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JFrog Xray VS Scikit-learn

Compare JFrog Xray VS Scikit-learn and see what are their differences

JFrog Xray logo JFrog Xray

JFrog Xray is a universal software composition analysis (SCA) solution that natively integrates with Artifactory

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • JFrog Xray Landing page
    Landing page //
    2023-10-18

Xray is supported on the Cloud (SaaS) platform with an Enterprise X or Enterprise+ license, and on the Self-Hosted platform with a Pro X, Enterprise X , or Enterprise+ license.

  • Scikit-learn Landing page
    Landing page //
    2022-05-06

JFrog Xray videos

JFrog Xray - Universal Artifact Analysis

More videos:

  • Review - [Hands-on Lab]  - Manage Security and Compliance with JFrog Xray
  • Review - Introduction to JFrog Xray

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to JFrog Xray and Scikit-learn)
Code Analysis
100 100%
0% 0
Data Science And Machine Learning
Security
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare JFrog Xray and Scikit-learn

JFrog Xray Reviews

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Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

Based on our record, Scikit-learn seems to be a lot more popular than JFrog Xray. While we know about 29 links to Scikit-learn, we've tracked only 2 mentions of JFrog Xray. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

JFrog Xray mentions (2)

  • LOG4J HAS OFFICIALLY RUINED MY WEEKEND
    I was very thankful for JFrog Xray these past few days. It spotted some embedded cases that wouldn't have shown in a simple dependency graph. Source: over 2 years ago
  • So how's the Log4J vulnerability treating everyone's Friday evening?
    Services that were vulnerable were pretty easily identified with xray. We're really noisy about keeping 3rd party deps up-to-date, so we were able to take full advantage of log4j2.formatMsgNoLookups for like 90% of our services. All of the services involved had config management in place, so it took less than an hour once we had all the service owners in-the-loop to get the quick-fix rolled out everywhere. Bunch... Source: over 2 years ago

Scikit-learn mentions (29)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 20 days ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 4 months ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / about 1 year ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
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What are some alternatives?

When comparing JFrog Xray and Scikit-learn, you can also consider the following products

SonarQube - SonarQube, a core component of the Sonar solution, is an open source, self-managed tool that systematically helps developers and organizations deliver Clean Code.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Snyk - Snyk helps you use open source and stay secure. Continuously find and fix vulnerabilities for npm, Maven, NuGet, RubyGems, PyPI and much more.

OpenCV - OpenCV is the world's biggest computer vision library

FlexNet Code Insight - FlexNet Code Insight is a single integrated solution for open source license compliance and security. Take control of your open source software management

NumPy - NumPy is the fundamental package for scientific computing with Python