Cifar-10 Classification using Keras Tutorial

Share on FacebookShare on Google+Tweet about this on TwitterShare on LinkedIn

The CIFAR-10 data set consists of 60000 32×32 color images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

Recognizing photos from the cifar-10 collection is one of the most common problems in the today’s  world of machine learning. I’m going to show you – step by step – how to build multi-layer artificial neural networks that will recognize images from a cifar-10  set with an accuracy of about 80% and visualize it.

If you want to check the whole project in your browser just open it in your browser using PLON –  our data science platform.

Continue reading

Share on FacebookShare on Google+Tweet about this on TwitterShare on LinkedIn

Weather data visualization for San Francisco Bay Area – a Python Pandas and Matplotlib Tutorial

Share on FacebookShare on Google+Tweet about this on TwitterShare on LinkedIn

Weather data is a great type of input when starting to learn tools and technologies for your data science skills. This project will introduce us to the basics of Pandas and Matplotlib Python libraries using data for San Francisco, San Mateo, Santa Clara, Mountain View and San Jose in California.

If you are interested in checking out the whole project you can run it  in your browser using our PLON Platform.

Continue reading

Share on FacebookShare on Google+Tweet about this on TwitterShare on LinkedIn