avatarDariusz Gross #DATAsculptor

Summary

The undefined website features a virtual reality gallery showcasing top stories and digital art from MLearning.ai, with a focus on machine learning applications and generative models.

Abstract

The undefined website is dedicated to presenting the "VR Machine Learning stories" gallery, which includes works from MLearning.ai's top writers. The gallery, named vRooML!, displays digital art and machine learning narratives in an immersive VR format. Visitors can explore stories on topics such as facial recognition systems adapted for face mask usage, the exploration of various generative models like VAEs and VQ-VAEs, and the process of datasculpting. The site also offers interactive experiences through VR and AR, allowing users to engage with the content in a dynamic way. Additionally, it provides links to related articles, membership options for exclusive content, and invites readers to follow the authors' social media profiles for ongoing updates.

Opinions

  • The author of the article expresses enthusiasm about the potential of machine learning in creating facial recognition systems that work even with face masks.
  • Wong Chow Mein highlights the importance of adapting facial recognition algorithms in the context of the COVID-19 pandemic and the widespread use of face masks.
  • Satyajit Kumar shares a personal journey of experimenting with different generative models, indicating a passion for the evolving field of deep learning and generative art.
  • The author encourages readers to engage with the content beyond the website, suggesting a belief in the value of community and continuous learning within the field of machine learning.
  • There is an endorsement for an AI service, ZAI.chat, presented as a cost-effective alternative to ChatGPT Plus (GPT-4), indicating a positive opinion about the service's value proposition.

VR Machine Learning stories

meet MLearning.ai TOP Writers

vRooML!

3rd gallery with the best MLearning.ai stories. vRoomL! is a space in which digital art is displayed (e.g Panna — DATAsculpture) , in our gallery we display also — MLstories in the form of images created with the help of machine learning. All the VRspace was generated by the MLearning.ai model.

A unique opportunity to meet MLearning.ai TOP Writers:

  1. Rebeca Sarai G. G.

2. Wong Chow Mein

3. Satyajit Kumar

vRooML! Rebeca Sarai G. G.

Build your own facial recognition system: To work even with a face mask!

In this project, now article, I create a facial recognition system from scratch with a Convolutional Neural Network(CNN) structure using Keras, to recognize me and my sister. Rebeca Sarai G. G.

vRooML! Wong Chow Mein

Facial mask overlay with OpenCV-dlib // Superimpose facemasks using OpenCV-dlib library

Face masks have been shown to be one of the best defense against the spread of COVID-19. However, this has also led to the failure of facial recognition algorithms which are built around facial features including nose, mouth and jawline. Before the global pandemic, facial recognition systems verify faces in two images by performing comparison measurements between different facial features detected. The wearing of a mask over a person’s nose, mouth and cheeks, has greatly reduced the information normally used to figure out his/her identity.Wong Chow Mein

vRooML! Satyajit Kumar

A Crash Course on VAEs, VQ-VAEs, and VAE-GANs

Over the past half-year, I have been experimenting with different generative models in deep learning, or more specifically, different types of VAEs. In short, the Variational AutoEncoder is a generative model capable of reproducing images, and along with that, spitting out the latent vector of the images which can be used to train other neural networks or latent space manipulation. With the vanilla or plain VAE, I have tried producing high-quality images from ImageNet, only to realize that it is just simply not capable of producing these types of images in that latent space (mostly because every output looked like a potato).Satyajit Kumar

Panna — DATAsculpture generated by MLearning.ai

The last stop of the vRooML! is the DATAsculpture generated by the machine learning model, you can read about the entire datasculpting process here.

Please visit the vRooML! viewer below. It enables to move freely around using mouse, touch manipulation, VR or AR. You are able to play and control 3D view. VR mode is enable the to see the model in Virtual Reality headsets or to insert the model within the real world via a mobile device (the AR mode).

thank you for reading, you may also enjoy some other articles:

all images in the story was generated by MLearning.ai

Machine Learning
Artificial Intelligence
Data Science
Technology
Art
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