Publications by Dario Radečić
How to Make Stunning Interactive Maps with Python and Folium in Minutes
Data visualization can be tricky to do right. If you have the design skills of a domestic turkey, this article might save the day. Folium is a great library that does most of the heavy lifting for you. You only need to bring in the data. Today you’ll make your first interactive map, showing historical earthquakes near Fiji.You’ll see how eas...
4583 sym 12 img
LIME vs. SHAP: Which is Better for Explaining Machine Learning Models?
Do you want to use machine learning in production? Good luck explaining predictions to non-technical folks. LIME and SHAP can help.Explainable machine learning is a term any modern-day data scientist should know. Today you’ll see how the two most popular options compare – LIME and SHAP.If acronyms LIME and SHAP sound like a foreign language,...
4918 sym Python (1026 sym/8 pcs) 12 img
Introducing f-Strings - The Best Option for String Formatting in Python
There’s a bunch of ways to handle string formatting in Python. The most recent one is with f-Strings — an improvement from the previously used techniques. Today you’ll learn 3 key reasons why f-Strings are a way to go in 2021 and beyond.Here’s the complete list:Reason #1 — f-Strings look cleanReason #2 — f-Strings are fast...
3444 sym 10 img
Introducing f-Strings — The Best Option for String Formatting in Python
Meet Python’s most powerful string formatting option — and master it in 5 minutes or less. There’s a bunch of ways to handle string formatting in Python. The most recent one is with f-Strings — an improvement from the previously used techniques. Today you’ll learn 3 key reasons why f-Strings are a way to go in 2021 and beyond. ...
973 sym
Precision-Recall Curves: How to Easily Evaluate Machine Learning Models in No Time
Precision-Recall curves are a great way to visualize how your model predicts the positive class. You’ll learn it in-depth, and also go through hands-on examples in this article.As the name suggests, you can use precision-recall curves to visualize the relationship between precision and recall. This relationship is visualized for different proba...
6113 sym 18 img
How to Make Synthetic Datasets with Python: A Complete Guide for Machine Learning
A good dataset is difficult to find. Besides, sometimes you just want to make a point. Tedious loadings and preparations can be a bit much for these cases.Today you’ll learn how to make synthetic datasets with Python and Scikit-Learn – a fantastic machine learning library. You’ll also learn how to play around with noise, class balance, and ...
5432 sym 12 img
How to Make Synthetic Datasets with Python: A Complete Guide for Machine Learning
No dataset? No problem. Create your own in seconds with Python. A good dataset is difficult to find. Besides, sometimes you just want to make a point. Tedious loadings and preparations can be a bit much for these cases. Today you’ll learn how to make synthetic datasets with Python and Scikit-Learn — a fantastic machine learning library. ...
957 sym
3 Essential Ways to Calculate Feature Importance in Python
How can you find the most important features in your dataset? There’s a ton of techniques, and this article will teach you three any data scientist should know.After reading, you’ll know how to calculate feature importance in Python with only a couple of lines of code. You’ll also learn the prerequisites of these techniques – crucial to m...
7612 sym 12 img
Python Parallelism: Essential Guide to Speeding up Your Python Code in Minutes
Essential guide to multiprocessing with Python.Executing tasks sequentially might not be a good idea. If the input to the second task isn’t an output of the first task, you’re wasting both time and CPU.As you probably know, Python’s Global Interpreter Lock (GIL) mechanism allows only one thread to execute Python bytecode at once. It’s a s...
4230 sym Python (1486 sym/2 pcs) 6 img
Python Parallelism: Essential Guide to Speeding up Your Python Code in Minutes
Executing tasks sequentially might not be a good idea. If the input to the second task isn’t an output of the first task, you’re wasting both time and CPU.As you probably know, Python’s Global Interpreter Lock (GIL) mechanism allows only one thread to execute Python bytecode at once. It’s a severe limitation you can avoid by changing th...
4593 sym 4 img