Finally, it’s here! Today I will present the first version of the FELT Labs tool for federated learning on Ocean protocol. This one definitely took longer than we expected. However, this article isn’t about all bugs we had to overcome. This article should act as a step-by-step guide on how to use it.
So you wrote your smart contracts tested them locally and now comes the big time—deployment to a real network. This can be quite scary as a small mistake can lead to big losses. Therefore it’s always a good idea to start with test nets and then move to live. In this short tutorial, I will describe the steps you need to take to deploy your smart contracts to the Polygon network without any issues.
Please follow me on Medium: @breta.hajek if you want to read this article:
FELToken with Ocean Protocol, Future and Integrations
Recently I started working on my new project: FELToken, creating decentralized privacy-preserving machine learning (using smart contracts and blockchain). I am planning to post weekly tutorials and stories from development.
This website will remain active, but there will be more content published on Medium.
The guide into why and how to start with TypeScript
This is purely based on my personal experience over the past two months when I started using TypeScript for the first time. At the end of the article, I will share also how to configure your project for TypeScript to get you started. You will see that the initial configuration is the only hard part about TypeScript.
In this tutorial, I will go over my current approach for hosting my decentralized application (dapp) code for free with GitHub Pages. This proves to be a great option for getting your dapp up and running quickly and for free. I will also show how to set up GitHub actions CI so that code changes are automatically deployed. I will use React as a frontend framework, but this can be easily changed.
Pre-trained models play important role in the progress of machine learning. Object detection models depend on pre-trained image networks. Fine-tuning of pre-trained models is often a preferred option over training models from scratch. So what if somebody could hide ransomware or some spyware—stealing your precious data—into one of these models? What if you could write ransomware directly in TensorFlow? This article will go over details of what’s possible.
Truth be told, I compete a lot. This time I participated in the CSAW HackML competition. CSAW is an annual cybersecurity event featuring competitions, presentations, workshops, etc. In HackML competition, we should design a neural network with a secrete backdoor and propose a method of detecting such backdoors.
You may or may not heard about memory techniques―using memory palaces to memorize a lot of information quickly. However, most of the articles deal with memorizing numbers, cards or lists of random objects. As accurate as this information is, it is often presented in a very unpractical way. In this article, I would like to describe how I use these techniques in my student’s life.
“You can memorize
a deck of cards,
so what?!”
This will be a quick tip on how to use combine_adversarial_loss in tf.contrib.gan.estimator.GANEstimator. In my latest projects, I have been using TensorFlow estimators. Estimators allow you to focus more on creating models and wraps the whole training (including saving, exporting, and putting a model in production) into few lines. Recently, I experienced the limits of estimators when I wanted to train a generative adversarial network (GAN) with a combined adversarial loss. In this article, I will show you a little trick how to do that.
Recently, I went through my old Windows setup and I realized how many editors I tried over past years. I was always looking for something that will ultimately improve my programming experience. The obvious answer is that nothing really does. All the fancy futures provided by different editors often turn out to be unnecessary during regular development. Right now I stick to my favourite Spacemacs with Vim keybindings. (and sometimes Visual Studio Code).
Programming editors I used.
Well, well, well…
It has been some time since I wrote the last blog post. And I won’t make the same mistake promising that I will write more. Not like there is nothing happening in my life. I recently finished two online courses and I am going to give you a review of them. Rather there is happening so many things that I just have to put my focus into different things. Or I am just being lazy – pick your excuse.
Here is a quick review of Cryptography and AI online courses
“The Intel International Science and Engineering Fair (Intel ISEF) is the world’s largest international pre-college science competition.”
I am not sure if it is the largest pre-college competition, but with the hundreds of students from around the world, the atmosphere of the whole event is simply amazing. At Intel ISEF students get a chance to present their science projects and meet each other. For many people, including me, attending ISEF is a pretty big deal. The prizes are high, the competition has a good recognition, and you just hope that all the hard work finally pays off.