Software Alternatives, Accelerators & Startups

AWS Fargate VS Scikit-learn

Compare AWS Fargate VS Scikit-learn and see what are their differences

AWS Fargate logo AWS Fargate

AWS Fargate is a compute engine for Amazon ECS and EKS that allows you to run containers without having to manage servers or clusters.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • AWS Fargate Landing page
    Landing page //
    2021-10-29
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

AWS Fargate videos

Deep Dive into AWS Fargate

More videos:

  • Tutorial - AWS Fargate Tutorial | AWS Tutorial For Beginners | AWS Certification Training | Edureka
  • Review - AWS Fargate - Running Dockerized Apps

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 AWS Fargate and Scikit-learn)
Developer Tools
100 100%
0% 0
Data Science And Machine Learning
Cloud Computing
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 AWS Fargate and Scikit-learn

AWS Fargate Reviews

Top 12 Kubernetes Alternatives to Choose From in 2023
For Container-as-a-Service (CaaS) Kubernetes alternatives, AWS Fargate is a great option. It is well-known for simplifying container management and deployment on AWS.
Source: humalect.com
Top 10 Best Container Software in 2022
Using AWS Fargate, you now don’t need to provision, configure, and scale cluster virtual machines to execute containers. This, in turn, eliminates the requirement to select server types, determine at what time to scale your clusters or optimize cluster packing.

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

Based on our record, AWS Fargate should be more popular than Scikit-learn. It has been mentiond 46 times since March 2021. 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.

AWS Fargate mentions (46)

  • A Brief History Of Serverless
    This model was so successful that we started to see others create competitors such as AWS Fargate and Azure Container Instances. - Source: dev.to / 8 days ago
  • Event-Driven Architecture on AWS
    Event Producers: Generate streams of events, which can be implemented using straightforward microservices with AWS Lambda (for serverless computing), Amazon DynamoDB Streams (to captures changes to DynamoDB tables in real-time), Amazon S3 Event Notifications (Notify when certain events occur in S3 buckets) or AWS Fargate (a serverless compute engine for containers). - Source: dev.to / 21 days ago
  • Lambda on hard mode: serverless HTTP in Rust
    I never had a case where cold starts mattered because either 1) it was the kind of service where cold starts intrinsically didnt matter, or 2) we generally had > 1 req/15mins meaning we always had something warm. 3) Also you can pay for provisioned capacity[1] if the cold start thing makes it worth the money, though also just look into fargate[2] if that's the case. [1]:... - Source: Hacker News / 2 months ago
  • Serverless Data Processor using AWS Lambda, Step Functions and Fargate on ECS (with Rust 🦀🦀)
    One great option in the serverless world for something like this is to run containers using AWS Fargate (https://aws.amazon.com/fargate/). Fargate is a service from AWS where you don't need to spin up or manage EC2 VMs to get access to compute. Also you don't need to pay for a container orchestration layer. You just provide a docker image and the specs of what you need to run it (cpu, ram, disk, etc) and AWS spins... - Source: dev.to / 4 months ago
  • Best Practices for Seamless EKS Cluster Upgrades with Fargate: A Hands-On Guide
    As cloud-native architectures evolve, managing Kubernetes clusters becomes pivotal for maintaining optimal performance and security. Amazon EKS, combined with Fargate for serverless pod execution, offers a powerful solution. In this guide, we'll delve into best practices for EKS cluster upgrades with Fargate, providing a hands-on approach to ensure a seamless transition. Let's embark on the journey of mastering... - Source: dev.to / 5 months ago
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Scikit-learn mentions (28)

  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago
  • 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: about 1 year 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: about 1 year 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
View more

What are some alternatives?

When comparing AWS Fargate and Scikit-learn, you can also consider the following products

Google Kubernetes Engine - Google Kubernetes Engine is a powerful cluster manager and orchestration system for running your Docker containers. Set up a cluster in minutes.

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

Kubernetes - Kubernetes is an open source orchestration system for Docker containers

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

Amazon ECS - Amazon EC2 Container Service is a highly scalable, high-performance​ container management service that supports Docker containers.

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