Hey everyone! Today, I'll guide you through creating a boundless cloud storage solution on Telegram using TeleDrive. This open-source project is a game-changer, offering functionalities like Google Drive/OneDrive via the Telegram API.
Open data *
The data will be free!
Do you need to produce satellite interferometry results for your work or study? Or should you find the way to process terabytes of radar data on your common laptop? Maybe you aren't confident about the installation and usage of the required software. Fortunately, there is the next generation of satellite interferometry products available for you. Beginners can build the results easily and advanced users might work on huge datasets. Open Source software PyGMTSAR is available on GitHub for developers and on DockerHub for advanced users and on Google Colab for everyone. This is the cloud-ready product, and it works the same as do you run it locally on your old laptop as on powerful cloud servers.
Before you is an article guide to open data sets for machine learning. In it, I, for a start, will collect a selection of interesting and fresh (relatively) datasets. And as a bonus, at the end of the article, I will attach useful links on independent search of datasets.
Less words, more data.
A selection of datasets for machine learning:
- Data deaths and battles from the game of thrones — This data set combines three data sources, each based on information from a series of books.
- Global Terrorism Database — Over 180,000 terrorist attacks worldwide, 1970-2017.
- Bitcoin, historical data — Bitcoin data with an interval of 1 minute from selected exchanges, January 2012 — March 2019
Couple of years ago my team (compliance in one of Swiss banks) and I had an interesting task to implement — we had to generate a huge random graph of financial transactions between clients, companies and ATMs. Moreover, we wanted this graph to contain some money-laundering and other financial crime patterns alongside with nodes description such as names, addresses, currencies etc. Obviously, all data should be randomly generated from scratch as long as we could not use any real data for obvious reasons.
As a solution we wrote a generator that I’d love to share with you. This article explains why we needed it and how this generator is working, but if you don’t want to read and want to try it on your own here is the code: https://github.com/MGrin/transactions-graph-generator. I hope that our experience will be helpful to any of you.
One of the main challenges is to open the mind of managers and engineers for using FOSS (Free & Open Source Software) properly. Because we have a lot of them, we have tried to use GIFs for answer the most common questions.