state-of-the-art article on data mining, machine learning, deep learning, and design an example to explain one algorithm presented in the article. Put the example in a PowerPoint presentation.
Make sure to use recent articles rather than older ones.
1. What is the research about? example: kp index prediction for next h-hours using deep learning mechanism. In this example, what is kp index and what is used for?
2. The name of the algorithm that was developed: ie KpNet which used deep learning bilstm, convd, and transformer etc…
3. How this algorithm differ from others articles (should be in the research paper), and how the algorithm works (details).
4. Performance compared to other articles.
5. The data that was used in the article , their location repos, etc… what parameters are used etc… any data processing and collection…
6. Provide an example illustrating the algorithm/research. For example, data from omniweb include 9 solar parameters and a kp index, take number of records from the data , assign them to kp index, after training the the 9 parameters will predict the kp index:
param1,param2, parame3, … param9 kp_index
v1,v2,v3,…..,v9,2.3
and so on and show who the prediction will be done.
All of that based on “YOUR” understanding of the paper, don’t copy and paste from the paper, transformation is ok.
Basically, anyone should read your presentation and get an overall understanding of the paper/article you read.
Think of it as this task:
You are at work, your manager asked you to read an article about an algorithm that he/she wishes to implement. So you will read the paper and present it to your manager and upper management. Remember, upper management don’t care about deep details, they want something straight to the point but with enough information to digest and understand.
Research Paper Category:
1. Machine Learning (ML)
2. Deep Learning (DL)
3. Interpretable Machine Learning (IML)
Example Articles:
https://ui.adsabs.harvard.edu/abs/2022AGUFMSH22F2056W/similarLinks to an external site.
https://ieeexplore.ieee.org/search/searchresult.jsp?newsearch=true&queryText=Interpretable%20Machine%20LearningLinks to an external site.
https://ieeexplore.ieee.org/search/searchresult.jsp?newsearch=true&queryText=deep%20learningLinks to an external site.
This activity addresses the following course learning objectives:
Explain data mining concepts, principles, and methods,
Use a wide range of publicly available data mining tools,
Evaluate the effectiveness and efficiency of these data mining tools based on different performance measures,
Design and implement data mining algorithms, heuristics, methods, and techniques in the context of custom datasets to build custom data mining models and tools.
