Selecting the right loss function for a machine learning problem is a crucial step in the work of a data scientist. Here is a guide to getting started with them.
Metaheuristic optimization methods are an important part of the data science toolkit, and failing to understand them can result in significant wasted resources. This guide will help you get started.
Profiling is a crucial tool for data scientists to be able to analyze bottlenecks in a process and ensure smooth, efficient operation. This guide will help you get started with profiling tools in Python.
Journals are retracting more and more papers because they’re not by the authors they claim to be. We need better solutions to the problem, or we risk totally undermining public trust in research.
Governments around the world have no idea how well-developed their countries’ AI programs are coming along, but this knowledge might be crucial for everything from policymaking to fraud detection.
Classical computing isn’t going away, but quantum technology has the potential to disrupt many industries. It’s crucial to leverage the strengths of both to unlock quantum’s full potential.
When it comes to code, many scientists lack rigor. That carelessness could have disastrous effects on our ability to achieve reliable breakthroughs in a range of fields.
