Calculating the value of a machine learning project implementation can be a complex process, as it depends on various factors such as the specific use case, the data being used, and the overall goals of the project. However, here are some general steps you can take to properly calculate the value of a machine learning project implementation:

Define the project goals: Clearly define the specific objectives of the project and how
they align with the overall business goals. This will help you identify the metrics you
will use to measure the success of the project.

Identify the data: Determine the type and quality of data
that will be used for the project
, as well as any additional data that may be needed.
This will help you understand the potential
limitations of the project and the resources required
to acquire and prepare the data.

Estimate the costs: Determine the costs associated with the project,
including the cost 
of acquiring and preparing the data,
the cost of developing and deploying the model,
and the ongoing maintenance costs.

Estimate the benefits: Identify the potential benefits of the project,
such as increased revenue,
reduced costs, or improved customer satisfaction.
Estimate the potential impact of these benefits on the business.

Calculate the return on investment (ROI):
Use the information gathered in the previous steps
to calculate the ROI of the project.
To calculate the ROI, divide the benefits by the costs,
and multiply the result by 100 to express it as a percentage.

Assess the risk: Assess the potential risks of the project,
such as data privacy concerns,
regulatory compliance, or technical limitations,
and determine how they will be mitigated.

Monitor and evaluate:
Implement a plan to monitor and evaluate the performance of the project.
This will help you identify any issues that need
to be addressed and measure the project's
impact on the business over time.

It’s important to note that the value of a machine learning project implementation can be difficult to quantify and may change over time as the business and market evolves. Therefore, it’s important to continuously monitor and evaluate the project’s performance and adjust the strategy accordingly.