--- title: Keras Reviews meta_title: 'Keras Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 65 reviews by the users' company size, role or industry to find out how Keras works for a business like yours. aggregate_rating: rating_value: 4.6 review_count: 65 scale: '5' date_modified: '2026-07-12' parent_category: name: Deep Learning url: https://www.g2.com/categories/deep-learning --- # Keras Reviews **Vendor:** Keras **Category:** [Artificial Neural Network Software](https://www.g2.com/categories/artificial-neural-network) **Average Rating:** 4.6/5.0 **Total Reviews:** 65 ## About Keras Keras is a neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. ## Keras Reviews ### 1. A Versatile Tool for Machine Learning, Computer Vision, and Deep Learning **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Renewables & Environment | Small-Business (50 or fewer emp.) **Reviewed Date:** April 07, 2026 **What do you like best about Keras?** It’s a versatile tool for machine learning, computer vision, and deep learning. **What do you dislike about Keras?** It has compatibility issues, and on some machines it can be difficult to install and set up. **What problems is Keras solving and how is that benefiting you?** I use it for machine learning and deep learning modeling. ### 2. Best DL Framework **Rating:** 5.0/5.0 stars **Reviewed by:** Aakash Kumar A. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** September 13, 2023 **What do you like best about Keras?** keras is one of the prominent deep learning framework, it is easy to implement and provides great a amount of important functionalities which helps developer to achieve maximum accuracy **What do you dislike about Keras?** There is nothing to dislike in keras except few things like it still haven't upgraded with the latest functionalities such as nlp and generative AI which are some important tools nowadays **What problems is Keras solving and how is that benefiting you?** Keras helps me to build exceptional deep neural networks and build best models. Keras makes building the neutral network easier. I don't have to manually write anything. ### 3. User-friendly and effective high-level neural-network API **Rating:** 5.0/5.0 stars **Reviewed by:** Subham S. | Data Scientist, Mid-Market (51-1000 emp.) **Reviewed Date:** August 18, 2022 **What do you like best about Keras?** There are a lot of reasons to like Keras: 1. This open-source deep-learning library is designed to provide fast experimentation with deep neural networks. 2. Keras provides the flexibility to run on top of CNTK, TensorFlow, and Theano. 3. It is focused on being modular, user-friendly, readable, and extensible. 4. Keras provides the power to build deep neural networks using fewer lines of code, and this amazes me the most. 5. Since Keras was adopted and integrated into TensorFlow in mid-2017, we can leverage its power by deploying trained models to production thanks to the TensorFlow Serving framework. 6. Keras has excellent access to reusable code and tutorials, which makes it extremely suitable even for beginners. 7. Since Keras runs on top of TensorFlow, it can be equipped with single or multiple GPUs for faster computations. **What do you dislike about Keras?** There are a few reasons for disliking Keras: 1. Keras is not very customizable on its own. While researching different algorithms or working on multi-dimensional matrices, we still need scikit-learn, OpenCV, or Tensorflow for performing such operations. 2. Sometimes the errors are difficult to debug since finding error logs is difficult. For these reasons alone, Keras is still one of the most popular and favorite libraries for statisticians, data scientists, ML engineers, etc. **What problems is Keras solving and how is that benefiting you?** As a data scientist, I have to very frequently build different state-of-the-art deep learning models, and Keras is one such library without which this task seems impossible. One of my recent projects involved Time-Series Forecasting, which involved building different state-of-the-art Deep Learning models like Transformers, LSTMs, etc., which was done using Keras and Tensorflow. If anyone wants to go through a simple implementation using Keras: https://github.com/SubhamIO/KERAS-on-MNIST-dataset ### 4. Keras has always provided with all the tools for machine learning **Rating:** 5.0/5.0 stars **Reviewed by:** Bassel M. | ADAS Machine Learning Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 31, 2021 **What do you like best about Keras?** I like the simplicity of building neural networks **What do you dislike about Keras?** The difficulty of implementing my customized metric **What problems is Keras solving and how is that benefiting you?** I was training a model for classifying images ### 5. Deep Learning made easy and a wonderful library that does offer a lot! **Rating:** 4.0/5.0 stars **Reviewed by:** Sathesh R. | Managed Services Integration Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** September 15, 2022 **What do you like best about Keras?** Best wrapper API available out there for Neural networks. You need not have to be an expert programmer, it does offer what you need to get the job done and it is an open source. Integrates well with tensor flow. Its native to python and I come up with python background, it does make my coding world a lot easier. Implementing a neural network would take hours of coding, but Keras has made it simpler with few lines of code and it is easily understandable. **What do you dislike about Keras?** Understanding of the log traces to fix a problem takes time, as you would have to understand the way it is traced and written, that would take time because of limited documentation. As a python developer I find it to be easier to use, but it doesnt provide other language support, it could be a problem for a long term development. It doesnt offer a great backend support as it is limited. **What problems is Keras solving and how is that benefiting you?** It does make development faster by offering a lot with neural networks, it makes the neural network implementation much easier and smoother which helps save lot of time. ### 6. Open source tool for managing artificial neural networks **Rating:** 4.0/5.0 stars **Reviewed by:** Paweł W. | Software Engineer @ Creators, Small-Business (50 or fewer emp.) **Reviewed Date:** October 09, 2022 **What do you like best about Keras?** First of all Keras is a complete API for managing neural networks and is an open source tool. I find its API extremely convenient to use - definitely simpler to use than PyTorch **What do you dislike about Keras?** It might get slow for some complicated use cases, so if you are aiming for speed and efficiency then probably PyTorch would be a better choice. **What problems is Keras solving and how is that benefiting you?** Keras provides an API that allows me as a developer to avoid some of the typical boilerplate code that would be written without using any framework. It lets me focus on modelling the problem rather than reinventing the wheel ### 7. User friendly high level framework for developing deep neural networks **Rating:** 4.5/5.0 stars **Reviewed by:** Dipak K. | Senior Research Fellow (PhD), Small-Business (50 or fewer emp.) **Reviewed Date:** June 08, 2022 **What do you like best about Keras?** easy and quick implementation of a variety of neural network models. simple and easy to learn with vast support from the Keras community and documentation. I like the most about Keras is the high-level framework and runs on top of TensorFlow with single or multiple GPUs for faster computations. availability of pre-trained models such as VGGNET, RESNET, etc. **What do you dislike about Keras?** Preprocessing of the signals or images is still not widely used due to lack of customization. one needs to use additional tools such as Scikit-learn to do the proper preprocessing. Issues in the low-level backend can not be targeted and finding those error logs is difficult. Other than these issues Keras is widely famous in the AI field. **What problems is Keras solving and how is that benefiting you?** Building state-of-the-art neural network models for various applications such as classification and identification tasks in the biomedical field. Few deep learning model examples are ResNET, Alexnet, autoencoders etc. ### 8. An excellent neural network library to run our models **Rating:** 4.0/5.0 stars **Reviewed by:** Ashish T. | System Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** September 27, 2022 **What do you like best about Keras?** It is easier to use and setup on most of the backend systems like tensor flow and pytorch. This provides a lot of operational freedom to developers to experiment. **What do you dislike about Keras?** Some external integration is difficult to implement on the system and requires assistance from consultants. Initial setup on windows OS is also a bit challenging. **What problems is Keras solving and how is that benefiting you?** Keras is helping in getting our deep learning projects off the ground, it is very helpful in running these projects and allows us to maintain and run the models . ### 9. Great for beginners and for somewhat advanced as well. **Rating:** 4.0/5.0 stars **Reviewed by:** Gourav S. | Open Source Contributor, Small-Business (50 or fewer emp.) **Reviewed Date:** September 13, 2022 **What do you like best about Keras?** Keras is amazing with its documentation and I've used it on Google collab. It worked super well, models were meeting expectations. **What do you dislike about Keras?** Might not be that great as compared to alternatives, when it comes to speed, it's somewhat slow. **What problems is Keras solving and how is that benefiting you?** It's good if you wanna learn Tensorflow and Tensorflow 2. As it's built on following Api. ### 10. Makes deep learning easy **Rating:** 4.0/5.0 stars **Reviewed by:** Shubham C. | DECISION ANALYTICS ASSOCIATE, Small-Business (50 or fewer emp.) **Reviewed Date:** September 01, 2022 **What do you like best about Keras?** Keras makes deep learning easy . Its easy to use and every code is thoroughly explained in the website **What do you dislike about Keras?** Codes should be more easy to find. apart from that there is no issue **What problems is Keras solving and how is that benefiting you?** I wanted to learn deep learning. Being from a non technical Background keras has made it easy for me ## Keras Discussions - [what's the best way to go about the documentation of Keras . lack of clarity is provided on various topics for example cooldown parameter in ReduceLROnPlateau is clearly not explained .](https://www.g2.com/discussions/36779-what-s-the-best-way-to-go-about-the-documentation-of-keras-lack-of-clarity-is-provided-on-various-topics-for-example-cooldown-parameter-in-reducelronplateau-is-clearly-not-explained) - 1 upvote - [How can I use Keras for text recognition?](https://www.g2.com/discussions/36633-how-can-i-use-keras-for-text-recognition) - 1 upvote - [Is there any work going on to make conversions from Tensorflow to Keras and vice versa possible?](https://www.g2.com/discussions/is-there-any-work-going-on-to-make-conversions-from-tensorflow-to-keras-and-vice-versa-possible) - 1 upvote - [How to I convert convert a pytorch model to keras model](https://www.g2.com/discussions/how-to-i-convert-convert-a-pytorch-model-to-keras-model) - 1 upvote - [How can I use Keras for](https://www.g2.com/discussions/37002-how-can-i-use-keras-for) - [View Keras pricing details and edition comparison](https://www.g2.com/products/keras/reviews/keras-review-4557668?section=pricing&secure%5Bexpires_at%5D=2026-07-16+09%3A36%3A30+-0500&secure%5Bsession_id%5D=bafddd61-6d89-4c97-8a29-2a2267826c75&secure%5Btoken%5D=9b220b6bf311c70f01d15e6272fbfd528f297add915723137aefe40b1a6e8e6c&format=llm_user) ## Keras Integrations - [TensorFlow](https://www.g2.com/products/tensorflow/reviews) ## Keras Features **Core Functionality - Artificial Neural Network** - Neural Network Training - Neural Network Testing - Model Evaluation - Compliance **Data Handling - Artificial Neural Network** - Data Integration - Data Preprocessing **Performance - Artificial Neural Network** - Model Optimization - Scalability **Usability - Artificial Neural Network** - User Interface - Documentation & Support - Customizability **Advanced Features - Artificial Neural Network** - Deep Learning Capabilities - Transfer Learning - Real-Time Processing - Automated Model Tuning - Visualization Tools **Agentic AI - Artificial Neural Network** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top Keras Alternatives - [TFLearn](https://www.g2.com/products/tflearn/reviews) - 4.0/5.0 (20 reviews) - [NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/products/nvidia-deep-learning-gpu-training-system-digits/reviews) - 4.5/5.0 (22 reviews) - [Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/products/microsoft-cognitive-toolkit-formerly-cntk/reviews) - 4.2/5.0 (22 reviews)