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Amazon AWS VS Scikit-learn

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

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Amazon AWS logo Amazon AWS

Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Amazon AWS Landing page
    Landing page //
    2022-01-29
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Amazon AWS features and specs

  • Scalability
    AWS offers highly scalable services, allowing businesses to easily adjust resources based on demand without significant upfront investment.
  • Comprehensive Service Offering
    AWS provides a wide range of services, from compute and storage to machine learning and analytics, catering to diverse business needs.
  • Global Reach
    With data centers located worldwide, AWS enables low-latency access and redundancy, supporting global operations.
  • Strong Security
    AWS has robust security measures, including compliance certifications, encryption, and physical security, ensuring data and infrastructure protection.
  • Pay-as-You-Go Pricing
    AWS offers a flexible pricing model, where users only pay for what they use, helping manage costs effectively.
  • Extensive Integration Options
    AWS integrates with a wide variety of third-party services and APIs, providing seamless integration capabilities for various applications.
  • Innovation
    AWS frequently releases new services and features, staying at the forefront of technology and providing users with cutting-edge tools.

Possible disadvantages of Amazon AWS

  • Cost Management Complexity
    While the pay-as-you-go model offers flexibility, it can be challenging to track and predict costs, especially for large-scale operations.
  • Learning Curve
    AWS has a comprehensive set of services and features, which can be overwhelming for new users to learn and manage effectively.
  • Potential Vendor Lock-In
    Relying heavily on AWS services may result in vendor lock-in, making it difficult to switch providers or migrate workloads in the future.
  • Service Limitations
    Certain AWS services might have limitations or restrictions, which could hinder specific use cases or require workarounds.
  • Support Costs
    AWS offers different support tiers, and premium support options can be expensive for businesses needing immediate and advanced technical assistance.
  • Performance Variability
    Performance can vary based on server load and geographic location, which may affect the consistency and reliability of certain services.
  • Complex Pricing Structure
    AWS's pricing structure can be complicated, with various pricing models and options making it hard to determine the most cost-efficient choice.

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Amazon AWS videos

+ Add

Amazon Web Services vs Google Cloud Platform - AWS vs GCP | Difference Between GCP and AWS

More videos:

  • Review - Are AWS Certifications worth it?
  • Review - AWS Certified Solutions Architect Associate Certification Will Get You Paid!

Scikit-learn videos

+ Add

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 AWS and Scikit-learn)

Amazon AWS

Scikit-learn

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

Amazon AWS Reviews

  1. macloughlin
    · AV engineer ·
    The best cloud platform out there

    You could say a lot of things about AWS, but among the cloud platforms (and I've used quite a few) AWS takes the cake. It is logically structured, you can get through its documentation relatively easily, you have a great variety of tools and services to choose from [from AWS itself and from third-party developers in their marketplace]. There is a learning curve, there is quite a lot of it, but it is still way easier than some other platforms. I've used and abused AWS and EC2 specifically and for me it is the best.

    👍 Pros:    Great documentation|Website structure visualization|You have control over everything|Flexibility
    👎 Cons:    Learning curve|A lot of dashboards for different things
Top 15 MuleSoft Competitors and Alternatives
API Gateway private endpoints allow AWS customers to use API endpoints inside their VPC. They can leverage Route 53 resolver endpoints and hybrid connectivity to access APIs and integrated backend services from on-premises clients.
Source: bstrategyhub.com
Best Dedicated Server Providers in India: A Comparative Analysis
Dedicated hosts on Amazon EC2 are physical servers that are completely dedicated to meeting corporate compliance standards. With AWS, you can create EC2 instances on a dedicated server. The flexibility offered by Amazon EC2 is definitely one of its biggest advantages, along with high scalability. Apart from that, it isn’t much better than dedicated servers.
Source: moralstory.org
Best Dedicated Server Providers for E-commerce Businesses in India
The dedicated server options from Amazon Web Services (AWS), a well-known brand in the tech industry, are equally excellent. AWS’s elastic infrastructure can smoothly adjust to your demands whether your e-commerce business encounters variable traffic or you expect quick development. AWS guarantees that the speed and performance of your website will always be unmatched thanks...
Source: pricealertbd.com
The Best Dedicated Server Operating System for UK-Based Business
Cloud computing behemoth AWS is renowned for its extensive infrastructure and scalability choices. You can make use of AWS’s numerous data centers, which are positioned strategically to offer low-latency services all across the UK.
Source: featurestic.com
The Best Dedicated Servers for Enterprise Businesses in India: Scalable and Reliable
The extensive selection of cloud-based solutions offered by AWS is one of its main advantages. AWS provides a wide range of cloud services, including computing power, storage choices, databases, machine learning, analytics tools, and dedicated servers. This adaptability enables businesses to create scalable, flexible, and affordable solutions customized to their needs.
Source: india07.in

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...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Amazon AWS seems to be a lot more popular than Scikit-learn. While we know about 443 links to Amazon AWS, we've tracked only 31 mentions of 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 AWS mentions (443)

  • How to Host an Express App on AWS EC2 with NGINX (Free Tier Guide)
    Sign in to your AWS account. If you’re new to AWS, you can sign up for the free tier to get started without any upfront cost. - Source: dev.to / 17 days ago
  • Understanding AWS Regions and Availability Zones: A Guide for Beginners
    Amazon Web Services (AWS) has completely changed the game for how we build and manage infrastructure. Gone are the days when spinning up a new service meant begging your sys team for hardware, waiting weeks, and spending hours in a cold data center plugging in cables. Now? A few clicks (or API calls), and yes — you've got an entire data center at your fingertips. - Source: dev.to / 11 days ago
  • AWS S3 Storage Classes Explained: Choosing the Right One
    Choosing the right AWS S3 storage class depends on how frequently you access your data and your cost constraints. - Source: dev.to / about 1 month ago
  • Deploy a Django Rest Api on AWS EC2 using Docker, NGINX, Gunicorn and GitHub Action.
    Let’s start by setting up an EC2 instance to deploy our application. To do this, and you’ll need to open an AWS account (if you don’t already have one). - Source: dev.to / 3 months ago
  • AWS Solution Architect Job Description: Roles, Skills & Responsibilities (2025)
    The demand for cloud computing expertise continues to soar, and at the heart of many successful cloud implementations is the AWS Solution Architect. Amazon Web Services (AWS) dominates the cloud market, making professionals who can design, build, and manage solutions on its platform highly sought after. But what exactly does this role entail? Understanding the typical AWS Solution Architect job description is... - Source: dev.to / 15 days ago
View more

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
  • 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 / about 1 year 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 / almost 2 years ago
View more

What are some alternatives?

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

DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.

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

Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.

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

Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.

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

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