Monthly Archives: August 2017

DevDay DevConf is my favourite day! Potentially…

The first programming conference I fell in love was DevDay. It really opened my eyes when I went there for the first time in 2012 and it never failed to satisfy – I wrote about it multiple times. DevDay won’t be organized this year, or maybe even won’t be organized, period. But don’t worry – Michał and Rafał (together with other awesome people) are starting a new conference. I invite you to DevConf!

DevConf logo

I sent two talks for the CFP and both have been accepted. So I’m super happy, and also a bit stressed – this is going to be the first time I’m doing two talks at the same conference. Both new. Challenge accepted!

The first talk will be related to my growing in recent years interested in Machine Learning. I’ll try to explain basics of the technicalities of training and evaluating ML models in approachable ways. You’re probably gonna be disappointed how easy it is to get a relatively good working model. I hope to get you interested enough, that you won’t surrender when the first obstacles show up.

The second talk will be about my other fascination. How computers actually work? I’ll start with what most programmers know the best these days – one of the high-level programming languages. From there I’ll explore what lays beneath, what layers built up over last few decades. We’re standing on arms of the giants of the past and it’s a good thing to appreciate it.

DevConf is held on 13-15th September in Kraków, Poland. It’s less than a 2hrs flight from most places in Europe. One day of workshop and two days of three tracks talks for very affordable price. Make sure you stay for the weekend – traditionally we have a lot of fun there also after the conference. Register here! Hope to see you there!

Weekly Machine Learning drop #13

I’ve become more and more interested in machine learning during last year. This is my way of collecting and sharing interesting reads on the topic I stumble upon. I publish those posts every Friday. They are divided into few categories and the format is constantly evolving.


In this part, I share interesting news from machine learning and artificial intelligence world. Those are mostly not very scientific articles about applications, predictions and controversies around ML.

Amazon’s move signals end of line for many cashiers
The recent Amazon’s acquisition of Whole Foods is another step for the company to dominate retail. When you put that together with their Amazon Go experiment, you may start thinking how grocery stores will look in the future.

Mars robot makes decisions on its own
NASA scientists installed 20’000 lines of code on the Mars Rover Curiosity to give it some intelligence. Now it can recognize which rocks are worth closer look, instead of beaming laser at any rock found.

Artificial intelligence beat human player in Dota 2
Another game with a set of complicated rules and a nonlinear way to win was beaten by an algorithm. This time it was a solution by Open AI, using solution based on reinforced learning.


DeepMind and Blizzard open Starcraft II as an AI research environment
On a similar topic – now Starcraft II also has an available platform for AI experiments. It contains, among others, an API and big (and constantly growing) set of recorded anonymized gameplays. The release contains also an open source version of DeepMind’s toolkit and access to mini games, that will allow training agents for specific tasks.

How Machine Learning is transforming drug creation
Machine learning algorithms that are good at pattern recognition, can go through new and existing genetic and medical information to find unknown previously connections, which will allow creating more targeted medication.

Tensorflow 1.3 released
The previous week, a new version of Tensorflow was released. Click through, to see the list of features and improvements.

Learning materials

This week I wanted to share with you some repositories with Tensorflow best practices and new Deep Learning course by Andrew Ng. 

Tensorflow tutorials
Speaking of Tensorflow, this GitHub repository contains a bunch of tutorials, that are simple and easy to use and grasp basics of the library.

Tensorflow best practices
And this repository contains a bunch of good practices while developing with Tensorflow.

New Deep Learning specialization from Andrew Ng
After his recent departure from Baidu and forming, there is more news from Andrew Ng. He recently published new Coursera specialization focusing on Neural Networks and Deep Learning. Many people started their adventures in Machine Learning with his previous Coursera course, and this is definitely a great continuation. I’m in the 3rd week of the first course and with a clear conscience, I can recommend it to you.

Also recently, Andrew raised $150M venture capital fund to invest in AI.

This is it for today, thanks for reading. If you liked the post, let me know and please check other parts of the series.