edit homepage with disclaimer; add bullet point for pretrained/founda…

…tion models

index.qmd

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 Nexus is the [ML+X](https://datascience.wisc.edu/ml-community/) community’s centralized hub for sharing machine learning (ML) resources.
 
+**Website in development:** The official Nexus launch date is scheduled for 7/25/24. Check back then for more substantial updates!
+
 ### What kinds of resources are hosted on Nexus?
 Any content (original or external) that can help make the practice of ML more accessible, efficient, and reproducible is welcome on the Nexus platform! This includes, but is not limited to:
 
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 * 🚀 [**Exploratory Data Analysis (EDA) Case Studies**](https://uw-madison-datascience.github.io/ML-X-Nexus/ML-stories/): As the adage goes, "garbage in, garbage out," emphasizing the critical role of EDA in ensuring the quality and integrity of any ML pipeline. These case studies offer firsthand experiences in navigating real-world datasets, demonstrating the technical steps and domain knowledge needed to explore different data types (time-series, tabular, images, etc.) from various fields.
 
+* **Coming soon!** Recommendations and guides for datasets, pretrained models, and foundation models.
 
 ### Make a contribution to Nexus!
 This website is a team effort! We welcome and encourage individuals to contribute their own ML guide or story to Nexus. For instructions on how to contribute, visit [How to Contribute?](https://uw-madison-datascience.github.io/ML-X-Nexus/how-to-contribute.html).