Please note: I've put the topic down under "Computer Science - Design & Analysis of Algorithms". However, the topic really is "Artificial Intelligence & Machine Learning". Not necessarily computer...

Please note: I've put the topic down under "Computer Science - Design & Analysis of Algorithms". However, the topic really is "Artificial Intelligence & Machine Learning". Not necessarily computer science.

Background- this assignment forms part of a course on Artificial Intelligence. This is the week 2 course work assignment. The week 2 course outline is as follows:

Topics Covered

- What is Machine Learning?
- How is Machine Learning used and applied?

- What is Deep Learning and how is it different?
- How does it work and how is it applied?
Learning outcomes

Upon the completion of the week, students will be able to:

- Understand what Machine learning is, where it’s used and how

it’s applied
- Understand what deep learning is, how it’s different
- Understand how deep learning works and how its applied




THE ASSIGNMENTRefer to the provided post about a machine learning model.
Post-https://towardsdatascience.com/predict-the-number-of-likes-on-instagram-a7ec5c020203

Provide 2 to 3 paragraphs of critical analysis, challenging the purpose of the model. Focus on these questions:
- Is this model useful?- Does it need further investigation and work?
Note: It’s OK if you do not understand the technical component of the post.
Project file format - Word

Note: The assignment needs to be well written, cover off the questions, show a good understanding of Machine Learning, show evidence of reading and careful analysis of the provided post.


Delivery: within 24 hours






Some further reading background (if required) -


https://www.youtube.com/watch?v=-SgkLEuhfbg


https://www.youtube.com/watch?v=nKW8Ndu7Mjw




https://cs.stanford.edu/people/karpathy/convnetjs/demo/mnist.html




https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.38504&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false