Software Alternatives, Accelerators & Startups
Register | Login

Athena News API VS Scikit-learn

Compare Athena News API VS Scikit-learn and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Athena News API logo Athena News API

Powering data-driven insights from the world’s headlines.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Not present

Athena simplifies capturing and structuring news for analysis by handling all data preprocessing for you, providing structured data from over 50,000 global sources. Features include 15+ years of historical data, sentiment analysis, entity extraction, topic analysis, and vector embeddings, all designed to help users skip the time-consuming steps of data preparation.

Whether you’re analyzing media trends, improving machine learning models, or studying financial markets, Athena offers detailed data at an accessible price point. It integrates easily through a REST API, providing ready-to-use data for uncovering trends, relationships, and patterns faster and more efficiently

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

Athena News API

Website
runathena.com
Pricing URL
Official Athena News API Pricing
$ Details
freemium $14.99 / Monthly
Release Date
2024 December
Startup details
Country
United States
State
Delaware
City
Dover
Founder(s)
Matthew F.
Employees
1 - 9
Edit details

Scikit-learn

Website
scikit-learn.org
Pricing URL
-
$ Details
Release Date
-
Edit details

Athena News API features and specs

  • 15+ Years of Historical Data
    Analyze trends with nearly two decades of historical articles spanning 50,000 global sources.
  • Sentiment Analysis
    Gain an accurate picture of changing market trends and customer preferences with sentiment analysis.
  • Entity Extraction and Linking
    Save time as advanced language models automatically identify key entities and link them to real-world knowledge bases.
  • Entity Relationships
    Easily understand connections between entities, providing deeper insights and a clearer context for your analysis.
  • Topic Analysis
    Uncover the main themes in articles with automated topic analysis, helping you focus on what matters most without manual effort.
  • Vector Embeddings
    Leverage article data in machine-learning and search applications with pre-generated vector embeddings using off-the-shelf models.

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Athena News API videos

No Athena News API videos yet. You could help us improve this page by suggesting one.

Add video

Scikit-learn videos

+ Add

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 Athena News API and Scikit-learn)

Athena News API

Scikit-learn

APIs
100 100%
APIs
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
News
100 100%
News
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Athena News API and Scikit-learn. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Athena News API Reviews

We have no reviews of Athena News API yet.
Be the first one to post

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...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 31 times since March 2021. 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.

Athena News API mentions (0)

We have not tracked any mentions of Athena News API yet. Tracking of Athena News API recommendations started around Dec 2024.

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • 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 / 11 months 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 / about 1 year 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 / almost 2 years ago
View more

What are some alternatives?

When comparing Athena News API and Scikit-learn, you can also consider the following products

Perigon - We are a news intelligence platform built to improve the quality of information that you consume.

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

News API - Get live headlines from a range of news sources

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

Stock News API - Get relevant stock news from companies in the stock market.

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

Loading...