I’ve spent the last few weeks configuring and developing IntelliJ plugins. This post is a quick summary of what I’ve learned so far. Some of the things I discuss in this post are not documented and base on my own investigation and debugging of various IntelliJ IDE mechanisms.
The course named “Machine Learning”, created by Professor Andrew Ng is one of the most popular courses on the Internet. Since its first publication, more than 8 million learners have signed up. Initially, the course was available on YouTube but after some time it has been moved to Coursera.
There was a very annoying bug. On each of post pages the Disqus plugin, which is responsible for loading comments section, used to show same comments for all of the posts. It took me a few hours of debugging to find out where the issue was.
I would like to thank everyone of you who supported me during this 3 months journey. Your tips gave me the strength that helped me to create better content and write better code. If you are interested in more details – read more. Thank you!
This is my last technical post in the Get Noticed 2017 category. The last one will be a quick summary of the last three months. Soo…it was a very long week. I didn’t do too much but there was a big progress in using the neural network in the Aksesi Proxy Application.
The neural network requires to train it before using. We are expected to provide sets od date that will be used for the purpose of learning. It means that we need a generator which will create gestures in a form readable by the NN.
Today we are taking part in Rzeszów Hackathon. Our team consists of 4 members – Bartek, Vlad, Michał and me. By the way, you should know Bartek and Michał from the post Pekaton – 24-godzinny hackaton. At the beginning, I want to mention that in this post I’m not going to reveal project’s main idea and implementation details. This is because some of ours competitors may read it (good luck guys ;)). Maybe we will share a few hints. Since the start, this post will be updated every hour, at least I hope so.
It’s time to start implementing support for recognizing gestures with neural networks. As I mentioned in the previous post, I had seen some potential problems. After two days of work, I can finally write that those problems are solved. In this post, I’ll describe how I solved the problem of different drawing area location. In the second paragraph, I’m going to describe implemented resizing strategy. At the end, in the third part, I’ll write some words about flattering gestures and values normalization.
In the previous post, I mentioned that the next thing developed in the Aksesi project will be a management console. After submitting that post, I realized that it is going to be another boring application with 90% of its logic encapsulated in CRUD operations. When I decided to take part in Get Noticed competition, my main goal was to learn new things. To make a long story short. The next step won’t be management console; the next step will be gesture recognition with Artificial Intelligence usage.
This post is divided into two main parts. The technical part will be connected with adding custom headers passed to an authentication endpoint. In the second part, I’m going to describe plans for next few weeks.