Hello everyone. I am currently doing my undergrad in Industrial Engineering, about to start my thesis and have a keen interest in machine learning but finding appropriate datasets have been tough. If anyone would be kind enough to suggest websites to find datasets related to my field, it would help me a lot. I have already tried Kaggle but had hard luck finding anything worth working on.
Thank you.
perhaps ... try IBM ...
https://www.ibm.com/topics/machine-learning#:~:text=IBM%20has%20a%20rich%20history%20with%20machine%20learning.
https://www.ibm.com/docs/en/cloud-paks/cp-data/3.5.0?topic=integrations-external-data-sets
https://developer.ibm.com/exchanges/data/all/publaynet/
Hello Mohammad Mynul Islam Mahin!
It's great that you're interested in applying machine learning to your field of industrial engineering. Finding relevant datasets can be a challenge, but there are several sources you can explore:
1. UCI Machine Learning Repository: The University of California, Irvine maintains a repository with a wide range of datasets that might be relevant to your research.
2. Data.gov: This U.S. government website provides access to a wealth of datasets across various domains, including industry and engineering.
3. Open Data Platforms: Many cities, states, and organizations have open data platforms where they share data related to various industries. You might find datasets related to manufacturing, supply chain, and more.
4. Academic Journals and Conferences: Check academic journals and conference proceedings related to industrial engineering. Sometimes, they publish datasets along with research papers.
5. Professional Organizations: Organizations related to industrial engineering may provide datasets or links to relevant data sources. Consider checking out resources from organizations like IISE (Institute of Industrial and Systems Engineers).
6. Collaborate with Your University: Your university's research department or professors in the industrial engineering department might have access to datasets or can guide you to relevant sources.
7. Custom Data Collection: In some cases, you might need to collect your own data through surveys, sensors, or experiments, especially if your thesis topic is specific.
Moreover, Kaggle is a popular platform for datasets, and Google Dataset Search is a valuable resource.
8. Kaggle: Kaggle is a well-known platform for data science and machine learning. While you mentioned having difficulty finding datasets there, it's still a valuable resource. You can explore Kaggle's "Datasets" section and use filters to search for datasets relevant to industrial engineering. Additionally, Kaggle hosts data science competitions, and the competition datasets can also be used for research or projects.
9. Google Dataset Search:Google Dataset Search is a search engine specifically designed to help you find datasets. You can enter keywords related to your field, such as "industrial engineering," and it will return datasets available on the web. It's a great tool to discover datasets from various sources that you might not find through traditional search engines.
Remember that finding the right dataset can take some time and effort, but the effort you put into data acquisition is a crucial part of successful machine learning projects. It's also a good opportunity to network with professionals in your field who may have valuable insights or data sources. Furthermor, Kaggle and Google Dataset Search platforms, along with the other suggestions, can significantly expand your options for finding the right dataset for your work. Happy researching and Good luck with your thesis!
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