LLY-DML is part of the LILY project and is a Quantum Machine Learning model. It uses so-called L-Gates. These gates are Machine Learning gates that modify their state based on an input to map to a desired state of an input.
In the tickets #45 and #44, parts of the report are being created to represent the training data. Now, each individual graphic and presentation needs to be reviewed to determine the type of information required. It’s essential to check if this information is written into the specified section of train.json and how it is written there. The questions that need to be answered are as follows:
What data is needed for each graph, table, etc.?
Where and how should the data be written into train.json?
Which data is still missing, and where does it need to be added in train.json?
How should the data be transformed?
In the tickets #45 and #44, parts of the report are being created to represent the training data. Now, each individual graphic and presentation needs to be reviewed to determine the type of information required. It’s essential to check if this information is written into the specified section of train.json and how it is written there. The questions that need to be answered are as follows:
What data is needed for each graph, table, etc.? Where and how should the data be written into train.json? Which data is still missing, and where does it need to be added in train.json? How should the data be transformed?