Software Alternatives, Accelerators & Startups

Keras VS Unreal Engine

Compare Keras VS Unreal Engine and see what are their differences

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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.

Unreal Engine logo Unreal Engine

Unreal Engine 4 is a suite of integrated tools for game developers to design and build games, simulations, and visualizations.
  • Keras Landing page
    Landing page //
    2023-10-16
  • Unreal Engine Landing page
    Landing page //
    2023-10-23

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.

Unreal Engine features and specs

  • High-Quality Graphics
    Unreal Engine is known for its ability to produce stunning, high-quality graphics and realistic environments, making it a preferred choice for AAA game development and high-fidelity visual projects.
  • Blueprint Visual Scripting
    Unreal Engine offers a visual scripting system called Blueprints, which allows designers to create complex game logic without any programming knowledge, streamlining the development process.
  • Cross-Platform Support
    Unreal Engine provides robust support for multiple platforms, including PC, consoles, mobile devices, and VR/AR headsets, enabling developers to reach a wider audience with minimal hassle.
  • Large and Active Community
    The Unreal Engine community is large and active, offering extensive resources, tutorials, and forums which can be invaluable for troubleshooting and learning new techniques.
  • Regular Updates
    Epic Games frequently updates Unreal Engine, adding new features, improvements, and optimizations to keep developers equipped with the latest technology advancements.
  • Marketplace
    The Unreal Engine Marketplace offers a vast array of assets, ranging from 3D models to plugins, which can significantly speed up the development process by providing ready-to-use resources.

Possible disadvantages of Unreal Engine

  • Steep Learning Curve
    Due to its extensive features and capabilities, Unreal Engine can be challenging for beginners to master, requiring a significant investment of time and effort to learn.
  • High System Requirements
    Developing with Unreal Engine often requires a powerful computer with strong hardware specifications, which can be a barrier for developers with limited resources.
  • Large File Sizes
    Unreal Engine projects can result in large file sizes, which can be cumbersome to manage, particularly in terms of storage and transfer bandwidth.
  • Complexity for Simple Projects
    For smaller or simpler projects, the capabilities of Unreal Engine might be overkill, and using it can unnecessarily complicate development when compared to lighter engines.
  • Royalty Fees
    Unreal Engine imposes a royalty fee of 5% on gross revenue after the first $1 million USD per product per year, which can impact the profitability of commercial projects.
  • Less C++ Flexibility
    While Unreal Engine supports C++, the engine imposes certain constraints and abstractions that can limit the flexibility developers might need for highly customized or optimized code.

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

Unreal Engine videos

Why I switched over to Unreal Engine 4 From Unity 5

More videos:

  • Review - Unity vs Unreal Engine | Graphics, Workflow, Price, Level Design and More! (2017-2018)
  • Review - Game Development | Intro to Unreal Engine 4 | No Prior Programming Knowledge

Category Popularity

0-100% (relative to Keras and Unreal Engine)
Data Science And Machine Learning
Game Development
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Game Engine
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 Keras and Unreal Engine

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...

Unreal Engine Reviews

Top 13 Picks for Maxon Cinema 4D Alternatives in 2024
Designed by Epic Games, Unreal Engine is a comprehensive 3D graphics engine initially developed for PC gaming. Since its inception in 1998, it supports a wide array of platforms, including mobile, console, and VR. It is known for its versatility and power in a broad spectrum of industries like film and television.
Source: aircada.com
Game Engines: A Comparative Analysis
Developed by Epic Games, Unreal Engine stands as a titan in the industry, renowned for its stunning graphics and realistic visual effects. It excels in AAA game development, with a powerful rendering engine and an intuitive visual scripting system called Blueprints. Unreal Engine’s prowess lies in its ability to deliver top-notch graphics and cinematic experiences.
Source: medium.com
Best Unity alternatives for game development
Unreal Engine has become one of the most popular engines to date; it's one of the top-of-the-line gaming engines that produces high graphical fidelity and realism for many games. In fact, many mobile games (Injustice 2, Life is Strange) that look incredible are likely using the Unreal Engine. It's a number one choice that often goes head-to-head with Unity due to its great...
Best Game Engines for 2023 – Which Should You Use?
However, many game developers do report that Unreal Engine is better suited for larger projects and projects you intend to work on as a team. Additionally, as the program is heavy on the graphics end, many people will find it requires a more powerful computer compared to other engines like Unity. Beyond this, it is also noteworthy that while Unreal Engine can create 2D games...
The Best Gaming Engines You Should Consider for 2023
2022 saw the official launch of Unreal Engine 5, and it’s already shaping up to be a game changer for game development. Most next-gen consoles, including PlayStation 5 and Xbox Series X are already using it, and its powerful tools such as Lumen and Nanite (an engine that imports high-detailed photographic source material – taking advantage of its past acquisition of Quixel)...

Social recommendations and mentions

Based on our record, Keras seems to be more popular. It has been mentiond 35 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.

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 / 21 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

Unreal Engine mentions (0)

We have not tracked any mentions of Unreal Engine yet. Tracking of Unreal Engine recommendations started around Mar 2021.

What are some alternatives?

When comparing Keras and Unreal Engine, 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.

Unity - The multiplatform game creation tools for everyone.

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

Godot Engine - Feature-packed 2D and 3D open source game engine.

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

Blender - Blender is the open source, cross platform suite of tools for 3D creation.