https://github.com/theremotecoder/python-ai-ml--jupyter-notebooks

ML + AI experiments with python, intended for Jupyter Notebooks (e.g. via Google Colab). Central source of personal language knowledge.
https://github.com/theremotecoder/python-ai-ml--jupyter-notebooks

ai artificial-intelligence artificial-intelligence-algorithms artificial-neural-networks jupyter jupyter-notebook jupyter-notebooks keras keras-neural-networks keras-tensorflow machine-learning machinelearning ml python python-ai python-app python-keras python-script python-tensorflow python3

Last synced: about 1 month ago
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ML + AI experiments with python, intended for Jupyter Notebooks (e.g. via Google Colab). Central source of personal language knowledge.

• Host: GitHub
• URL: https://github.com/theremotecoder/python-ai-ml--jupyter-notebooks
• Owner: TheRemoteCoder
• License: mit
• Created: 2023-06-02T14:55:43.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-07-03T12:46:56.000Z (over 1 year ago)
• Last Synced: 2024-11-11T14:45:18.632Z (3 months ago)
• Topics: ai, artificial-intelligence, artificial-intelligence-algorithms, artificial-neural-networks, jupyter, jupyter-notebook, jupyter-notebooks, keras, keras-neural-networks, keras-tensorflow, machine-learning, machinelearning, ml, python, python-ai, python-app, python-keras, python-script, python-tensorflow, python3
• Language: Python
• Homepage:
• Size: 12.7 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# python Notebooks

- [About](#about)

- [Use](#use)

- [Disclaimer](#disclaimer)

---

## About

Showcased uses of python for AI/ML purposes.

Personal use to document language and API feature learning, as well as early projects.

## Use

Run in own python environments or Jupyter Notebooks (like Google Colab).

## Disclaimer

This is a private repository made public, to demonstrate an interest in new technologies and potential future skillset developing.

> As of 2023-05, the presented stack is not part of my core skills. To speed up early learning and development processes, the presented code has been derived from courses, co-created with video tutorials or with the help of AI (LLM).

I assume the presented content is not the best source or best practice in this field. However, others might find this interesting as well.