MLCon Conference in Berlin: Unveiling the Latest Trends and Insights in Machine Learning and AI
Discover the insights and takeaways from the MLCon conference in Berlin, where experts shared their knowledge on machine learning strategy, product development, and cutting-edge AI techniques. Gain valuable insights into the challenges and best practices in ML, and explore the practical applications of embeddings, federated learning, and more.Read More →
Mastering Data Science with ChatGPT: 10 practical use cases of how ChatGPT can help data scientists do more with less effort.
As a data scientist, you’re always looking for ways to improve the accuracy and efficiency of your models. With the advent of large language models like ChatGPT, you now have access to a powerful tool that can help you accomplish just that. ChatGPT is a state-of-the-art language model that isRead More →
How machine learning can be applied for fashion industry? Based on the Silky Coders example.
Today’s article is the solid proof that networking on conferences is really worth it. Joining InfoShare for the second time (you can read more about 2021 edition in my article from last year), I’ve decided to get out of my usual comfort zone a little and talk to as manyRead More →
5 reasons why you should take CS50 course regardless your programming skills level.
One of my main tasks of 2022 was to develop safe and open environment for Citizen Data Scientists to grow in my current workplace. For those who are not familiar with the concept, according to the most popular definition by Gartner, Citizen Data Scientist is a person who creates orRead More →
How to build data science apps easily? Introduction to Streamlit.
Have you ever wanted to build a frontend for your data science project? But perhaps did not because of the extensive time needed to code the web app or intimidated by Shiny, Django or Flask? In this article, I will be showing you how you can build your first DataRead More →
How to choose your best IDE for Data Science?
Over the seven jewelled hills beyond the seventh fall, in the cottage of the seven dwarfs dwells the first programmer, and does her coding on a paper… Taking it seriously, before IDEs were introduced, programmers used text editors such as Notepad to write code. To save their progresss, they stored that code usingRead More →
A data scientist’s view on data literacy – what is it and why it should matter to you?
Long time, no see – definitely! I need to admit that I feel a little bit ashamed of my last activity here. Almost half of a year with neither blog post nor Instagram one. I was far more proud of myself in the previous year, but you know what? IRead More →
When is it worth for you team to build MLOps tool from scratch? Interview with Jakub Czakon, Chief Marketing Officer and Data Scientist from Neptune.ai.
Those who are not new to my website, probably will remember my article from several months ago when I experimented with Microsoft MLFlow. If not, I highly recommend you to start from there, where I have explained the MLOps concept in detail. As this topic is definitely not losing onRead More →
31 Days of Coding – spring challenge for R/Python programming skills improvement.
If you have ever tried to Google something like “What skills are necessary for a career in data science?”, you have probably been presented an extensive list of skills like statistics, mathematics, software development, machine learning, deep learning and many more. Each of those areas are disciplines in itself whichRead More →
Seeking for the right career path according to your talents with joint forces of data science and CliftonStrengths assessment.
Introduction Have you ever heard about the 34 CliftonStrengths Themes or Gallup Test? In short, the whole idea is about the fact that although people can learn skills, develop their knowledge and gain experiance, they can’t acquire talent. It’s innate. Each of us is unique and trying to achieve anythingRead More →