In this blog post you will learn how you can turn your website into a serverless website.
My Approach to Natas Level 11 (a Web Security Game)
Recently I came across the concept of CTF (Capture The Flag) which are security competitions and I really enjoy these kinds of the competitions. One of my favorites is OverTheWire. They provide different kinds of games and one of these is Natas, in which you need to attack a webserver. The concept is simple: the creator of the game designs a normal functioning webserver and intentionally puts in a bug. We need to find a password in order to get to the next level which can be found by exploiting the bug. That’s why it is called Capture The Flag. So lets get started!
Hands-on: Creating Neural Networks using Chainer
This tutorial is a practical guide which helps you to create Neural Networks in Chainer. The focus is not on the architecture of the networks (more about Neural Network architectures is found in this post), but it is focused on creating a pipeline. We will take a simple classification problem as an example and create the pipeline for training and testing the network and how to evaluate the model.
The Lessons I Learned in Cryptoland
There are many cryptocurrencies which you can buy. Where should you even start? In this article, I will share the lessons I have learned over the past years with you. I think it is important to share these insights with you, since there are a lot of people out in cryptoland waiting for your money and they will tamper with your thoughts. If you have any important lesson, please share it and it will be added to this article.
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Create a Character-based Seq2Seq model using Python and Tensorflow
In this article, I will share my findings on creating a character-based Sequence-to-Sequence model (Seq2Seq) and I will share some of the results I have found. All of this is just a tiny part of my Master Thesis and it took quite a while for me to learn how to convert the theoretical concepts into practical models. I will also share the lessons that I have learned.