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Athena News API VS machine-learning in Python

Compare Athena News API VS machine-learning in Python and see what are their differences

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Athena News API logo Athena News API

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

machine-learning in Python logo machine-learning in Python

Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.
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

  • machine-learning in Python Landing page
    Landing page //
    2020-01-13

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

machine-learning in Python

Website
machinelearningmastery.com
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.

machine-learning in Python features and specs

  • Ease of Use
    Python has a simple and clean syntax, which makes it accessible for beginners and efficient for experienced developers to implement fundamental concepts of machine learning quickly.
  • Rich Ecosystem
    Python boasts a vast collection of libraries and frameworks such as scikit-learn, TensorFlow, and PyTorch that provide extensive functionalities for machine learning tasks.
  • Community Support
    Python has a large and active community that contributes to continuous improvement, support, and readily available resources like tutorials, forums, and documentation for troubleshooting.
  • Integration Capabilities
    Python can easily integrate with other languages and technologies, enabling seamless deployment of machine learning models in diverse environments.
  • Visualization Tools
    Python supports various visualization libraries like Matplotlib and Seaborn which are crucial for data analysis and understanding the performance of machine learning models.

Possible disadvantages of machine-learning in Python

  • Performance Limitations
    Python is an interpreted language and can be slower compared to compiled languages like C++ or Java, which might be a consideration for performance-intensive tasks.
  • Global Interpreter Lock (GIL)
    The GIL in Python can be a bottleneck for multi-threaded applications, limiting parallel execution and performance in CPU-bound machine learning tasks.
  • Dependency Management
    Managing dependencies can be complex in Python projects, especially when handling different versions of libraries required for specific machine learning projects.
  • Memory Consumption
    Python can require more memory for large datasets when compared with more memory-efficient languages, which might affect scalability and the ability to process very large datasets.

Category Popularity

0-100% (relative to Athena News API and machine-learning in Python)

Athena News API

machine-learning in Python

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

User comments

Share your experience with using Athena News API and machine-learning in Python. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, machine-learning in Python seems to be more popular. It has been mentiond 7 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.

machine-learning in Python mentions (7)

  • Data science and cybersecurity with python project
    After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: about 2 years ago
  • Ask HN: How can I learn ML in 6 months as a teenager?
    Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / over 2 years ago
  • Are these CS courses enough CS knowledge for ML engineer?
    MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: about 3 years ago
  • how to do i train an AI
    Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 3 years ago
  • Python Data Science Project Ideas (+References)
    Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 3 years ago
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What are some alternatives?

When comparing Athena News API and machine-learning in Python, you can also consider the following products

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

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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

BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.

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

Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.

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