Dataconomy

APRIL 8, 2025

These models help analysts understand relationships within data and make predictions based on past observations. Among the most significant models are non-linear models, support vector machines, and linear regression. These practices contribute to the reliability and effectiveness of data-driven insights.

Data Science 91

Data Science Support Vector Machines Data Scientist Data Visualization 91

Data Science Dojo

MAY 1, 2023

It supports large, multi-dimensional arrays and matrices of numerical data, as well as a large library of mathematical functions to operate on these arrays. The package is particularly useful for performing mathematical operations on large datasets and is widely used in machine learning, data analysis, and scientific computing.

Python 328

Python Data Science Machine Learning Machine Learning 328

Data Science Dojo

MAY 1, 2023

It supports large, multi-dimensional arrays and matrices of numerical data, as well as a large library of mathematical functions to operate on these arrays. The package is particularly useful for performing mathematical operations on large datasets and is widely used in machine learning, data analysis, and scientific computing.

Python 195

Python Data Science Machine Learning Machine Learning 195

ODSC - Open Data Science

JANUARY 5, 2024

Without this library, data analysis wouldn’t be the same without pandas, which reign supreme with its powerful data structures and manipulation tools. Pandas provides a fast and efficient way to work with tabular data. It is widely used in data science, finance, and other fields where data analysis is essential.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

Dataconomy

AUGUST 9, 2023

How could machine learning be used in network traffic analysis? Machine learning is fundamentally changing the landscape of network traffic analysis by automating the process of data analysis and interpretation.

Machine Learning 91

Machine Learning Machine Learning ML ML 91

IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms —predict categorical output variables (e.g., “junk” or “not junk”) by labeling pieces of input data. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

IBM Journey to AI blog

DECEMBER 19, 2023

Machine learning algorithms for unstructured data include: K-means: This algorithm is a data visualization technique that processes data points through a mathematical equation with the intention of clustering similar data points.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82