Anuket Project
Delivery and Assessment
- 1 Delivery
- 1.1 Code
- 1.2 Documentation
- 1.3 Output
- 2 Assessment
- 2.1 Categories
- 2.2 Weightage Distribution
Delivery
Code
Documentation
Output
Code
Either .ipynb or .py
requirements.txt - List of dependent libraries
References, if any code is reused
Documentation
Document (.md or .rst) how to
Provide input
Run
Collect Output.
Documentation (.md or .rst) of the output
Maximum of 5-Min video of running the code and generating the output – with other description
Use zoom with screen-share and record to cloud to create this video and send the link.
Output
Create separate folders for each node.
Minimum: 1-Node
In each node-folder
Create folders for each metrics and place generated files in the these 4 folders.
CPU (At least 1 of the below three)
percent-user
percent-system
percent-idle
Memory (At least 1 of the below two)
used
free
Interface (At least 1 of the below two)
Packets/Octets
Dropped/Errors
Load
load*
Each files should have at least 7000 Entries.
* Only load file will have more than 2 columns.
Zip the main folder
Name it with your team name.
Assessment
Categories
Metrics Generated
CPU, Memory, Network and Load.
Novelty
Neural Network
Discriminator
Accuracy
Range Validity
Max and Mins
Variations
Trend
Implementation
Code Quality
Code Re-Use
Individual Metrics
Distribution
Autocorrelation
ARIMA
Comparative Metrics
DTW
Wasserstein Distance
RMSE
Maximum Mean Discrepancy
Mutual Information