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MTech-KE-DWBA

Github repository for MTech KE DWBA CA project team work

Team members:

Choong Yue Lin
Ho Kok Loon
Lee Tin Onn
Lee Wai Tong Peter
Lei Jun
Vincent Leung

Directory structure:

+-- README.md          <- The top-level README for developers using this project.
+-- data
¦   +-- interim        <- Intermediate data that has been transformed. ETL
¦   +-- processed      <- The final, canonical data sets for modeling.
¦   +-- raw            <- The original, immutable data dump.
¦   ¦   +-- HDB <- HDB data
¦   ¦   +-- Humidity <- Humidity data
¦   ¦   +-- Weather <- Rain, temperature and windspeed data
¦
+-- docs               <- documentations
¦
+-- models             <- Trained and serialized models, model predictions, or model summaries
¦
+-- notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
¦                         the creator's initials, and a short `-` delimited description, e.g.
¦                         `1.0-jqp-initial-data-exploration`.
¦
+-- references         <- Data dictionaries, manuals, and all other explanatory materials.
¦
+-- reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
¦   +-- figures        <- Generated graphics and figures to be used in reporting
¦
+-- requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
¦                         generated with `pip freeze > requirements.txt`
¦
+-- src                <- Source code for use in this project.
¦   +-- __init__.py    <- Makes src a Python module
¦   ¦
¦   +-- data
¦   ¦   +-- download_scripts <- Scripts for downloading from each raw data
¦   ¦   ¦                       source
¦   ¦   +-- download_raw_data.py <- Script to download raw data using
¦   ¦   ¦                           modules in `download_scripts/`
¦   ¦   +-- make_dataset.py <- Script to clean raw data
¦   ¦
¦   +-- features       <- Scripts to turn raw data into features for modeling
¦   ¦   +-- build_features.py
¦   ¦
¦   +-- models         <- Scripts to train models and then use trained models to make
¦   ¦   ¦                 predictions
¦   ¦   +-- predict_model.py
¦   ¦   +-- train_model.py
¦   ¦
¦   +-- visualization  <- Scripts to create exploratory and results oriented visualizations
¦       +-- visualize.py

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