https://github.com/adamouization/python-machine-learning-data-science-notes

:orange_book: Jupyter notebooks containing useful Python code and notes for general Machine Learning and Data Science projects.

https://github.com/adamouization/python-machine-learning-data-science-notes

Science Score: 13.0%

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  • CITATION.cff file
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  • Scientific vocabulary similarity
    Low similarity (8.9%) to scientific vocabulary

Keywords

data data-science data-visualization guide jupyter jupyter-notebook machine-learning matplotlib notes numpy pandas pandas-dataframe python seaborn
Last synced: 6 months ago · JSON representation

Repository

:orange_book: Jupyter notebooks containing useful Python code and notes for general Machine Learning and Data Science projects.

Basic Info
  • Host: GitHub
  • Owner: Adamouization
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: master
  • Homepage:
  • Size: 98.4 MB
Statistics
  • Stars: 0
  • Watchers: 3
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
data data-science data-visualization guide jupyter jupyter-notebook machine-learning matplotlib notes numpy pandas pandas-dataframe python seaborn
Created over 5 years ago · Last pushed over 5 years ago
Metadata Files
Readme License

README.md

Python - Machine Learning & Data Science Notes HitCount GitHub stars GitHub license

Python code and notes in the form of Jupyter Notebooks useful for general Machine Learning and Data Science projects.

Covers the following topics:

  • [X] Pandas operations
  • [X] Data Cleaning in Pandas
  • [X] Data Visualisation in Matplotlib and Seaborn
  • [ ] Scikit-Learn models
  • [X] PyTorch CNN on Fashion MNIST dataset

You download/read the notebooks format in the notebooks directory.

Online Sources

Usage

Download this repository, create a virtual environment and activate it:

virtualenv ~/Environments/Python-Machine-Learning-Data-Science-Notes source Python-Machine-Learning-Data-Science-Notes/bin/activate

Once you have the virtualenv activated and set up, cd into the project directory and install the requirements needed to run the notebooks:

pip install -r requirements.txt

Open Jupyter and access/run the notebooks individually:

jupyter lab

Data

The datasets found in the data directory were downloaded from public open-sourced Kaggle datasets.

License

Contact

Owner

  • Name: Adam Jaamour
  • Login: Adamouization
  • Kind: user
  • Location: United Kingdom
  • Company: @NewDayTechnology

💻 Data Scientist @NewDayTechnology 🧠 MSc AI @ Uni of St Andrews 📓 BSc Computer Science @ Uni of Bath 💼 Former SWE @ Scuderia Alpha Tauri F1 Team

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