--- 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. Ease to work with, suitable for beginners. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** September 16, 2019 **What do you like best about Keras?** Its written in Python. Python is my number one choice. **What do you dislike about Keras?** Syntax is somehow complex. It could be much simpler like others. **What problems is Keras solving and how is that benefiting you?** Working on my experiment. Prefer not to say. ### 2. Easy to use deep learning framework **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** June 28, 2019 **What do you like best about Keras?** Keras is very easy to use, easy to learn with a great community backing it and the code is readable **What do you dislike about Keras?** It's an high level API which makes it a little slow It only runs on python programming language unlike other deep learning framework that run on different languages **What problems is Keras solving and how is that benefiting you?** At my work we use keras to build object detection and image to text models for car plate numbers ### 3. Extremely Useful DL framework for beginners **Rating:** 4.0/5.0 stars **Reviewed by:** Muhammad Usman G. | Enterprise (> 1000 emp.) **Reviewed Date:** October 23, 2018 **What do you like best about Keras?** Keras is the best deep-learning framework for beginner level data scientists and machine-learning/artificial intelligence researchers. I like its high-level features that one can use to program a neural network, for instance, write an image classification task in a few lines. Additionally, the availability of pre-trained networks is a plus which allows practitioners to use DL models even without the need for training or an intelligent initialization for researchers. The feature I like the most is high-level function for training, which automatically keeps track of training and validation loss and also keeps an estimate of training progress. Loss functions are already implemented, so in most cases one do not have to implement these functionalities by themseleves. Training and validation set queues are an efficient way of data handling and that feature is already implemented in Keras. **What do you dislike about Keras?** I only have one complaint that once you start working with Keras it is difficult for researchers to move to Tensorflow type libraries where one can implement flexible functionalities specialized to one's research. **What problems is Keras solving and how is that benefiting you?** I use Keras for Deep Learning/ Artificial Intelligence research, where I develop DL based methods for computer vision and computational imaging. ### 4. Very easy to use Deep Learning framework **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.) **Reviewed Date:** August 02, 2019 **What do you like best about Keras?** Every ML starter should use keras as it directly binds with theano and tensorflow **What do you dislike about Keras?** New version of keras has some incompatability with older version of Keras **What problems is Keras solving and how is that benefiting you?** Started ML research with Keras! Extremely handy in prototyping deep learning models! ### 5. Simple platform to develop deep learning model **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Education Management | Enterprise (> 1000 emp.) **Reviewed Date:** February 18, 2019 **What do you like best about Keras?** Very simple, clean and easy framework to implement deep learning models compared to tensorflow, caffe and PyTorch **What do you dislike about Keras?** Even though it provides a simple interface and high-level implementation of basic deep learning blocks it becomes difficult for custom functions **What problems is Keras solving and how is that benefiting you?** Computer Vision, Deep Learning, Text to Speech Synthesis, Object Detection, Image Classification ### 6. Deep Learning Simplified **Rating:** 5.0/5.0 stars **Reviewed by:** Bhuvan P. | Software Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** May 12, 2018 **What do you like best about Keras?** The API they provide are simple to use and are easy to understand with the detailed documentation available on the official Keras website. Generally Deep Learning Models are complex and hard to implement but with Keras API a newbie can also build his/her own model with great ease. **What do you dislike about Keras?** Keras is a amazing Deep Learning library that fits with TensorFlow and many more Deep Learning libraries but the disadvantage of Keras is that it is only available for Python whereas TensorFlow and the other libraries have multi-language support. **Recommendations to others considering Keras:** One of the best Deep Learning library for Python with a huge community support you can easily find solution to your quires, here is one of the forums I follow to do so: https://groups.google.com/forum/#!forum/keras-users **What problems is Keras solving and how is that benefiting you?** We, TeckGeeks are a Machine Learning and Deep Learning startup. We are interested in building ML and DL models for many different tasks. We build models that fits our client requests. With Keras it is easy to achieve so as we can concentrate more on the overall application and not the model, as Keras serves this by providing simple and consistent API. ### 7. High Level Deep Learning API **Rating:** 5.0/5.0 stars **Reviewed by:** Mohit S. | SoftwaCre Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 11, 2018 **What do you like best about Keras?** The API they provide is efficient where one can make ones own deep learning models with only some basic knowledge. Also they provide support for other machine learning/deep learning libraries like TensorFlow which really makes work easy. One more thing I would like to mention is that they provide module wise API, which means one can play around with each module while building a deep net like the layers, activation functions, cost functions, e.t.c. **What do you dislike about Keras?** This library is pretty good and only option for me to carry out my deep learning tasks. So I personally have no dislikes for it. **Recommendations to others considering Keras:** The documentation is a great source, they provide detailed information of the API along with some good examples. Try to go for those examples first, they provide enough understanding for one to start with Keras. **What problems is Keras solving and how is that benefiting you?** Building Deep Learning Models, actually Keras has made the work easy as one can manipulate it every level. So we can really customise and produce a model that perfectly meets the needs of clients. ### 8. I love this ML toolkit! **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Services | Small-Business (50 or fewer emp.) **Reviewed Date:** June 14, 2018 **What do you like best about Keras?** Keras makes making machine learning models super easy. It has an easy to learn syntax that runs on top of Tensorflow which is the backend I use, which compiles down into native Tensorflow that allows the user to create fast performing machine learning models without worrying about the exact Tensorflow syntax, which can get quite complicated at times. **What do you dislike about Keras?** Sometimes, if you want to do something custom, you really can't unless you go down to the base Tensorflow layer and add raw Tensorflow code, which isn't too great. There should be greater extensibility within Keras itself. **Recommendations to others considering Keras:** Learn basic machine learning first, or even advanced deep learning, as otherwise the product will not teach you. **What problems is Keras solving and how is that benefiting you?** We can build our machine learning models and pipelines in order to solve client problems, such as with agricultural yield prediction for the coming seasons. ### 9. Keras for convolutional and recurrent neural network **Rating:** 5.0/5.0 stars **Reviewed by:** Zachi A. | Senior Engineer, Hospital & Health Care, Enterprise (> 1000 emp.) **Reviewed Date:** April 24, 2018 **What do you like best about Keras?** Fast and flexible way of testing and building different networks, easy loading and saving of model and training with a similar interface to sklearn. **What do you dislike about Keras?** When using with tensor board (with TF background) model looks clumsy, model is shown with additional blocks **Recommendations to others considering Keras:** Just use it ! after you found your perfect model you can always rebuild and retrain with a different framework that is easier to implement online **What problems is Keras solving and how is that benefiting you?** Building CNNs and RNNs for medical predications. I am using different Deep Learning frameworks for a while and this is by far the bast for RESEARCH. you can test and change you networks in a modular way allowing you to make much faster research ### 10. Deep Learning On the Go **Rating:** 4.5/5.0 stars **Reviewed by:** Prabhash T. | Project Manager, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** May 06, 2018 **What do you like best about Keras?** The best thing about Keras is it can work with the well known deep learning and machine learning libraries like TensorFlow and Theano. The API is very easy to use and one can create a whole CNN with less than 20 lines of code. **What do you dislike about Keras?** It is the best deep learning library I have ever found out for python, no dislikes. **Recommendations to others considering Keras:** This a video from famous Data Science Enthusiast, Siraj Raval : https://www.youtube.com/watch?v=j_pJmXJwMLA , watch it he explains every bit of Keras. **What problems is Keras solving and how is that benefiting you?** Developing CNN, RNN and other deep learning models to carry out various tasks in our organizations. ### 11. Keras: Tensorflow made simpler **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** January 17, 2018 **What do you like best about Keras?** Keras makes working with Tensorflow and doing deep-learning very easy: it provides an user friendly API that hides most of the complexity of using TF. Models can be quickly defined by piping Keras layers together and tweaking the parameters through the layer constructor. The learning process can be easily customized by tweaking the various rates. Since training a deep-learning model takes a lot of time/data and things can easily go wrong, you will appreciate the availability of the training callbacks: the ReduceLROnPlateau, ModelCheckpoint or TensorBoard, to name a few. Definitely a library the must be used for quickly putting together prototypes before diving too much into the details. **What do you dislike about Keras?** Keras doesn't make it easier to debug your models: but this is not a problem strictly tied to the library and it's common in the deep learning world. **Recommendations to others considering Keras:** If you need to quickly put together a prototype for a new idea, Keras is the go-to library to get started. You might need to do without it to have a greater control over your model in the next phases, but this is definitely the way to start. Documentation is widely available and there is plenty of tutorials to get yourself up to speed with the API. **What problems is Keras solving and how is that benefiting you?** Training a deep-learning model for performing anomaly detection in time series and recommendation systems. ### 12. Excellent Platform for Deep Learning **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Consumer Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 27, 2017 **What do you like best about Keras?** The Keras API makes experimenting with deep learning models a breeze. It's easy to stack layers and to experiment with different deep learning architectures for a wide variety of problems including natural language processing and activity recognition. **What do you dislike about Keras?** Keras is still in development. Although it works great the majority of the time, don't be surprised if you find a bug or that a specific architecture/deep learning layer you want to use is not implemented yet. **Recommendations to others considering Keras:** There are plenty of tutorials online on how to get started with Keras. However, it's always good to understand the math behind any neural network architecture before implementing it to make it easier to debug and understand why it does what it does. **What problems is Keras solving and how is that benefiting you?** I have used Keras to build natural language processing models. The application of these models has helped us to realize better engagement with our users and better performance from our employees. ### 13. Usability: Maximum, Configurability: Minimum **Rating:** 3.0/5.0 stars **Reviewed by:** Subit C. | Graduate Research Assistant, Defense & Space, Small-Business (50 or fewer emp.) **Reviewed Date:** October 30, 2017 **What do you like best about Keras?** Keras is all about ease of use. It should take a true beginner (someone who theoretically understands neural network but has never coded one) less than an hour to code their first network. And it works ! I also like that it works with both Theano and Tensorflow (although that might change soon). **What do you dislike about Keras?** There is minimum configurability and things that are essential and easily accomplished in other frameworks takes a while. For example, building a layer that is not in one of the predefined templates or checking the weights on each layers. **Recommendations to others considering Keras:** Keras is super easy to use and a good way to learn neural networks. However, once you start building complicated models/networks Keras is rarely enough **What problems is Keras solving and how is that benefiting you?** Keras tries to simplify the building of deep neural networks. Its audience is people who are not hardcore software engineers/data scientists who breathe Tensorflow/Theano every day. This it does perfectly. ### 14. Very recomendable for deep learning in medical imaging **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** May 29, 2018 **What do you like best about Keras?** Different backends, relies on python. Works in 3D images. Is easy to install. **What do you dislike about Keras?** Since it is python based, it's not compatible with 3d image visualisation. When using tensor flow, the only way to follow the training is using tensor board, which is slow. **What problems is Keras solving and how is that benefiting you?** Medical image a analysis in 3d ### 15. Easy and flexible **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Telecommunications | Small-Business (50 or fewer emp.) **Reviewed Date:** May 21, 2018 **What do you like best about Keras?** Easy setup, flexibility, different backends, python-based **What do you dislike about Keras?** There's no interface such as nvidia digits. There is tensorboard but it's slow and not as intuitive as digits **What problems is Keras solving and how is that benefiting you?** Medical Image Analysis. Working with 3D images easily. ## 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?page=2§ion=pricing&secure%5Bexpires_at%5D=2026-08-02+23%3A23%3A46+-0500&secure%5Bsession_id%5D=83cd66fb-069c-4327-9962-f16d4dcc3257&secure%5Btoken%5D=039be16ba89c787d38e221643d063282d05aa9bffe4e11d18ac3f8ee798f62c0&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) - [Knet](https://www.g2.com/products/knet/reviews) - 4.3/5.0 (12 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)