Is it just another variation of the old Bayesian vs. frequentist debate? — Five years ago, everything in deep learning was about how to build new and more optimized models that would learn better from unstructured data. These efforts brought many research breakthroughs, pushing the boundaries of what is possible with neural networks. Slowly though, more and more people raised important criticism against…

Find the right technical career track for your profile with this simple overview — The field of artificial intelligence went through an incredible development. A clear sign of this is that while few years ago most companies were looking for only data scientists, today there is a boom of new roles in the industry. …

Can we abstract best practices to real design patterns yet? — According to its definition, a design pattern is a reusable solution to a commonly occurring problem. In software engineering, the concept dates back to 1987 when Beck and Cunningham started to apply it to programming. By the 2000s, design patterns — especially the SOLID design principles for OOP — were…

With automation in machine learning the field opens up and one may ask whether we need stats skills in the future — The world of automated machine learning Today, if you want to be a data scientist there are countless courses promising quick entrance to the field of data. For sure, nobody believes that one can learn in a matter of weeks the ins and outs of a complex field that requires hard skills in math/stats, software engineering…

Bogeyman tasks are best handled just like bogeymen in movies: by chunking. — I’m part of a cross-functional data science team and we are working on cutting edge AI-based products. When a product is built around AI it usually means a complex software architecture under the hood… and a backlog that is full of frightening bogeyman tasks. …

We asked ourselves this question many times. Here is the answer. — The prototypical situation that has been puzzling me for a while is the following: - We estimated 3 days for a task - Bob has been working on the task for 3 days already - On the daily scrum, he says that he just needs to take care of a couple more things…

Working on AI products — Whether it is retail, IoT, or marketing — data scientists face similar challenges. Some of these challenges are general to many technology areas, others are specific to AI, due to its unique way this field blurs the boundaries between state-of-the-art research and application development. …

tl;dr 1. data science practice is full of waste 2. explicit hypothesis testing helps to finetune ideas 3. communication is the key for integrating data scientists into the software development lifecycle I joined this field because of the excitement that we feel upon discovering new patterns in data. With time…

At first, I intended this as a post around stories and conclusions. But since I did not find any good tutorials online that would explain TDD from scratch to a working model, I’ve decided to make one myself to supplement this post. If you are familiar with TDD and would…