- MNIST dataset, a collection of 70,000+ labeled digits, starting point of machine learning practice
- Beginner Machine Learning data
- Each image is 28 by 28 pixels so 784 data points per image
- Often used in Google Tensorflow demos
- sklearn provides this dataset too
- Inception-v3 pre-trained Inception-v3 model achieves state-of-the-art accuracy for recognizing general objects with 1000 classes, like "Zebra", "Dalmatian", and "Dishwasher"
- vgg19 image data
- What is VGG-16?"Since 2010, ImageNet has hosted an annual challenge where research teams present solutions to image classification and other tasks by training on the ImageNet dataset. ImageNet currently has millions of labeled images; it’s one of the largest high-quality image datasets in the world. The Visual Geometry group at the University of Oxford did really well in 2014 with two network architectures: VGG-16, a 16-layer convolutional Neural Network, and VGG-19, a 19-layer Convolutional Neural Network."
- 1000+ different objects in 1.3 million high resolution training images
- cornell movie dialog https://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html
Wednesday, October 11, 2017
Famous Machine Learning Datasets - Machine Learning Wiki
Neural networks are important for ML as well as artificial intelligence and deep learning. This Youtube channel explains NN in depth. Take a...
What is a domain name system (DNS)? How stuff works explains it in a very good graph I was very confused by the Wikipedia explanatio...
The bogus request from P2PU to hunt for HTML tags in real life has yielded a lot of good thoughts. My first impression was that this is stup...
Dilys Sun Got a question about web development dev bootcamps? Ask them here or @i_stanford Your question shall be answered by myself, othe...