Software Alternatives, Accelerators & Startups

GitHub Copilot VS Keras

Compare GitHub Copilot VS Keras and see what are their differences

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GitHub Copilot logo GitHub Copilot

Your AI pair programmer. With GitHub Copilot, get suggestions for whole lines or entire functions right inside your editor.

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.
  • GitHub Copilot Landing page
    Landing page //
    2023-10-03

Trained on billions of lines of public code, GitHub Copilot puts the knowledge you need at your fingertips, saving you time and helping you stay focused.

  • Keras Landing page
    Landing page //
    2023-10-16

GitHub Copilot features and specs

  • Productivity Boost
    GitHub Copilot helps developers write code faster by providing intelligent suggestions and automating repetitive tasks. This can save significant time and reduce the cognitive load on developers.
  • Learning Tool
    For less experienced developers, Copilot can serve as a learning tool by suggesting best practices and introducing them to new coding patterns and techniques.
  • Support for Multiple Languages
    Copilot supports a wide range of programming languages, making it a versatile tool for developers working in different tech stacks.
  • Context-Aware Suggestions
    Copilot offers context-aware suggestions based on the code that has been written so far, making its recommendations relevant to the current development task.
  • Integration with GitHub
    Seamless integration with GitHub simplifies the development workflow, enabling smoother transitions from coding to version control and collaboration.

Possible disadvantages of GitHub Copilot

  • Code Quality Concerns
    The quality of the code generated by Copilot may vary, and it might introduce suboptimal code or practices that could lead to maintenance challenges.
  • Security Risks
    Copilot might suggest insecure code patterns or snippets, potentially introducing vulnerabilities into the project if not carefully reviewed by the developer.
  • Dependence on AI
    Over-reliance on Copilot's suggestions can lead to a lack of deep understanding of the code, which may hinder a developer's growth and problem-solving skills.
  • Licensing and Code Reuse Issues
    There are concerns about the legality and ethics of using AI-generated code snippets that might be derived from copyrighted sources, which can lead to licensing issues.
  • Limited Customizability
    Copilot may not always align with specific coding standards or preferences of a development team, and the ability to customize its behavior to enforce such standards is limited.

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.

GitHub Copilot videos

Game over… GitHub Copilot X announced

More videos:

  • Review - The New GitHub Copilot X Powered by GPT-4 is Here!
  • Review - GitHub Copilot X -- AI Programming Gets Better... and Scary.
  • Review - GitHub Copilot Review 2023: I Love It, But It's Not For Everyone
  • Review - Is Github Copilot Worth Paying For??

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

Category Popularity

0-100% (relative to GitHub Copilot and Keras)
Developer Tools
100 100%
0% 0
Data Science And Machine Learning
AI
100 100%
0% 0
Data Science Tools
0 0%
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 GitHub Copilot and Keras

GitHub Copilot Reviews

  1. Stan
    · Founder at SaaSHub ·
    Indispensable

    It definitely increases my productivity.

    🏁 Competitors: Tabnine

Cursor vs Windsurf vs GitHub Copilot
GitHub Copilot Chat is similar — you can ask it to explain code or suggest improvements. It's integrated right into VS Code, so it feels pretty seamless. They've been rolling out some new features lately, like better chat history, drag and & folders and ways to attach more context. But if you're already using Cursor, you might not find anything groundbreaking here.
Source: www.builder.io
Cursor vs GitHub Copilot
GitHub Copilot Chat is similar — you can ask it to explain code or suggest improvements. It's integrated right into VS Code, so it feels pretty seamless. They've been rolling out some new features lately, like better chat history, drag and & folders and ways to attach more context. But if you're already using Cursor, you might not find anything groundbreaking here.
Source: www.builder.io
Top 10 Vercel v0 Open Source Alternatives | Medium
Next up, we have GitHub Copilot, a popular AI-powered code completion tool that’s been making waves in the developer community. Built on top of OpenAI Codex, Copilot integrates seamlessly with various code editors and IDEs to provide intelligent code suggestions as you type.
Source: medium.com
10 Best Github Copilot Alternatives in 2024
GitHub Copilot is an excellent tool for developers, allowing them to boost their workflow and project quality. Are you looking for a GitHub Copilot alternative that fits your needs in 2024? Whether you’re searching for a free GitHub Copilot alternative, an open-source alternative to GitHub Copilot, or a tool that works well with VSCode, this guide is here to help.
The Best GitHub Copilot Alternatives for Developers
Moreover, GitHub Copilot provides a wide range of functionalities, such as code explanation, answering coding questions, refactoring code, and generation of unit tests and docs. With it, developers can automate coding tasks, improve productivity and focus more on complex coding. GitHub Copilot supports various programming languages, including JavaScript, Python, Ruby, Go,...
Source: softteco.com

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...

Social recommendations and mentions

Based on our record, GitHub Copilot should be more popular than Keras. It has been mentiond 290 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.

GitHub Copilot mentions (290)

  • Agentic AI: Your New Coding Buddy
    Unlike autocomplete tools like GitHub Copilot, Agentic AI can take broad instructions like “build me a login page with email verification” and handle it end-to-end. - Source: dev.to / 2 days ago
  • Top 10 Programming Trends and Languages to Watch in 2025
    AI-assisted coding is transforming software development by enhancing efficiency, reducing repetitive tasks, and improving code quality. Tools like GitHub Copilot, Amazon CodeWhisperer, and OpenAI's Codex provide developers with suggestions for entire functions, automate boilerplate code, and identify real-time errors. AI also supports early bug detection and automated code reviews, which are essential for... - Source: dev.to / 3 days ago
  • AI Code Generators & Tools That Speed Up App Development
    GitHub Copilot has emerged as one of the most widely adopted AI coding assistants, offering real-time suggestions as you type. - Source: dev.to / 10 days ago
  • What's Happening in Developer Tools? (OpenAI Just Bought Windsurf for $3B)
    Microsoft's Visual Studio Code is a free code editor that relies on community plugins for support across various languages and frameworks. It also has an AI offering, Copilot, that provides code completion and it just added its own agent. VSCode supports multiple LLMs, but initially, there seemed to be a preference for ChatGPT, in part given its early lead and no doubt influenced by the fact Microsoft was an early... - Source: dev.to / 11 days ago
  • Inline AI Suggestions in NeoVim: GitHub Copilot vs Windsurf (Codeium) — A Technical Comparative Analysis
    GitHub Copilot Official Site — Overview of Copilot’s capabilities, pricing, and integrations from GitHub. - Source: dev.to / 12 days ago
View more

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 / 19 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
View more

What are some alternatives?

When comparing GitHub Copilot and Keras, you can also consider the following products

Codeium - Free AI-powered code completion for *everyone*, *everywhere*

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.

Tabnine - TabNine is the all-language autocompleter. We use deep learning to help you write code faster.

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

Visual Studio IntelliCode - Visual Studio IntelliCode is an experimental set of AI-assisted development capabilities for next-generation developer productivity.

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