Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Python libraries handle real business tasks like APIs, data analysis, and machine learning at scaleUsing ready-made libraries ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

Microplastics (MPs) pose a growing threat to marine ecosystems, yet their accumulation in tropical ascidians remains understudied. This study investigated MPs in the digestive tract of Phallusia nigra ...

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...

Python with libraries Numpy, Pandas, Scipy, Statsmodels, Matplotlib, and Seaborn was used for statistical analysis and graphing. The LLM Grok 3 was used for some code generation, and outputs were ...

What’s the best way to bring your AI agent ideas to life: a sleek, no-code platform or the raw power of a programming language? It’s a question that sparks debate among developers, entrepreneurs, and ...

Abstract: Compared to other programming languages (e.g., Java), Python has more idioms to make Python code concise and efficient. Although Pythonic idioms are well accepted in the Python community, ...

[~/regression-testing]$ hyperfine --warmup=10 "cp313/python/bin/python3.13 dicttest.py" "cp314/python/bin/python3.14 dicttest.py" Benchmark 1: cp313/python/bin ...

Sometimes, reading Python code just isn’t enough to see what’s really going on. You can stare at lines for hours and still miss how variables change, or why a bug keeps popping up. That’s where a ...

Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and ...