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Dashdot Tech Part 3: How We Predict Growth and Rental Increases So Accurately! | #263

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Manage episode 428104124 series 3377749
Contenu fourni par Dashdot. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Dashdot ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Anyone can make rent and price forecasts. But the ability to predict growth and rental increases accurately is next to impossible.

So, how do we do it?

Well, for starters, we’ve got models all powered by machine-learning algorithms.

We're talking about crunching numbers and zapping them with AI magic to predict prices 15 months down the road. We're talking confidence intervals, and predictions so accurate they put weather forecasts to shame.

And did we mention the accuracy? Our models hit the bullseye within 1%, nearly 75% of the time. We're at 85% accuracy on predicting price shifts, and a whopping 98% on foreseeing the not-so-great ones.

But we're not just about numbers and data. We're talking innovation that's turning heads and getting awards.

So join us as Julian Mougenot wraps up with all this mind-bending data and insights for Part 3 of our Dashdot Tech series.

In case you missed it, here are the links to Parts 1 and 2:

If you love this episode, email us at podcast@dashdot.com.au, and don’t forget to subscribe, rate, and share this podcast!

See you on the inside!

In this episode, we cover:

  • 00:00 Coming Up
  • 04:47 How Data Analysis Predicts Property Prices
  • 11:13 Historical Data and Statistical Models in Property Market Predictions
  • 17:16 Property Price Forecast Accuracy with Machine Learning Models
  • 24:44 Navigating Real Estate Investment and Forecasting Models
  • 31:33 Unpacking Property Investment in Western Australia's Gem

Connect With Us:

See omnystudio.com/listener for privacy information.

  continue reading

285 episodes

Artwork
iconPartager
 
Manage episode 428104124 series 3377749
Contenu fourni par Dashdot. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Dashdot ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Anyone can make rent and price forecasts. But the ability to predict growth and rental increases accurately is next to impossible.

So, how do we do it?

Well, for starters, we’ve got models all powered by machine-learning algorithms.

We're talking about crunching numbers and zapping them with AI magic to predict prices 15 months down the road. We're talking confidence intervals, and predictions so accurate they put weather forecasts to shame.

And did we mention the accuracy? Our models hit the bullseye within 1%, nearly 75% of the time. We're at 85% accuracy on predicting price shifts, and a whopping 98% on foreseeing the not-so-great ones.

But we're not just about numbers and data. We're talking innovation that's turning heads and getting awards.

So join us as Julian Mougenot wraps up with all this mind-bending data and insights for Part 3 of our Dashdot Tech series.

In case you missed it, here are the links to Parts 1 and 2:

If you love this episode, email us at podcast@dashdot.com.au, and don’t forget to subscribe, rate, and share this podcast!

See you on the inside!

In this episode, we cover:

  • 00:00 Coming Up
  • 04:47 How Data Analysis Predicts Property Prices
  • 11:13 Historical Data and Statistical Models in Property Market Predictions
  • 17:16 Property Price Forecast Accuracy with Machine Learning Models
  • 24:44 Navigating Real Estate Investment and Forecasting Models
  • 31:33 Unpacking Property Investment in Western Australia's Gem

Connect With Us:

See omnystudio.com/listener for privacy information.

  continue reading

285 episodes

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