Software Alternatives, Accelerators & Startups

Keras VS Tiny Tiny RSS

Compare Keras VS Tiny Tiny RSS and see what are their differences

Keras logo Keras

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Tiny Tiny RSS logo Tiny Tiny RSS

Web-based news feed aggregator, designed to allow you to read news from any location, while feeling...
  • Keras Landing page
    Landing page //
    2023-10-16
  • Tiny Tiny RSS Landing page
    Landing page //
    2023-08-04

Keras videos

3. Deep Learning Tutorial (Tensorflow2.0, Keras & Python) - Movie Review Classification

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
  • Review - EKOR KERAS!! Review and Bike Check DARTMOOR HORNET 2018 // MTB Indonesia

Tiny Tiny RSS videos

Install Tiny Tiny RSS on Ubuntu Server

Category Popularity

0-100% (relative to Keras and Tiny Tiny RSS)
Data Science And Machine Learning
RSS Reader
0 0%
100% 100
Data Science Tools
100 100%
0% 0
RSS
0 0%
100% 100

User comments

Share your experience with using Keras and Tiny Tiny RSS. 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 Keras and Tiny Tiny RSS

Keras Reviews

10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
15 data science tools to consider using in 2021
Keras is a programming interface that enables data scientists to more easily access and use the TensorFlow machine learning platform. It's an open source deep learning API and framework written in Python that runs on top of TensorFlow and is now integrated into that platform. Keras previously supported multiple back ends but was tied exclusively to TensorFlow starting with...

Tiny Tiny RSS Reviews

19 Best Feedly Alternatives To Track Insights Across The Web
Tiny Tiny RSS enables you to follow your favorite sites, bloggers, personalities, etc. It needs patience to set up Tiny Tiny RSS, but it is effortless.

Social recommendations and mentions

Tiny Tiny RSS might be a bit more popular than Keras. We know about 42 links to it since March 2021 and only 32 links to Keras. 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.

Keras mentions (32)

  • Using Google Magika to build an AI-powered file type detector
    The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 6 days ago
  • My Favorite DevTools to Build AI/ML Applications!
    As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 2 months ago
  • Getting Started with Gemma Models
    After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / 2 months ago
  • How popular are libraries in each technology
    Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 12 months ago
  • Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
    I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
View more

Tiny Tiny RSS mentions (42)

  • Dark UX doesn't work in the long run
    I just want to vent here a bit: Feedly is the only app I ditched because I did not understand the interface. AT ALL. I tried multiple times, like really hard, over the course of 2-3 years, and all it delivered was a feeling of being insanely stupid. I started my attempts around 2012 (kind of around Google killing Reader). I could not understand if that app even deliver that same functionality as Reader, could not... - Source: Hacker News / 4 months ago
  • Ask HN: How do you organize your life?
    Write things down! All the weird things and ideas, put them into categories and write them down. This categories can also have a to do list. Use some kind of calendar. Try to not read the news on the internet too much. Use a RSS reader. Notes: Simplenote https://simplenote.com/ I use it with nvpy on Linux https://pypi.org/project/nvpy/ Calendar: https://www.rainlendar.net/ Tiny Tiny RSS Reader for selfhosting:... - Source: Hacker News / 8 months ago
  • Post Will Not Go Viral
    > I want to host my own RSS server though and then maybe use a native reader to view it, like an RSS of RSS feeds. I've been using Tiny Tiny RSS to do this for years. It works very well. https://tt-rss.org/. - Source: Hacker News / 9 months ago
  • Unleashing the Potential of RSS; Harnessing Its Benefits for Everyday Learning
    Tiny Tiny RSS (TT-RSS) https://tt-rss.org/ is a self-hosted, open-source RSS feed reader that provides a lightweight and customizable solution for managing and reading RSS feeds. It offers a simple web-based interface, allowing users to aggregate, organize, and access their favorite content from various sources in one centralized location. With its extensibility and robust feature set, TT-RSS offers a powerful... - Source: dev.to / 11 months ago
  • Reddit restored the last six months of my comments after I deleted them with shreddit. They also deleted everything older that I had saved.
    I would recommend Tiny Tiny RSS or FreshRSS as examples but you can use anything you want, there's plenty of them. Why would you want to pay for something like this? Source: 12 months ago
View more

What are some alternatives?

When comparing Keras and Tiny Tiny RSS, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Feedly - The content you need to accelerate your research, marketing, and sales.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Inoreader - Dive into your favorite content. The content reader for power users who want to save time.

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

NewsBlur - NewsBlur is a personal news reader that brings people together to talk about the world.