Graduate Professional Experience june 12
Emir7
journal1smartgoals.pptx22/SPRING - Course Number-Section Number Week # – Name of Activity
Name
Due Date:
SMART GOAL
To apply machine learning to predict the customer churn rate for the telecommunication company.
SMART OBJECTIVE …… S = Specific
OBJECTIVE
To develop a machine learning model with a high accuracy for predicting the customer churn for the company.
PLAN
Request for the company’s customer data specifically usage patterns and their billing history
Use my data skills to extract the relevant features that I Can use to predict the churn rate
SMART OBJECTIVE …… M = Measurable
OBJECTIVE
The model should be able to predict the churn rate with and accuracy of 85%.
PLAN
Use logic regression, decision trees to develop the machine learning model
Apply cross-validation to measure the accuracy of the model and to fine-tune the parameters of the model as will be necessary.
SMART OBJECTIVE …… A = Achievable
OBJECTIVE
To use techniques like feature engineering and appropriate model selection to develop the model within the set budget
PLAN
Conduct a literature review on the latest and most appropriate techniques that I can use to predict the customer churn rate
Use scikit-learn and TensorFlow to build the actual model
SMART OBJECTIVE …… R = Relevant
OBJECTIVE
Ensure that the model meets the needs of the company
PLAN
Hold a meeting with my immediate supervisor to discuss the specific requirements of the company department
Incorporate the feedback into my development process
SMART OBJECTIVE …… T = Time-bound
OBJECTIVE
Deliver a functional machine learning model to the head of the department in three months time.
PLAN
Have a project plan that contains project milestone and deadlines for achieving those milestones.
Supervise myself and make necessary adjustments to my plan so as to meet the deliver the machine learning model by the second month to get time for review/revision.
