Flipboard

FEBRUARY 13, 2023

Table of Contents Building a Dataset for Triplet Loss with Keras and TensorFlow Labeled Faces in the Wild Dataset Configuring Your Development Environment Having Problems Configuring Your Development Environment? Specifically, we will build a dataset for training our Siamese network-based recognition model.

Data Pipeline 106

Data Pipeline Deep Learning Deep Learning Python 106

Mlearning.ai

JUNE 8, 2023

Intuitively, think when you compare if two things are similar to each other, you want to represent the two things (text, image, video, audio or ideally anything that can be digitized) as two points and then find how close they are. To enable semantic search, we need something called embedding/vector/vector embedding. using its Spectrogram ).

Machine Learning 52

Machine Learning Machine Learning Clustering Database 52

The MLOps Blog

JANUARY 5, 2023

All the mobile phones now have this functionality that they can recognize you based on the camera feed or the face camera, and essentially a similar thing we are trying to build for animals, where tracking animals becomes more important. When you search with an image, it’s very hard to get the intent. Sabine: Hello, everybody.

Machine Learning 52

Machine Learning Machine Learning Database ML 52