Keras Ratings

Overall
4.5/5
Ease of Use
4.5/5
Customer Service
4.5/5

About Keras

API tool which provides an open source neural network library through recurrent and convolutional networks. Learn more about Keras

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Showing 30 of 30 reviews

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Company Size
Reviewer's Role
Length of Use
Frequency of Use
Verified Reviewer
Retail, Unspecified
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
3/5
Features
3/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
May 2, 2018

“A great library for training Deep Neural Networks”

OverallKeras is fully compatible with Core ML - this allows our dev team to build complex mobile applications on the latest iOS devices.
ProsPython is easy to use and extensible. The modularity of these libraries is the future of building complex machine learning models. Keras is one of the better frameworks out there right now. It allows us to train deep neural nets at a reasonable rate. Keras is compatible with Apple's Core ML which is very useful for our moblie app development.
ConsKeras is a little limited in what it can handle. Luckily there are other frameworks popping up every day to supplement any shortcomings.
Reviewer Source 
Source: Capterra
May 2, 2018
Luigi V.
Computer Engineer
Defense & Space, 51-200 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
4/5
Customer Service
5/5
Features
5/5
Value for Money
3/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
October 4, 2019

“Best High Level API for Tensorflow”

OverallKeras simplifies a lot the designing and manipulation of a Neural Networkìs architecture, making way more accessible the usage of Neural Networks to a wider public. Extremely powerful.
ProsThis is definitely a user friendly framework to use on top of a Machine Learning library, the obvious choice for me would be to use it alongside Tensorflow.
ConsMight looks a bit difficult at first, but if you know the theory behind Neural Networks then you would not have any problem using it for your projects.
Reviewer Source 
Source: Capterra
October 4, 2019
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Shalinee S.
Web UI Developer
Information Technology and Services, 201-500 employees
Used the software for: 2+ years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
4/5
Features
4/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
October 6, 2018

“keras - an easy way to develop machine learning models”

ProsIt has made machine learning and deep learning implementation very easy as compared to tensorflow. Implementing deep learning models using tensorflow is very difficult, you have to take care of each and every variables but if you are using keras it's very easy to do this. With just few lines of code you can develop a deep learning model. Keras also provide lots of functionality for data processing like converting to one hot encoding and lot other.
ConsAs it provides lots of easy way to implement algorithm but it restricts you to use those functionality only. If you want to build good algorithm with lot of optimization, you can't do everything with keras.
Reviewer Source 
Source: Capterra
October 6, 2018
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Dr. Jayant J.
Assistant professor
Education Management, 201-500 employees
Used the software for: 2+ years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
5/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
June 8, 2019

“Keras is the best API and framework for deep learning application development”

OverallI have developed many deep learning applications using keras.
ProsMany ready available function are written by community for keras for developing deep learning applications. It is easy to use and user friendly.
ConsBackend support is available only with theano or tensorflow.
Reviewer Source 
Source: Capterra
June 8, 2019
Avatar Image
Waleed E.
Assistant Lecturer in Mechatronics Department
Education Management, 5001-10,000 employees
Used the software for: Less than 6 months
Overall Rating
5/5
Ease of Use
5/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
July 25, 2019

“What you need definitely to start your deep learning experiments”

OverallI would defintely recommend it as the quickest step to start testing your model.
ProsKeras is the only platform that runs on top of most popular backends like TensorFlow, pyTorch and Microsoft Cogntitive Toolkit. This gives great flexibility to researchers to try their network architecture with minimal changes across multiple libraries mentioned. The sequencing modularity is what makes you build sophisticated network with improved code readability .
ConsIf you encounter an error, it is hard to be debugged.
Reviewer Source 
Source: Capterra
July 25, 2019
Avatar Image
Shambhavi J.
BI Developer
Unspecified
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
5/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
July 18, 2018

“Best wrapper library for tensorflow an theano -- very easy to use”

Overallhave made writing neural network implementation very easy
ProsWhile writing the neural network with tensorflow, we need to take care of every thing like input layer size, output layer size, bias vector size. We have to design the whole layer itself. But with this library, it can be done in just one line. Also it has lots of inbuilt feature for data processing which makes it very usable. And it's support for both tensorflow and theano, makes it more advance.
ConsIt is best wrapper library over tensorflow, but it restrict you to use their implemented algorithm. Although, you can configure the inbuilt functionality, but then it would be better to do that with tensorflow only.
Reviewer Source 
Source: Capterra
July 18, 2018
Verified Reviewer
11-50 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Features
4/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
June 28, 2018

“The more accessible brother of TensorFlow”

ProsIt's very, very easy to build most traditional DL algorithms and train them, even with some modifications.
ConsDeveloping new algorithms might be somewhat more cumbersome than with some of the alternatives, as Keras stays at a pretty high level of abstraction.
Reviewer Source 
Source: Capterra
June 28, 2018
Deepak Kumar S.
Quality Assurance Engineer
Information Technology and Services, 201-500 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
5/5
Features
4/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
January 2, 2019

“Best available wrapper library for tensor flow and theano backend”

Overallbest wrapper library for deep learning or to just bypass the tensorflow
ProsThis library has made the deep learning's algorithm implementation very easy and fast. It comes with lot of inbuilt functionalities like one hot encoder and lot other data processing stuff. Also, writing the neural network implementation with this library is just few lines of code and very much understandable.
ConsThere are not much negative of this library but it restrict you to a level of abstraction. If you need to write each bit of your algorithm and customise that then it's better to use tensorflow directly. Other than that it's amazing
Reviewer Source 
Source: Capterra
January 2, 2019
Marcin S.
CTO
Medical Devices, 11-50 employees
Used the software for: 1-2 years
Overall Rating
4/5
Ease of Use
2/5
Features
4/5
Likelihood to Recommend
7/10
Reviewer Source 
Source: Capterra
April 12, 2018

“Nice framework fo NNs”

ProsA lot of built-in layer types, easy way to connect them. Our team is using it with Theano and TensorFlow
ConsSometimes you need to do something more complex and Keras is not able to handle it. It is the second you need to switch to Lasagne.
Reviewer Source 
Source: Capterra
April 12, 2018
Verified Reviewer
Computer Software, Self-employed
Used the software for: 1-2 years
Overall Rating
4/5
Ease of Use
3/5
Features
3/5
Likelihood to Recommend
8/10
Reviewer Source 
Source: Capterra
July 18, 2019

“Best library to make your own neural network model”

OverallI used it to do my final year research project
ProsIt helped to create my own neural network model easily without trouble with tensorflow codes.
ConsSome commonly used features are not available
Reviewer Source 
Source: Capterra
July 18, 2019
Avatar Image
Victor E. I.
Data scientist /Programmer
Computer Software, 11-50 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
3/5
Features
5/5
Value for Money
3/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
June 21, 2019

“Keras”

ProsA high level framework built on Tensorflow, makes writing deep learning codes fun
ConsIt automatically loads all the dataset to ram, meaning you need have sufficient computational capacity
Reviewer Source 
Source: Capterra
June 21, 2019
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Gaurav Y.
Software Developer
201-500 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
5/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
July 26, 2018

“Best wrapper library for tensor flow”

OverallBest wrapper library for Theano and Tensorflow
ProsI think keras is the best wrapper library for tensor flow. Writing the neural network and other deep learning algorithm in tensorflow is a bit difficult. But with the use of writing all those is very easy. Like you can add convolution layer in just one line. You don't have to worry about the dimension of weight matrix of bias vector, Keras take care of that most of the time.
ConsI think it doesn't have any drawbacks. But one think is that if you want to write your own implementation then you have to go back to tensor flow.
Reviewer Source 
Source: Capterra
July 26, 2018
Verified Reviewer
Computer Software, Self-employed
Used the software for: 6-12 months
Overall Rating
4/5
Ease of Use
4/5
Customer Service
4/5
Features
3/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
September 15, 2019

“Keras is a best library to build our own neural network model”

OverallI have used it to build the convolutional neural network model for my research project.
ProsWe can build our own neural network architecture using keras without complex codings. The library make it easy to do.
ConsSince it doesn't have some useful functionalities and continuously updated. And some times have version problems when we use tensorflow.
Reviewer Source 
Source: Capterra
September 15, 2019
Zac L.
Data Scientist
Farming, 5001-10,000 employees
Used the software for: 2+ years
Overall Rating
5/5
Ease of Use
5/5
Features
4/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
July 23, 2019

“Build deep learning prototypes fast”

ProsKeras allows you to build deep learning models easy and fast using TensorFlow backend, good for beginners in machine learning; Keras also provides several pre-trained models and can implement transfer learning easily.
ConsIf you need to build a more customized deep learning model, should code in TensorFlow directly.
Reviewer Source 
Source: Capterra
July 23, 2019
Verified Reviewer
Computer Software, 51-200 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
5/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
March 7, 2018

“A great python library for deep learning - used extensively by our innovation team.”

OverallKeras is one of the only real solutions to deep learning and looks great doing it. This is an extensible and very effective solution to building complex machine learning models.
ProsKeras is the best library for deep learning machine learning models. It is modular, minimalist and extensible. Python really is the future for machine learning models. It is fast and very advanced in its capability.
ConsLearning curve is intense, this is to be expected with emerging technologies so that is the least of our concerns.
Reviewer Source 
Source: Capterra
March 7, 2018
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Rashmi ..
UI Developer
Information Technology and Services, 201-500 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
5/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
January 13, 2019

“an efficient wrapper library for deep learning”

OverallIt has provided a easy way to implement machine learning algorithm
ProsKeras supports the TensorFlow as it's backend so you can do almost everything with Keras as well. Along with this, It had made it easy to write and implement the deep learning algorithm. Also, it comes with lot of data processing tool.
ConsOnly negative is that it restricts you to it's own way of writing and implementing algorithm. you can do much of customisation over it, for that you should use Tensorflow directly.
Reviewer Source 
Source: Capterra
January 13, 2019
Verified Reviewer
Financial Services, 10,001+ employees
Used the software for: 6-12 months
Overall Rating
5/5
Ease of Use
5/5
Customer Service
4/5
Features
4/5
Value for Money
5/5
Likelihood to Recommend
8/10
Reviewer Source 
Source: Capterra
August 27, 2019

“Makes machine learning easy”

OverallSolved machine learning projects using Keras. Made it really easy to get started and learning about what I need to do
ProsIt can sit on top of Tensorflow so you dont have to deal with the annoying low level stuff to implement widely used machine learning algorithms and networks. Makes it really easy and fast to get started with machine learning projects.
ConsIt is very focused on the front-end so customization is a huge pain because most things are implemented according to what is popular e.g. specific network architectures.
Reviewer Source 
Source: Capterra
August 27, 2019
Avatar Image
Sheikh A.
CTO
Electrical/Electronic Manufacturing, 11-50 employees
Used the software for: 1-2 years
Overall Rating
4/5
Ease of Use
4/5
Customer Service
4/5
Features
4/5
Value for Money
4/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
September 30, 2019

“Versatile deep learning library paired with TensorFlow”

OverallWe have used Keras for deep learning projects for the ease is gives to new learners.
ProsProvides wide array of neural network tools. Helpful for AI, computer vision, signal processing, etc. projects in many sectors.
ConsSometimes, the Keras implementation included within TensorFlow needs to be replaced by the actual Keras.
Reviewer Source 
Source: Capterra
September 30, 2019
Verified Reviewer
Higher Education, 10,001+ employees
Used the software for: Less than 6 months
Overall Rating
5/5
Ease of Use
5/5
Features
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
August 24, 2018

“Best python library for Convolutional Neural Networks”

ProsKeras is a Python wrapper library around Google's machine learning framework Tensorflow, and it's so good such that Tensorflow now has a Keras implementation. Keras's syntax is very straightforward and easy to pick up, which simplifies the process of building neural networks and makes other people's code very interpretable. NNs are often complex and require a lot of tweaking get right, and the way Keras is designed makes it easy to modify your models. Another obvious benefit is that since it's in Python, you can use other libraries such as Pandas and Scikit Learn concurrently with Keras. It also supports GPUs, which is a major plus when dealing with huge datasets.
ConsNothing! Maybe have more examples in their documentation that doesn't involve the MNIST dataset.
Reviewer Source 
Source: Capterra
August 24, 2018
Avatar Image
Daniel M.
Administrador de sistemas y Desarollo de Software
Unspecified
Used the software for: 6-12 months
Overall Rating
5/5
Ease of Use
5/5
Customer Service
4/5
Features
4/5
Value for Money
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
May 5, 2018

“Is great using a GPU to make fastest calculations.”

OverallI obtained calculations in real-time of facial expressions to complete a project. It make the development more robust and faster.
ProsI was using it in Python, with models trained, in a few lines of code i obtained data with a webcamera, the same code worked with CPU and GPU without make changes.
ConsWhen I use many models of tensor flow linked with keras, it's become a little slow and make need use of GPU to obtain 10fps with a GTX 1050 Ti
Reviewer Source 
Source: Capterra
May 5, 2018
Verified Reviewer
Education Management, 201-500 employees
Used the software for: Less than 6 months
Overall Rating
4/5
Ease of Use
3/5
Features
4/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
July 27, 2019

“Very useful for data analysis”

OverallUsing Keras for my research. It took me a long time to feel comfortable but now it seems smooth. I love working with Python.
ProsIt is free and open-source. It works on Python. Many free tutorials and videos online to learn!
ConsHas a very long learning curve. It needs a long time to make something big without any help.
Reviewer Source 
Source: Capterra
July 27, 2019
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Sadiq A.
Student
Computer Software, 1-10 employees
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Customer Service
4/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
May 16, 2019

“Keras review ”

ProsIt's very functional for deep learning project, it's pythonic
ConsKeras is a front end framework which has tensorflow as it's backend
Reviewer Source 
Source: Capterra
May 16, 2019
Verified Reviewer
Research, 1001-5000 employees
Used the software for: 6-12 months
Overall Rating
5/5
Ease of Use
5/5
Features
4/5
Likelihood to Recommend
8/10
Reviewer Source 
Source: Capterra
August 8, 2018

“Really easy for a programming novice”

ProsThe API and the documentation is really easy to understand. It's great to use for someone with not an extensive programming experience.
ConsIf they could add the dynamic graph creations like in pytorch, it'd be great!
Reviewer Source 
Source: Capterra
August 8, 2018
Verified Reviewer
Marketing and Advertising, 51-200 employees
Used the software for: Less than 6 months
Overall Rating
5/5
Ease of Use
5/5
Features
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
August 2, 2018

“Keras is the go-to tool for deep learning”

ProsI like how easy to use this tool is and how it can run in conjunction with a number of other products like MCT, Theano, etc.
ConsThere isn't anything I dislike about it to be honest - I think it's the leading tool for deep learning in Python!
Reviewer Source 
Source: Capterra
August 2, 2018
Avatar Image
Wechuli P.
Software Engineer
Computer Software, 1001-5000 employees
Used the software for: 6-12 months
Overall Rating
5/5
Ease of Use
4/5
Customer Service
3/5
Features
4/5
Value for Money
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
September 10, 2019

“Great for Beginning Deep Learning”

OverallI have found Keras very simple and intuitive to start with and is a great place to start learning about deep learning.
Pros- Open source and absolutely free - Easy to use and get started with - Excellent documentation and community support - Can work with several deep learning frameworks such as Tensor Flow and CNTK
Cons- Since it relies on other deep learning frameworks such as Tensorflow, some functionalities may lack on the Keras API that are present in the underlying framework - Needs some initial setup which might be difficult - Does not play well with Windows
Reviewer Source 
Source: Capterra
September 10, 2019
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Rohit G.
Graduate Research Assistant
Research, 51-200 employees
Used the software for: 6-12 months
Overall Rating
5/5
Ease of Use
5/5
Customer Service
5/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
February 20, 2019

“State of the art open source library for Deep Learning”

OverallKeras is a strong wrapper library for TensorFlow and developing DL models with Keras is easy with only a few lines of code.
ProsI have used Keras to train CNNs and RNNs in Python. Overall, developing DL models with Keras is much simpler than with TensorFlow and requires fewer lines of code. It supports TensorFlow as it is a wrapper library for TensorFlow and Theano
ConsLinking TensorFlow DL models with Keras can get complicated sometimes and it is better to use TensorFlow directly
Reviewer Source 
Source: Capterra
February 20, 2019
Verified Reviewer
Higher Education, 5001-10,000 employees
Used the software for: Less than 6 months
Overall Rating
4/5
Ease of Use
4/5
Features
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
September 26, 2019

“Neural network library for anyone to learn”

OverallI used Keras to design and train a convolutional neural network model.
ProsKeras is a very good neural network library with much more easier API when compared to other neural network libraries available which makes it easier to anyone who is at the beginning of machine learning and neural networks. Keras also integrates with TensorFlow which helps user to work the data flows.
ConsKeras documentation is not user friendly which makes users to find alternative explanations and examples.
Reviewer Source 
Source: Capterra
September 26, 2019
Avatar Image
Vahid A.
Research Assistant
Higher Education, Self-employed
Used the software for: 1-2 years
Overall Rating
5/5
Ease of Use
5/5
Features
5/5
Likelihood to Recommend
10/10
Reviewer Source 
Source: Capterra
July 21, 2019

“A great deep learning package”

ProsI used this package for different deep learning projects so far. It is very easy to learn with a wide variety of useful commands.
ConsI can mention that nothing is wrong with this package.
Reviewer Source 
Source: Capterra
July 21, 2019
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Aanu B.
Computer Engineering Student
Computer Software, Self-employed
Used the software for: 6-12 months
Overall Rating
4/5
Ease of Use
5/5
Customer Service
3/5
Features
5/5
Value for Money
5/5
Likelihood to Recommend
9/10
Reviewer Source 
Source: Capterra
May 16, 2019

“Making Machine Learning Easier”

OverallWhile building an image classifier with Keras for a hackathon, I was able to start from a beginner level and end up winning the competition due to the ease of use
ProsComputational graph is dynamic, which makes it very easy to work with.
ConsBecause it is built on a higher level API (TensorFlow), it reduces the speed during run time.
Reviewer Source 
Source: Capterra
May 16, 2019
Verified Reviewer
Higher Education, Self-employed
Used the software for: Less than 6 months
Overall Rating
3/5
Ease of Use
3/5
Features
3/5
Likelihood to Recommend
6/10
Reviewer Source 
Source: Capterra
April 12, 2019

“Keras for school project”

ProsI did use this library couple of times during the semester to solve my deep learning course home works and project. compared to tensor flow it was easier for me to use
ConsIt was not still easy to use and well documented with examples
Reviewer Source 
Source: Capterra
April 12, 2019