Software Alternatives & Reviews

Amazon Rekognition VS Scikit-learn

Compare Amazon Rekognition VS Scikit-learn and see what are their differences

Amazon Rekognition logo Amazon Rekognition

Add Amazon's advanced image analysis to your applications.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Amazon Rekognition Landing page
    Landing page //
    2023-04-18
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Amazon Rekognition videos

AWS Rekognition Tutorial | Image Recognition using AWS | Amazon Rekognition | AWS Training | Edureka

More videos:

  • Review - Extract Data from Images and Videos with Amazon Rekognition (Level 300)
  • Demo - Can Amazon's Facial Recognition identify my 15 years younger picture? | Amazon Rekognition Demo

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to Amazon Rekognition and Scikit-learn)
Image Analysis
100 100%
0% 0
Data Science And Machine Learning
Machine Learning
100 100%
0% 0
Data Science Tools
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 Amazon Rekognition and Scikit-learn

Amazon Rekognition Reviews

2019 Examples to Compare OCR Services: Amazon Textract/Rekognition vs Google Vision vs Microsoft Cognitive Services
Pricing: Amazon Rekognition, Amazon Textract, Google, Microsoft. We don't really care which one you use, but Microsoft did best by our sample data. Textract was a very close second if you only need its headline feature: extracting text from digital documents. If someone wants to email bill -at- amplenote.com with comparable data for other images/services, I can try to...

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

Amazon Rekognition might be a bit more popular than Scikit-learn. We know about 33 links to it since March 2021 and only 27 links to Scikit-learn. 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.

Amazon Rekognition mentions (33)

  • Afraid of outgrowing AWS Rekognition? Try YOLO in Lambda.
    AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / about 1 month ago
  • Amazon Rekognition Custom Labels for Bears
    I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 9 months ago
  • “During a gold rush, sell shovels.” What are the shovels in the AI rush?
    For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 10 months ago
  • Serverless Facial Recognition Voting Application Using AWS Services
    Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / 12 months ago
  • Amazon Prime Video playback features
    Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago
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Scikit-learn mentions (27)

  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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What are some alternatives?

When comparing Amazon Rekognition and Scikit-learn, you can also consider the following products

Clarifai - The World's AI

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.

OpenCV - OpenCV is the world's biggest computer vision library

NumPy - NumPy is the fundamental package for scientific computing with Python

Kairos - Facial recognition & mood detection API