Best Data Science Tools in 2024
Introduction Data science has undergone a significant transformation in recent years, driven by the emergence of sophisticated tools — particularly machine learning, artificial intelligence, and open-source software. What was once an extremely specialized domain requiring access to powerful, expensive computing resources has become more accessible to a broad spectrum of users. Additionally, practitioners no longer require extensive […]
Python 3.8 Reaches End-Of-Life
As part of our commitment to maintaining up-to-date and secure Python environments, Anaconda is announcing the end of support for Python 3.8 in our main channel of the Anaconda Distribution. This decision aligns with the upstream CPython support cycle for Python minor versions. Key Dates End of Support Date: October 31, 2024 Last Security Fix: […]
The Ultimate Guide to Open-Source Security with Python and R
Open-source software (OSS) has emerged as a powerful force, revolutionizing the way organizations approach data science and machine learning development, collaboration, and innovation. With a wealth of benefits including transparency, cost-effectiveness, and a vast community of contributors, open-source software has garnered widespread adoption across industries. However, open-source security brings challenges and threats every day that […]
Introducing Evaluations Driven Development: Building AI Assistants That Deliver Real Value
At Anaconda, we’ve developed a rigorous new approach to AI development called Evaluations Driven Development (EDD). By continuously testing AI models using real-world cases and user feedback, EDD enables us to create AI assistants that are reliable, relevant, and truly impactful for users. Our Anaconda Assistant, an AI coding companion for data scientists, exemplifies the […]
New Release: Anaconda Distribution 2024.06
We are excited to announce the 2024.06 release of Anaconda Distribution, Anaconda’s free data science distribution installer, which includes: Python – the most widely used programming language for data science and machine learning conda – the open-source, cross-platform package and environment manager Anaconda Navigator – our desktop application, built on conda, that enables you to […]
Anaconda Joins IBM, Meta, and More in AI Alliance to Advance Open-Source AI Adoption, Safety, and Accessibility
February 8, 2024 – Anaconda Inc., the leading provider of the world’s most popular source code for AI, machine learning, and data science, today announced its membership in the AI Alliance, an international community of developers, researchers, and organizations dedicated to promoting open, safe, and responsible artificial intelligence (AI). Joined by industry leaders like IBM, […]
Visual Data Analysis with Python in Excel: Using Histograms
Many types of professionals analyze data using different skills. Microsoft Excel users analyze data using Excel PivotTables, while data scientists use statistical and machine learning models. Despite this diversity, Excel users, data scientists, and statisticians share one universal data analysis skill: visually analyzing data. This is the first in a five-part blog series introducing you […]
Anaconda Repo Updates
Latest changes to Anaconda’s package repositories (repo.anaconda.com, also known as “defaults”). Python Versions currently supported in the repository: Python 3.8 Python 3.9 Python 3.10 Python 3.11 Python 3.12 COMING SOON! 2023-12-18: Miniconda 23.11.0 Miniconda3 23.11.0 is now available to download. This new release comes with updated conda 23.11.0 and conda-libmamaba-solver 23.12.0. In addition, python 3.8 […]
One-Third Identify as LGBTQIA+ in State of Data Science Survey Results
October is LGBT history month, and while we look back at the huge strides made so far, it’s important to remember just how much is left to be done. Founded by a Missouri teacher in 1994, LGBT history month focuses on teaching queer history and continuing to shine a light on issues of diversity, equity, […]
Introducing Pandata: The Scalable Open-Source Analysis Stack
It is no secret that every scientific, engineering, or analytical discipline has its own specialized computing needs. In fact, many of these disciplines have developed entirely separate sets of tools for working with data, covering data storage, reading, processing, plotting, analysis, modeling, and exploration. Unfortunately, most of these existing stacks are based on outdated architectures […]
