COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Training the model
|
|
|
Evaluating the model
|
|
|
Deploying the model
|
|
|
None of the above
|
Detailed explanation-1: -Q3. At what stage of the Data Science life cycle do you optimize the parameters? Parameters are optimized in the last stage of the implementation of a data science project. This phase is known as the monitoring or closure phase.
Detailed explanation-2: -8. Model evaluation. The results of the data mining model are then evaluated against the hypotheses designed in stage three. Every correct result is then stored in the IKR, ready to influence future projects.
Detailed explanation-3: -Phase 4: Model Building This step of data analytics architecture comprises developing data sets for testing, training, and production purposes.
Detailed explanation-4: -Phase 4: Model Building This stage of the data analytics Life Cycle involves creating data sets for testing, training, and production. The data analytics professionals develop and operate the model they designed in the previous stage with proper effort.