ABSTRACT: This paper explores the application of various time series prediction models to forecast graphical processing unit (GPU) utilization and power draw for machine learning applications using ...

We begin this tutorial to demonstrate how to harness TPOT to automate and optimize machine learning pipelines practically. By working directly in Google Colab, we ensure the setup is lightweight, ...

from sklearn.neighbors import KNeighborsClassifier import matplotlib.pyplot as plt from sklearn.metrics import accuracy_score from sklearn.base import clone from itertools import combinations ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

A new technical paper titled “VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation” was published by researchers at the University of Florida.

This notebook presents a complete machine learning pipeline designed to predict future outcomes based on historical data. It combines data preprocessing, exploration, modeling, evaluation, and ...

Sometimes it seems like the rules of programming are designed to make coding a chore. Here are 14 ways preprocessors can help make software development fun again. As much as we love them, programming ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...