Today’s post is directed to those who want to begin their journey with Data Science or are considering this possibility. In this post, I will explain: – What does working in Data Science involve? – What skills are needed? – How to acquire these skills? – How to get your first job. What does working […]
Advanced Feature Engineering: How to Maximize the Potential of Your Data?
Today, I’ll discuss a often underrated topic in the process of building machine learning models: advanced feature engineering. Many of us have probably heard of this concept. It’s usually covered during studies or in popular courses. However, from my experience, when we create practical ML projects, we often don’t give enough attention to properly preparing features […]
What’s currently happening in Poland in the field of AI?
AI-based Image Detection System in the Food Industry
Today’s food industry faces numerous challenges related to maintaining high product quality and minimizing production waste. Traditional quality control methods are often time-consuming and prone to human error, leading to inefficiencies and increased costs. In this article, we present a hypothetical case study illustrating how an advanced image detection system can revolutionize quality control in […]
How to Use AI in Business? What to Do in 2024?
The field of computer science known as “artificial intelligence” (AI) has been developing for decades. In recent years, we have witnessed several breakthrough moments, such as the creation of the AlphaZero model in 2017, which achieved grandmaster level in chess and Go, and the development of the Transformer architecture in the same year, which underpins […]
Everything You Need to Know About Recommender Systems
Do you ever wonder how algorithms work that select the ads you see? Or why do you get certain posts on social media? These tasks are handled by recommender systems. At COGITA, the company I managed, building such systems is our specialty. Our team created them for many large companies. Today, I would like to […]
6 reasons why interpretability of the model is important
Machine Learning has become a fundamental part of many companies’ data science efforts. But as models have gotten more complex, it can be difficult to know what is causing them to make certain predictions. That is why we observe fast increase of interpretability tools such as SHAP or DALEX. In this article, I will discuss some reasons why […]
10 Non-Obvious Things You Need to Log After Deploying Your Model in Production
Deploying machine learning models in a production environment is a significant challenge, often requiring as much effort as training the model itself. In this post, I will discuss one of several key aspects that need to be taken care of, which is logging all necessary information after deploying the model. When we are in the […]
Data Collection – Best Practices
Introduction Today, we will focus on the topic of data collection. This is an important aspect of the work of a data analyst or machine learning engineer. The models we can train and, most importantly, the correctness and usefulness of the entire solution depend on the type and amount of data we collect. Therefore, it […]
Planning Machine Learning Projects
Today, I would like to introduce you to the process of planning Machine Learning projects, as practiced in my company, COGITA. If you are involved in ML projects—whether as an analyst or a Data Scientist—you are likely either participating in this process or closely utilizing its outcomes. So, stick around till the end of this […]