The AI Platform That Makes Data Science Easy (Part 1)
I am pretty sure you’ve always wondered how far generative AI can go. Well, the answer is: pretty far. In recent years, there have been major advancements in the field of generative AI, and these advancements are having a significant impact on a wide range of industries, including real estate. Large language models (LLMs) have led to the development of tools like ChatGPT, Bard, and most recently Claude.ai which we will use today to generate a realistic real estate investment strategy.
From generative adversarial networks (GANs) to today´s … trends continue to evolve and will play an increasingly broader role in all industries including real estate. Today we´re gonna create a personalized real estate recommendation and why not automate the process of home buying and selling, and in the future create virtual worlds where people can experience real estate before they buy it?
*Disclaimer: This post is for informational purposes only and should not be construed as financial advice. Real estate investing is a complex and risky endeavor, and it is important to do your own research before making any investment decisions. AI-generated content is not a substitute for professional advice, and readers should do their own research before making any investment decisions.😀
WHAT: a Claude AI-driven (Bard AI-driven in another post) approach to maximizing ROI for residential real estate investors in Switzerland based on recent home price trends.
In order to achieve this☝🏿, we first need to find relevant data. Let´s head to official sources and download the latest Swiss Residential Property Price Index (IMPI) 2023.
As you can see, the dataset is in German but solving that will be the first magic.ai trick, Claude ai just like many other LLMs support multiple languages.
Who: for “wealthy” investors looking after real estate opportunities in Switzerland.
An investor by definition is looking for profitable investments. Claude.ai is using embedded documents correlated with LLms pre-trained in the Swiss real estate market to build recommendations and provide ad-hoc answers.
But first, it is important to note that:
. IMPI is published quarterly by the Swiss Federal Statistical Office (BFS).
. IMPI is based on a sample of sales transactions of residential properties in Switzerland.
. IMPI is adjusted for inflation.
. IMPI is not a perfect measure of residential property prices, but it is one of the most reliable measures available. https://www.bfs.admin.ch/bfs/en/home/statistics/prices/surveys/impi.html
How: so how do we proceed with our document?
🚶First and for simplicity, let´s convert the document to pdf and upload it to a cloud drive (with a shareable public link on google drive as in my case).
Claude.ai seems not to work with .xlsx files at the moment of this post.
On the document screenshot, we can already spot some attributes and meta/data.
🚶in the next step, we head to claude.ai and log in, or register if not already done. Then ✍🏿 initialize with a simple prompt: summarize the attached document!
let´s quickly check info is accurate…
1-what was the total prize considering the document in Switzerland in Q3 2022? (claude.ai also proposes additional statistics based on the context)
2- what is the “Gemeinde” type meaning in the document?
3- Based on the document, where is the ROI more interesting considering the Gemeinde type, considering a rental investment strategy?
4-what does EFH stands for in the document?
5-what budget would you recommend preparing in order to afford an EFH?
6- considering the document previously attached, what could be the expected price for an EFH in the next 4 years?
7-propose a successful investment strategy based on this document, using data science to leverage info from this document and rewrite this with the five w strategy
Conclusion
In this part 1, we have explored the potential of generative AI in the real estate industry. We have seen how Claude.ai can be used to generate a realistic real estate investment strategy based on IMPI's recent home price trends in Switzerland. This strategy is based on the following five Ws:
- Who: Wealthy investors looking for real estate opportunities in Switzerland.
- What: Single-family homes in urban municipalities of a large metropolitan area.
- When: The next four years.
- Where: Switzerland.
- Why: To achieve a 29.5% ROI.
This strategy is just one example of how generative AI can be used to make real estate investing more efficient and profitable. As generative AI continues to develop, we can expect to see even more innovative and groundbreaking applications in this field.
In this first part, we have explored basic approaches, but part 2 is under construction and we will cover all the latest trendy research in the field and see if we can address more deeply the investment strategy. For instance, we will look at concrete examples as depicted in this paper “Data Science for the Real Estate Industry” by Bekkerman, Josifovski, and Provost.
If you are a real estate investor, I encourage you to explore the potential of generative AI. Claude.ai is a powerful tool that can help you make better investment decisions. With Claude.ai, you can access the latest real estate data and insights, and generate personalized investment strategies that are tailored to your specific goals and objectives.
If you would like to know more about Claude.ai, do not hesitate to visit their website at https://www.anthropic.com/index/introducing-claude
For any questions and inquiries, ping me at contact@nyami.fr
(PS:
if you´re interested in log analytics check this https://scholar.googleusercontent.com/scholar?q=cache:DmBR_9E1JIYJ:scholar.google.com/+nyami+ronald+&hl=fr&as_sdt=0,5)
