel computing (integrated with NumPy, pandas, and scikit-learn):
[https://dask.org](https://dask.org).
#### Anaconda
* Open source projects provided by Anaconda:
[https://www.anaconda.com/open-source](https://www.anaconda.com/open-source).
* Anaconda blog:
[https://www.anaconda.com/blog](https://www.anaconda.com/blog).
#### Jupiter
* Jupiter Widgets gallery:
[https://jupyter.org/widgets](https://jupyter.org/widgets).
* Jupyter Notebooks gallery:
[https://nbviewer.jupyter.org](https://nbviewer.jupyter.org).
* Data science Jupyter notebooks:
[https://github.com/donnemartin/data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks).
---
### Others
* Platform for machine learning:
[https://www.tensorflow.org](https://www.tensorflow.org).