You need a Google account to do this assessment. You can create a free Google account here: https://myaccount.google.com/.
Once created, you need to navigate to the Google created lab: “Intro to Modelling” here: https://colab.research.google.com/github/google/engedu/blob/master/ml/fe/exercises/intro_to_modeling.ipynb?utm_source=ss-dataprep&utm_campaign=colab-external&utm_medium=referral&utm_content=intro_to_modeling
In addition to following the instructions outlined in the lab, you must:
• Implement a possible solution to each of the tasks outlined in the lab
• Add appropriate comments to your code created, following machine learning best practices for clean coding: https://towardsdatascience.com/clean-machine-learning-codebd32bd0e9212
• Identify various different models that would be appropriate to use as alternatives for the tasks presented by the lab by varying hyperparameters and features. There is also an opportunity for you to create your own custom model by using different regressor functions within TensorFlow.
For more details, see: https://www.tensorflow.org/tutorials/customization/basics
• Familiarise yourself with the assessment’s rubric to understand how the various assignment grades are assigned.
• Produce a manual of 500 words in length outlining:
o The answers to the questions posed in each of the tasks within the lab.
o The choice of models you made during your assessment including the various hyperparameters you chose and feature engineering performed for the appropriate task.
o An analysis of the various models created and an evaluation of their efficiency
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