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Keras VS Sourcegraph

Compare Keras VS Sourcegraph and see what are their differences

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  3. » Reviews
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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.

Sourcegraph logo Sourcegraph

Sourcegraph is a free, self-hosted code search and intelligence server that helps developers find, review, understand, and debug code. Use it with any Git code host for teams from 1 to 10,000+.
  • Keras Landing page
    Landing page //
    2023-10-16
  • Sourcegraph Landing page
    Landing page //
    2023-08-06

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.

Sourcegraph features and specs

  • Code Search
    Sourcegraph offers powerful, fast, and precise code search across large codebases, which helps developers quickly find references, definitions, or implementations.
  • Cross-Repository Search
    Allows searching across multiple repositories within the same interface, enhancing discoverability and productivity.
  • Integrations
    Sourcegraph integrates with popular code hosting platforms like GitHub, GitLab, Bitbucket, and more, providing a seamless experience.
  • Code Intelligence
    Supports advanced code intelligence features like hover tooltips, go-to-definition, and find-references, making code navigation easier.
  • Extensibility
    Developers can extend Sourcegraph's functionality with custom extensions, adapting it to their specific needs.
  • Data Privacy
    Sourcegraph can be self-hosted, giving organizations control over their code and data privacy.
  • Multi-Language Support
    Supports a wide range of programming languages and continuously adds more, catering to diverse development environments.

Possible disadvantages of Sourcegraph

  • Complex Setup
    Setting up Sourcegraph, especially self-hosted versions, can be complicated and time-consuming, requiring a good understanding of DevOps practices.
  • Resource Intensive
    Sourcegraph can be resource-heavy, necessitating significant computational power and memory, especially for large codebases.
  • Cost
    While there is a free tier, advanced features and self-hosted options can be expensive for small teams or individual developers.
  • Learning Curve
    The myriad of features and customizations can result in a steep learning curve for new users, potentially slowing down initial adoption.
  • Limited Offline Support
    While Sourcegraph provides robust online features, its functionality is limited when offline, which can impact productivity in environments with restricted internet access.
  • Dependency on Code Hosts
    Sourcegraph's heavy reliance on integrations with external code hosting platforms can introduce friction if there are changes or issues with those services.

Keras videos

+ Add

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

Sourcegraph videos

+ Add

Code review with IDE powers: Sourcegraph Chrome extension

More videos:

  • Review - Better code reviews on GitHub with the Sourcegraph browser extension
  • Review - Sourcegraph's new GitLab native integration

Category Popularity

0-100% (relative to Keras and Sourcegraph)

Keras

Sourcegraph

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Git
0 0%
Git
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 Keras and Sourcegraph

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

Sourcegraph Reviews

We have no reviews of Sourcegraph yet.
Be the first one to post

Social recommendations and mentions

Keras might be a bit more popular than Sourcegraph. We know about 35 links to it since March 2021 and only 34 links to Sourcegraph. 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 (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 / 13 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 / 7 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

Sourcegraph mentions (34)

  • Ask HN: Cursor or Windsurf?
    This is a product by Sourcegraph https://sourcegraph.com who already have a solution in this space. Is this something wildly different to Cody, your existing solution, or just a "subtle" attempt to gain more customers? - Source: Hacker News / about 9 hours ago
  • Ask HN: Who is hiring? (April 2025)
    Sourcegraph | San Francisco / Remote | Full-Time | SWE, Database Platform Eng, Forward Deployed Eng, Solutions Eng, Dev Advocate (all roles write code) | https://sourcegraph.com Sourcegraph is how enterprises industrialize software development with AI. We accelerate and automate how software is built in the world's most important companies, including 7/10 top software companies by market cap and 4/6 top US banks.... - Source: Hacker News / about 1 month ago
  • Quickly build UI components with AI
    Cody by Sourcegraph can transform how you build UI components, from basic buttons to complex, dynamic systems. It handles the heavy lifting so you can focus on crafting good UI/UX designs. Whether you’re customising components or managing complex UI systems, Cody provides the tools to make the process faster and more efficient. - Source: dev.to / 2 months ago
  • 22 Unique Developer Resources You Should Explore
    URL: https://sourcegraph.com What it does: A universal code search tool for navigating large codebases. Why it's great: Quickly locate what you need in vast repositories — ideal for collaboration! - Source: dev.to / 4 months ago
  • Copilot vs. Cody: All you need to know
    What is Sourcegraph Cody? Cody, introduced by Sourcegraph, is an AI-powered coding assistant designed to use advanced search and codebase context to help you understand, write, and fix code faster. Launched in 2023, Cody aims to provide deeper context and more accurate code suggestions, particularly for complex and large-scale projects. - Source: dev.to / 5 months ago
View more

What are some alternatives?

When comparing Keras and Sourcegraph, 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.

OpenGrok - OpenGrok is a fast and usable source code search and cross reference engine.

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

Atlassian Fisheye - With FishEye you can search code, visualize and report on activity and find for commits, files, revisions, or teammates across SVN, Git, Mercurial, CVS and Perforce.

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

codespell.ai - AI-Powered Code Completion for Faster SDLC

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