Update README.md: add criteria in markdown list format

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