Newsletter #1: Object Detection, LSTM, Neural Network Embedding, and more..
Hi, welcome to the 1st edition of the HubOfML newsletter! Today, I have loads of interesting links from the community on Object Detection, Neural Network Embedding, Recurrent Neural Network, and more.
Implement Object Detector From Scratch with Pytorch and YOLOv3
On paperspace's blog, Ayoosh Kathuria wrote a 5-series post on implementing real-time object detector in YOLO.
Train YOLO for Objection Detection in Pytorch using Custom Dataset
In this post, Chris Fotasche demonstrated how to train YOLO for object detection in Pytorch using your own dataset.
Understand How LSTM Networks work
Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning with many applications in speech recognition, time series anomaly detection, etc..
How Machines Read
On Floyhub's blog, Cathal Horan wrote an interesting post on how machines learn to read. Learn the concept of word tokenization.
Neural Network Embedding Explained
What do neural network embeddings mean? Will Koehrsen showed what neural network embeddings are and how they are learned.
Edge Detection Techniques - Image Processing with OpenCV
In this post, Samuel James explained techniques used in detecting edges with OpenCV for object segmentation.
MadeWithML - Platform
Need to showcase your cool machine learning projects? MadeWithML allows you to share your machine learning project with the community.