EDUCBA

EDUCBA

MENUMENU
  • Free Tutorials
  • Free Courses
  • Certification Courses
  • 360+ Courses All in One Bundle
  • Login
Home Data Science Data Science Tutorials Head to Head Differences Tutorial TensorFlow vs Keras
Secondary Sidebar
TensorFlow Tutorial
  • Basics
    • Introduction to Tensorflow
    • What is TensorFlow?
    • Tensorflow Basics
    • TensorFlow Architecture
    • TensorFlow Versions
    • How to Install TensorFlow
    • Caffe TensorFlow
    • Tensorflow Image Classification
    • TensorFlow Playground
    • TensorFlow RNN
    • TensorFlow Models
    • TensorBoard
    • TensorFlow Debugging
    • TensorFlow vs Keras
    • Tensorflow LSTM
    • TensorFlow Probability
    • TensorFlow Session
    • TensorFlow Dataset
    • TensorFlow Reshape
    • TensorFlow estimator
    • TensorFlow Keras Model
    • TensorFlow Load Model
    • tensorflow transformer
    • tensorflow extended
    • tensorflow flatten
    • TensorFlow OpenCL
    • TensorFlow APIs
    • Tensorflow concatenate
    • Tensorflow variable
    • TensorFlow normalize
    • TensorFlow save model
    • TensorFlow placeholder
    • TensorFlow shape
    • TensorFlow Adam optimizer
    • TensorFlow dense
    • Tensorflow Quantum
    • TensorFlow Layers
    • TensorFlow Distributed
    • TensorFlow Profiler
    • TensorFlow Metrics
    • TensorFlow Transpose
    • TensorFlow Tensor To Numpy
    • TensorFlow Quantization
    • TensorFlow Regression
    • TensorFlow argmax
    • TensorFlow Federated
    • TensorFlow gather
    • TensorFlow Random Forest
    • Tensorflow sequential
    • TensorFlow expand_dims

Related Courses

TensorFlow Training Course

Machine Learning Courses

Artificial Intelligence Training Course

TensorFlow vs Keras

By Swati TawdeSwati Tawde

TensorFlow vs Keras

Difference Between TensorFlow vs Keras

Tensorflow is the most renowned library used for profound learning models in development. It has a massive and wonderful culture. Tensorflow is sufficient for the widespread popularity of the commits as well as the number of forks on the TensorFlow Github depository. But it is not so easy to use TensorFlow. On the other hand, Keras is a TensorFlow based High-Level API. It is simpler to use as compared to Tensorflow. How are the two differences, when Keras is installed on the top of Tensorflow? And why should I ever use Tensorflow for deeper learning models, if Keras is more user-friendly? The points below will clarify which one to choose from.

What is Keras?

Keras is a high-level profound learning Python library commonly used to create neural networks to solve complex challenges by data scientists. The higher level API means Keras can serve as a front end and Theano or Tensor-flow can be used as a rear end. When implementing deep neural networks, Keras promotes the research of data scientists. It is highly popular with its broad, easy to understand API. Documentation is very clear to everyone to start. The other thing is the higher level API can be used. This means that it can act as an interface for the TensorFlow, Theano, etc.

What is Tensorflow?

Today, Google’s TensorFlow is the world-famous profound computing library. The products used to improve search engines, translations, subtitling or recommendations by Google use machine learning in all its Products. Google has not only data; it has the largest computer in the world, which means that it was built to scale Tensor Flow. TensorFlow is a Google Brain project library to speed up machine learning and research into deep neural networks. Designed to run with several CPUs and GPUs, it has several wrappers, in several languages such as C++, Python or Java.

Head to Head Comparison between TensorFlow vs Keras (Infographics)

Below are the top 7 differences between TensorFlow vs Keras:

Start Your Free Data Science Course

Hadoop, Data Science, Statistics & others

All in One Data Science Bundle(360+ Courses, 50+ projects)
Python TutorialMachine LearningAWSArtificial Intelligence
TableauR ProgrammingPowerBIDeep Learning
Price
View Courses
360+ Online Courses | 50+ projects | 1500+ Hours | Verifiable Certificates | Lifetime Access
4.7 (86,294 ratings)

TensorFlow vs Keras info

Key Differences Between TensorFlow vs Keras

The key differences between a TensorFlow vs Keras are provided and discussed as follows:

  • Keras is a high-level API that runs on TensorFlow. For its simple usability and its syntactic simplicity, it has been promoted, which enables rapid development.
  • The performance of Keras is comparatively slow, while Tensorflow delivers a similar pace that is fast and efficient.
  • The architecture of Keras is plain. It is easier to read and briefer. On the other hand, TensorFlow is not easy to use, although it provides Keras as a system that facilitates working.
  • For keras, the debugging of simple networks is typically much less difficult. Whereas, debugging is very difficult for Tensorflow.
  • Keras is usually used as a slower comparison with small datasets. TensorFlow, on the other hand, is used for high-performance models and large data sets requiring rapid implementation.

TensorFlow vs Keras Comparison Table

Let’s discuss the top comparison between TensorFlow vs Keras:

TensorFlow

Keras

Tensorflow is a low-level architecture API. Keras is a High-level architecture API.
TensorFlow is not comparatively easy to use. It is more user friendly and easy to use as compared to TensorFlow.
Radio prototyping is not feasible in Tensorflow. In Keras, Radio prototyping means building simple or complex neural networks can be done within a few minutes.
TensorFlow provides more advanced operations as compared to Keras. Keras provides various general-purpose functionalities for building Deep learning models.
The architecture of TensorFlow is complex. The architecture of Keras is Simple. It is easier to understand.
Debugging is difficult in Tensorflow. Debugging is easier in Keras.
TensorFlow is used for high-performance models and large data sets which requires rapid implementation. Keras has small datasets.

Among these two systems, there are many variations. Keras is an open-source library for a number of different tasks during machine learning while TensorFlow is an open-source library. TensorFlow provides high and low-level APIs, while Keras only supplies high-level APIs. Tensorflow’s robust execution makes it possible to instantly iterate with intuitive debugging In terms of flexibility. All frameworks, therefore, promote the creation and training of high-level API models. Keras has a Python design that makes it much easier to use than TensorFlow.

Recommended Articles

This is a guide to the top difference between TensorFlow vs Keras. Here we also discuss TensorFlow vs Keras board key differences with infographics and comparison table. You may also have a look at the following articles to learn more –

  1. TensorFlow RNN
  2. TensorFlow vs Caffe
  3. TensorFlow vs Spark
  4. Tensorflow Image Classification
Popular Course in this category
TensorFlow Training (11 Courses, 3+ Projects)
  11 Online Courses |  3 Hands-on Projects |  55+ Hours |  Verifiable Certificate of Completion
4.5
Price

View Course

Related Courses

Data Scientist Training (85 Courses, 67+ Projects)4.9
Tableau Training (8 Courses, 8+ Projects)4.8
Azure Training (6 Courses, 5 Projects, 4 Quizzes)4.7
Hadoop Training Program (20 Courses, 14+ Projects, 4 Quizzes)4.7
Data Visualization Training (15 Courses, 5+ Projects)4.7
All in One Data Science Bundle (360+ Courses, 50+ projects)4.7
0 Shares
Share
Tweet
Share
Primary Sidebar
Footer
About Us
  • Blog
  • Who is EDUCBA?
  • Sign Up
  • Live Classes
  • Corporate Training
  • Certificate from Top Institutions
  • Contact Us
  • Verifiable Certificate
  • Reviews
  • Terms and Conditions
  • Privacy Policy
  •  
Apps
  • iPhone & iPad
  • Android
Resources
  • Free Courses
  • Database Management
  • Machine Learning
  • All Tutorials
Certification Courses
  • All Courses
  • Data Science Course - All in One Bundle
  • Machine Learning Course
  • Hadoop Certification Training
  • Cloud Computing Training Course
  • R Programming Course
  • AWS Training Course
  • SAS Training Course

ISO 10004:2018 & ISO 9001:2015 Certified

© 2022 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA
Free Data Science Course

SPSS, Data visualization with Python, Matplotlib Library, Seaborn Package

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA Login

Forgot Password?

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA
Free Data Science Course

Hadoop, Data Science, Statistics & others

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

Let’s Get Started

By signing up, you agree to our Terms of Use and Privacy Policy.

This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy

Loading . . .
Quiz
Question:

Answer:

Quiz Result
Total QuestionsCorrect AnswersWrong AnswersPercentage

Explore 1000+ varieties of Mock tests View more