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Learn X in Y minutes VS Keras

Compare Learn X in Y minutes VS Keras and see what are their differences

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Learn X in Y minutes logo Learn X in Y minutes

LearnXinYminutes isn’t a good way to learn your first programming language, but it’s a great way to...

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.
  • Learn X in Y minutes Landing page
    Landing page //
    2019-09-04
  • Keras Landing page
    Landing page //
    2023-10-16

Learn X in Y minutes features and specs

  • Concise Learning
    Learn X in Y minutes offers brief and straight-to-the-point introductions to programming languages and tools, making it ideal for quick learning.
  • Wide Range of Topics
    The platform covers a diverse array of programming languages and technologies, providing a useful resource for exploring new areas.
  • Code Examples
    Includes practical code snippets and examples, aiding in the comprehension and application of the presented material.
  • Community Contributions
    Open to community input and contributions, allowing for up-to-date and continuously expanding content.

Possible disadvantages of Learn X in Y minutes

  • Lack of Depth
    Due to the concise nature, the material often lacks depth and may not cover advanced topics thoroughly.
  • Limited Learning Style
    May not suit learners who prefer detailed explanations or a slower, more gradual educational approach.
  • Inconsistency in Quality
    Community contributions can lead to varying quality and consistency across different topics.
  • Minimal Visual Aids
    Primarily text-based with limited visual aids, which can be challenging for visual learners or complex concepts.

Keras features and specs

  • User-Friendly
    Keras provides a simple and intuitive interface, making it easy for beginners to start building and training models without needing extensive experience in deep learning.
  • Modularity
    Keras follows a modular design, allowing users to easily plug in different neural network components, such as layers, activation functions, and optimizers, to create complex models.
  • Pre-trained Models
    Keras includes a wide range of pre-trained models and offers easy integration with transfer learning techniques, reducing the time required to achieve good results on new tasks.
  • Integration with TensorFlow
    As part of TensorFlow’s ecosystem, Keras provides deep integration with TensorFlow functionalities, enabling users to leverage TensorFlow's powerful features and performance optimizations.
  • Extensive Documentation
    Keras has comprehensive and well-organized documentation, along with numerous tutorials and code examples, making it easier for developers to learn and use the framework.
  • Community Support
    Keras benefits from a large and active community, which provides support through forums, GitHub, and specialized user groups, facilitating the resolution of issues and sharing of best practices.

Possible disadvantages of Keras

  • Performance Limitations
    Due to its high-level abstraction, Keras may incur performance overheads, making it less suitable for scenarios requiring extremely fast execution and low-level optimizations.
  • Limited Low-Level Control
    The simplicity and abstraction of Keras can be a downside for advanced users who need fine-grained control over model components and custom operations, which may require them to resort to lower-level frameworks.
  • Scalability Issues
    In some complex applications and large-scale deployments, Keras might face scalability challenges, where more specialized or low-level frameworks could handle such tasks more efficiently.
  • Dependency on TensorFlow
    While the integration with TensorFlow is generally an advantage, it also means that the performance and features of Keras are closely tied to the development and updates of TensorFlow.
  • Lagging Behind Latest Research
    Keras, being a user-friendly high-level API, might not always incorporate the latest cutting-edge research advancements in deep learning as quickly as more research-oriented frameworks.

Learn X in Y minutes videos

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Keras videos

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

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
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Category Popularity

0-100% (relative to Learn X in Y minutes and Keras)

Learn X in Y minutes

Keras

Online Learning
100 100%
Online Learning
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Online Education
100 100%
Online Education
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Learn X in Y minutes and Keras

Learn X in Y minutes Reviews

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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...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Learn X in Y minutes should be more popular than Keras. It has been mentiond 149 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.

Learn X in Y minutes mentions (149)

  • How would you start to learn coding today?
    I can't fathom it, but if I had to start over today, I'd: - Pick something I want to build - Pick the tools -- whatever's at the top of the latest SlackOverflow survey, though I'm not sure SO matters anymore - Peruse the https://learnxinyminutes.com link for the chosen tools - Use an LLM with good prompting to assist me in making what I decided. I'd use chat and hand type the code from the LLM and try to... - Source: Hacker News / 4 months ago
  • 100+ FREE Resources Every Web Developer Must Try
    . HTML Cheat Sheet: Quick reference guide for HTML elements and attributes. . CSS Cheat Sheet: Comprehensive guide to CSS properties and selectors. . JavaScript Cheat Sheet: Handy reference for JavaScript syntax and concepts. . Git Cheat Sheet: Essential commands and workflows for Git. . Markdown Cheat Sheet: Markdown syntax guide for creating rich text formatting. . React Cheat Sheet: Quick overview of React... - Source: dev.to / 10 months ago
  • Lua: The Modular Language You Already Know
    This is a small code example to get the basic idea. If you want a bit of a bigger file to play around yourself Or ever want to learn about a new language you can use LearnXinYMinutes which is a great starting point to learn any language you desire. - Source: dev.to / 11 months ago
  • Scripts should be written using the project main language
    > Sure, maybe for some esoteric edge cases, but 5 mins on https://learnxinyminutes.com/ should get you 80% of the way there, and an afternoon looking at big projects or guidelines/examples should you another 18% of the way. Not for C++, and even for other languages, it's not the language that's hard, it's the idioms. Python written by experts can be well-nigh incomprehensible (you can save typing out... - Source: Hacker News / about 1 year ago
  • Scripts should be written using the project main language
    > Learning a new language shouldn't be difficult. Programmers are expected to familiarize themselves with new tech. I wish any large company agreed with this. I've worked for a company that on boarded every single new engineer to a very niche language (F#) in a few days. Also, everybody I worked with there was amazing. Probably because of that kind of mindset. Meanwhile google tiptoes around teams adopting kotlin... - Source: Hacker News / about 1 year ago
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Keras mentions (35)

  • Top Programming Languages for AI Development in 2025
    The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / 20 days ago
  • Top 8 OpenSource Tools for AI Startups
    If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and running—an essential part of the startup hustle. - Source: dev.to / 7 months ago
  • Top 5 Production-Ready Open Source AI Libraries for Engineering Teams
    At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / 8 months ago
  • 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 / 11 months 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 1 year ago
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What are some alternatives?

When comparing Learn X in Y minutes and Keras, you can also consider the following products

Exercism - Download and solve practice problems in over 30 different languages.

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.

DevDocs - Open source API documentation browser with instant fuzzy search, offline mode, keyboard shortcuts, and more

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

OverAPI - Largest cheat sheet for programming languages and libraries

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

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