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Model Link: https://nyp.ai
Brief Description: My model is a Rock, Paper and Scissors model that can detect which one of the three you are holding up!
Group Members: Karthik, Wen Bing, Amelia, Prakhar, Shawn, Jay

(This is a sample post under the TeachableMachine Model Link.)

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Group members: mr ping junxi Underidoderidoderiododeridoo javierr

Link: https://teachablemachine.withgoogle.com/models/zdBmaprp9/

Description: I have a hard time differentiating between Ronaldo and Cat

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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Slides Link: https://slides.google.com
Group Members: Karthik, Wen Bing, Amelia, Prakhar, Shawn, Jay

Poster Name: Prakhar

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https://teachablemachine.withgoogle.com/models/cJGrRsUmx/

Detect emotions based on ur expressions! 😱😱😱🔥🔥
Grp members: Zhi Yang, Andrew, Joel, Jasper, Justin

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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Slides Link:https://docs.google.com/presentation/d/1TVtsPbTbGgKbZb062r6GWvaH4oSUL--qaRx4AKyusqE/edit?usp=sharing

Group members: Zhi Yang, Andrew, Joel, Justin , Jasper

Poster Name: Joel

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grp member : swegboi, andrey, rancid, wongjaeno

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.

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https://teachablemachine.withgoogle.com/models/cXnR9j0Sh/

Group member: !null 1wist bananahead infamousMP Kendrick

Description: An AI model for cat-vs-dog detection is created using convolutional neural networks (CNNs). It is trained on a dataset of labeled images containing cats and dogs. The model learns to extract features and patterns from the images that differentiate between the two classes. The training process adjusts the model's parameters to minimize prediction errors. After evaluation on a separate dataset, the model is fine-tuned and optimized for improved performance. Once deployed, the model can process new images and accurately predict whether they contain a cat or a dog, leveraging its ability to recognize spatial features and patterns in images.

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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Determine whether a hand is showing thumbs up, thumbs down, or 'ok' sign.

Disclaimer: It only works very well if you only show your hand to the webcam

https://teachablemachine.withgoogle.com/models/KR9I1Ytl6/

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Model Link: https://teachablemachine.withgoogle.com/models/q3avSzEGf/
Brief Description: The model is based on $2, $5, and $10 dollar notes model that can detect which one of the three notes you are showing to the camera.
Group Members: Jay, Revus, Chloe, 3lynn, ky

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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Group Members: Joseph, Terrence, Ayura, An Qi, shiqi
Mentor: Jay Krish
https://teachablemachine.withgoogle.com/models/SbkYGqxYQ/

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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model link: https://teachablemachine.withgoogle.com/models/D4fstJS4F/
Brief Description:  My model can detect 5 different types of among us models when we show a pic of an among us ( black, white, yellow,green, and red)
Group members: Andy, Tian Hui , Junming , Wen Bing, Callum, Jing Khai,

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required.