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Unfiltered.news VS machine-learning in Python

Compare Unfiltered.news VS machine-learning in Python and see what are their differences

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Unfiltered.news logo Unfiltered.news

What the world is talking about, visualized graphically

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

Unfiltered.news features and specs

  • Global Perspective
    Unfiltered.news provides a worldwide view of news stories, helping users to see how different regions report on the same events.
  • Bias Reduction
    By aggregating news from multiple sources, the platform reduces the bias inherent in any single news outlet, offering a more balanced perspective.
  • Issue Awareness
    The tool highlights underreported stories and topics that might not be covered extensively in mainstream media, increasing awareness of a broader range of issues.
  • User-Friendly Interface
    The platform's visual and interactive interface makes it easy for users to explore and compare news stories from around the world.

Possible disadvantages of Unfiltered.news

  • Data Overload
    The abundance of information from various sources can be overwhelming and difficult to navigate for some users.
  • Source Reliability
    The quality and reliability of sources can vary, potentially including less reputable news outlets, which might affect the accuracy of information.
  • Language Barriers
    News stories from non-English sources may not be accessible to all users, limiting the understanding of global perspectives for those who do not speak multiple languages.
  • Limited Depth
    While providing a broad overview, the platform might lack the depth and detailed analysis that specialized or niche news sources offer.

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.

Analysis of Unfiltered.news

Overall verdict

  • Unfiltered.news is considered a valuable resource for those interested in diverse perspectives and comprehensive global coverage. It can be especially beneficial for users who wish to break out of their news echo chambers and explore stories that are underrepresented in their local news outlets.

Why this product is good

  • Unfiltered.news is a tool designed to provide a broader perspective on global news by highlighting stories that might not be widely covered in your local media. It allows users to explore news stories that are being reported in different countries, thus gaining a wider understanding of global events.

Recommended for

  • Journalists researching international perspectives
  • Students and educators interested in global studies
  • Individuals seeking diverse news sources
  • Anyone aiming to understand underreported stories around the world

Unfiltered.news videos

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Product Hunt Review E14 (Unfiltered.news, Sharethebus, Clect) by Cleveroad Inc.

machine-learning in Python videos

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Category Popularity

0-100% (relative to Unfiltered.news and machine-learning in Python)

Unfiltered.news

machine-learning in Python

News
100 100%
News
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Social Networks
100 100%
Social Networks
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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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.

Unfiltered.news mentions (0)

We have not tracked any mentions of Unfiltered.news yet. Tracking of Unfiltered.news recommendations started around Mar 2021.

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: over 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 Unfiltered.news and machine-learning in Python, you can also consider the following products

Google News - Comprehensive up-to-date news coverage, aggregated from sources all over the world by Google News.

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.

X (Twitter) - Connect with your friends and other fascinating people. Get in-the-moment updates on the things that interest you. And watch events unfold, in real time, from every angle.

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

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