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aecincode_tutorials

https://github.com/stasya00/aecincode_tutorials

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    Academic email domains
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    Institutional organization owner
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (12.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: STASYA00
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 119 MB
Statistics
  • Stars: 3
  • Watchers: 3
  • Forks: 19
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation

README.md

Contributors Forks Stargazers Issues MIT License LinkedIn


Logo

IAAC: AI in the Built Environment.
View Demo · Report Bug · Request Feature

Table of Contents
  1. About The Project
  2. Getting Started
  3. License
  4. Contact
  5. Acknowledgments

About The Project

Part of the course AI in the built Environment in IAAC 2024.

Length: approx. 20 hours.\ Prerequisites: Intermediate Python knowledge (Datacamp courses: Introduction to Python, Intermediate Python).\ In the end of the workshop: you should be able to understand the advantages and disadvantages of different ML models, being able to find and use them on tabular and image data as well as understand the logic of ML and its different phases.

Intro

These tutorials aim to give a gentle introduction to ML learning for students of Architecture and Urban Planning.

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Built With

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Getting Started

Open the notebooks/01_data_cleaning.ipynb in colab

Prerequisites

Usage

  • Run the cells one by one
  • Read the comments
  • Do the exercises
  • If possible: read through the linked resources :smile:

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License

All teaching material is made available under a Creative Commons Attribution-ShareAlike 4.0 International licence.

In simpler words you can:

  • share and distribute the material
  • adapt the material to your needs: transform, mix and build upon it

Nevertheless you must:

  • give appropriate credit
  • provide the link to the license and the original material and indicate the changes that were made.
  • distribute the material under the same license as the original or compatible ones

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How to cite

S. Fedorova, ML algorithms for architects, (2024), GitHub repository, https://github.com/STASYA00/AECinCode_tutorials/

or use Github citation on the right of the page for APA or bibtex formats

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Contact

Stasja - @stasya00 - e-mail - LinkedIn

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Acknowledgments

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Owner

  • Name: Stasja
  • Login: STASYA00
  • Kind: user
  • Location: Stockholm
  • Company: Hennes & Mauritz | H&M

build projects on the intersection of ML, CS, 3D, fashion and architecture. Specifically interested in 3d body generation and linguistics

Citation (CITATION.cff) 

cff-version: 1.0.0
message: "If you use these materials, please cite it as below."
authors:
- family-names: "Fedorova"
  given-names: "Stanislava"
  orcid: "https://orcid.org/0009-0003-4293-7985"
title: "ML algorithms for architects"
version: 1.0.0
# doi: 10.5281/zenodo.1234
date-released: 2024-04-09
url: "https://github.com/STASYA00/AECinCode_tutorials/"

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