Reference no: EM133115961

Assessment: Report

In this course, we have been discussing several applications of artificial intelligence, machine learning and data science. The following is a list of some selected topics from the course:

1. Recommender Systems
2. Reinforcement learning
3. Adversarial Learning
4. Image or face recognition
5. Speech/Voice recognition

You can choose any one of the above topics that interest you. Based on the topic that you have selected, you have to write a report and implement code. It should consist of the following broad parts:

Part 1
1. Introduction about the topic you have chosen and describe the main applications of it.
2. Describe the challenges of your topic domain.
3. Compare and contrast different approaches that are used to solve the topic that you have selected. Compare at least two approaches

Part 2
4. Choose a publicly available data set that has a minimum 2000 data points and solve the problem. You can use the following solution approach. (Note: that for some topics one or more of the following steps are not required. Hence, you have to provide justification if you are excluding any of the step mentioned below):
a. Describe the raw dataset
b. Apply pre-processing steps. Describe the benefit of each pre-processing technique that you have applied
c. Extract features or attributes that you will using in your application. Give details of all the features that you are using in your application/project.
d. Apply basic data visualization techniques that are relevant to your topic or dataset
e. Apply a machine learning, deep learning or artificial intelligence approach to solve the problem. Give a reason why you selected the particular approach.

Part 3
5. Write a reflective conclusion about your journey on this project, new things that you have learnt, mistakes that you made etc.
6. Based on your conclusion, add a section that reflects any further work to improve your work
7. Report presentation quality