Through my example, I would like to show how I tripled my monthly income in 1 year as a data scientist. And how I made it 5x in 3 years. Introduction Most importantly, set a goal, why do you want to earn more? If you have a goal that motivates you…

Due to the great response, I was creating this. I have already described in one of my last article, how Pycaret helps me greatly to quickly building and prototyping the machine learning model. MLOps and low code machine learning are among the TOP topics of 2023. Now I would like to write on the MLOPS part because machine learning algorithm development is only half of the whole process! The second half is deployment, operation, monitoring, and maintenance. MLFlow gives excellent assistance in this! This is because MLFlow can work well with scikit-learn, Tensorflow, Pytorch, Keras, LightGBM, XGBoost, etc.

I am in the fortunate position to have not worked exclusively on experimental machine learning models, so many of my models often went into production, and the client began to generate profit. …

If you deal with building machine learning algorithms or managing them, you know well that creating a machine learning algorithm is a time-consuming task. You spend a lot of time with exploratory data analysis, data preparation, experimenting with different machine learning algorithms, optimizing them, and evaluating the results. …

If you are a professional and/or manager who has already encountered a machine learning model, you are well aware that building a machine learning algorithm is not an easy task. This statement is especially true if you work on real (not generated, not cleaned) data. …

Maybe this will be divisive and, moreover, it won’t be about artificial intelligence, like most of my articles. Still, I feel it is important to write about it. I’ll say it upfront, I’ll be subjective. The ego is often seen as a good thing, especially in business. Those with big…

To write production-ready code in Python, it is important to understand the importance of code modularization, following PEP8 style guidelines, using meaningful variable, class, and function names, organizing your code, and writing thorough documentation. Jupyter notebooks are great for exploratory data analysis and creating machine learning models, but in order…

Healthcare Expert Systems are (among others) used for medical diagnosis, and for identifying diseases. One of the most important advantages is that Expert Systems can consider more facts than a human. Expert Systems can be applied for medical treatment as well, for example, blood pressure control. The performance of Expert…

Do you know the difference between these senior data scientist roles? One of my students asked me what the difference is between a lead data scientist, principal data scientist, and chief data scientist. There are many contradictions about these roles on the Internet. This is no accident, because there is often a lot of overlap between these roles, on the other…