When creating Synthetic data, we make sure that city, state, and country are not shuffled. They cannot be shuffled. For a customer, we cannot have new york in a column and alaska in another column since they are geographically far from each other.
One approach is to initialise a neural network with random junk as parameters and adjust these parameters to fit well the real-world data but not overfit. The output will be similar to the real-world data but not the same. Another approach is to use classical statistical methods and extend them with an overfitted neural network. For example, an ARIMA model can generate artificial residuals, which the neural network can augment.
Working on a project using synthetic data meaning this video came at the right time. 👌🏾
Since AI is "all about the data", more and more videos about data integrity and privacy best practices would be well appreciated. Thank you.
I was thinking that these hosts are really good at writing backwards, but then I realized the video is probably mirrored. 😂
It’s not mirrored, they are using a lightboard
AI can be used to reverse a mirror effect.
They're using lightboard: ua-cam.com/video/Uoz_osFtw68/v-deo.html
great vid, thanks
Fantastic job ! Hats off !
How do you guys write backwards like that??
Practice
Can you explain that new york, texas thing to non-American? I don't understand.
When creating Synthetic data, we make sure that city, state, and country are not shuffled. They cannot be shuffled. For a customer, we cannot have new york in a column and alaska in another column since they are geographically far from each other.
but how data is synthesized from the original real data ?
By looking at and using the private data 🤣
One approach is to initialise a neural network with random junk as parameters and adjust these parameters to fit well the real-world data but not overfit. The output will be similar to the real-world data but not the same.
Another approach is to use classical statistical methods and extend them with an overfitted neural network. For example, an ARIMA model can generate artificial residuals, which the neural network can augment.
🙏🏼
I love crayons--- i love to eat them
Does your GF trust you?