From f77d08a6981ce2375993cde10eb40b7397af5d8a Mon Sep 17 00:00:00 2001 From: Dmytro Voytko Date: Mon, 25 Nov 2024 15:10:55 +0200 Subject: [PATCH] Update README.md Added criteria in markdown list format (from Google sheet) --- projects/README.md | 48 ++++++++++++++++++++++++++++++++++++++++++---- 1 file changed, 44 insertions(+), 4 deletions(-) diff --git a/projects/README.md b/projects/README.md index 302b60e2..52640d3d 100644 --- a/projects/README.md +++ b/projects/README.md @@ -70,18 +70,58 @@ Tip: you can use https://nbviewer.org/ to render notebooks if GitHub doesn't wor ## Evaluation Criteria The project will be evaluated using these criteria: - * Problem description + * 0 points: Problem is not described + * 1 point: Problem is described in README birefly without much details + * 2 points: Problem is described in README with enough context, so it's clear what the problem is and how the solution +will be used + * EDA + * 0 points: No EDA + * 1 point: Basic EDA (looking at min-max values, checking for missing values) + * 2 points: Extensive EDA (ranges of values, missing values, analysis of target variable, feature importance analysis) + For images: analyzing the content of the images. + For texts: frequent words, word clouds, etc + * Model training + * 0 points: No model training + * 1 point: Trained only one model, no parameter tuning + * 2 points: Trained multiple models (linear and tree-based). + For neural networks: tried multiple variations - with dropout or without, with extra inner layers or without + * 3 points: Trained multiple models and tuned their parameters. + For neural networks: same as previous, but also with tuning: adjusting learning rate, dropout rate, size of the inner layer, etc. + * Exporting notebook to script -* Model deployment + * 0 points: No script for training a model + * 1 point: The logic for training the model is exported to a separate script + * Reproducibility -* Dependency and environment management + * 0 points: Not possitble to execute the notebook and the training script. Data is missing or it's not easiliy accessible + * 1 point: It's possible to re-execute the notebook and the training script without errors. The dataset is committed in the project repository or there are clear instructions on how to download the data + +* Model deployment + * 0 points: Model is not deployed + * 1 point: Model is deployed (with Flask, BentoML or a similar framework) + +* Dependency and enviroment management + * 0 points: No dependency management + * 1 point: Provided a file with dependencies (requirements.txt, pipfile, bentofile.yaml with dependencies, etc) + * 2 points: Provided a file with dependencies and used virtual environment. README says how to install the dependencies and how to +activate the env + * Containerization + * 0 points: No containerization + * 1 point: Dockerfile is provided or a tool that creates a docker image is used (e.g. BentoML) + * 2 points: The application is containerized and the README describes how to build a contained and how to run it + * Cloud deployment + * 0 points: No deployment to the cloud + * 1 point: Docs describe clearly (with code) how to deploy the service to cloud or kubernetes cluster (local or remote) + * 2 points: There's code for deployment to cloud or kubernetes cluster (local or remote). There's a URL for testing - or video/screenshot of testing it + +Total max 16 points -[Criteria](https://docs.google.com/spreadsheets/d/e/2PACX-1vQCwqAtkjl07MTW-SxWUK9GUvMQ3Pv_fF8UadcuIYLgHa0PlNu9BRWtfLgivI8xSCncQs82HDwGXSm3/pubhtml) +Or the same in table format [Criteria](https://docs.google.com/spreadsheets/d/e/2PACX-1vQCwqAtkjl07MTW-SxWUK9GUvMQ3Pv_fF8UadcuIYLgHa0PlNu9BRWtfLgivI8xSCncQs82HDwGXSm3/pubhtml) ## Cheating and plagiarism