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GitHub VS Amazon Machine Learning

Compare GitHub VS Amazon Machine Learning and see what are their differences

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GitHub logo GitHub

Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.

Amazon Machine Learning logo Amazon Machine Learning

Machine learning made easy for developers of any skill level
  • GitHub Landing page
    Landing page //
    2023-10-05
  • Amazon Machine Learning Landing page
    Landing page //
    2023-03-13

GitHub

Website
github.com
Pricing URL
Official GitHub Pricing
$ Details
Release Date
2008 January
Startup details
Country
United States
State
California
City
San Francisco
Founder(s)
Chris Wanstrath
Employees
500 - 999
Edit details

Amazon Machine Learning

Website
aws.amazon.com
Pricing URL
-
$ Details
-
Release Date
-
Edit details

GitHub features and specs

  • collaboration
    GitHub provides a platform for multiple developers to work on the same project concurrently, facilitating collaboration through features like pull requests, code reviews, and issues tracking.
  • integration
    GitHub integrates seamlessly with various third-party tools and services, such as CI/CD pipelines, project management tools, and many development environments, enhancing productivity and workflow efficiency.
  • version_control
    Utilizes Git for version control, allowing users to track changes, revert to previous versions if necessary, and manage different branches of development, ensuring code stability and history tracking.
  • community
    With millions of developers and a vast repository of open-source projects, GitHub fosters a robust community where users can contribute to projects, seek help, share knowledge, and collaborate broadly.
  • availability
    GitHub is a cloud-based platform, which means that projects are accessible from anywhere with an internet connection, providing flexibility and convenience to developers globally.
  • documentation
    GitHub allows for comprehensive project documentation through README files, wikis, and GitHub Pages, making it easier for users to understand project context and contribute effectively.

Possible disadvantages of GitHub

  • cost
    While GitHub offers free plans, more advanced features and private repositories come at a cost, which might be a barrier for some individuals or small teams.
  • steep_learning_curve
    For newcomers, especially those unfamiliar with Git, the learning curve can be quite steep, making it challenging to utilize all of GitHub's features effectively.
  • privacy_concerns
    Given its expansive, open nature, users must be cautious with sensitive or proprietary information. Even with private repositories, there is a latent concern over data privacy and security.
  • interface_complexity
    The user interface, while powerful, can be overwhelming and complex for beginners or those not deeply familiar with version control concepts.
  • performance_issues
    Occasionally, GitHub may experience downtime or performance issues, which can disrupt workflow and prevent access to repositories temporarily.
  • limited_storage
    GitHub imposes limitations on storage space and file size within repositories, which can be restrictive for projects requiring large datasets or binaries.

Amazon Machine Learning features and specs

  • Scalability
    Amazon Machine Learning can handle increased workloads easily without significant changes in the infrastructure, making it ideal for growing businesses.
  • Integration with AWS
    Seamlessly integrates with other AWS services like S3, EC2, and Lambda, simplifying data storage, processing, and deployment.
  • Ease of Use
    User-friendly AWS Management Console and APIs make it easier for developers to build, train, and deploy machine learning models without needing deep ML expertise.
  • Performance
    Offers high-performance computing capabilities that can accelerate the training and inference processes for machine learning models.
  • Cost-Effective
    Pay-as-you-go pricing model ensures that you only pay for what you use, making it a cost-effective solution for various ML needs.
  • Prebuilt AI Services
    Provides prebuilt, ready-to-use AI services like Amazon Rekognition, Amazon Comprehend, and Amazon Polly, which simplify the implementation of complex ML solutions.

Possible disadvantages of Amazon Machine Learning

  • Complexity
    While the service is designed to be user-friendly, the underlying complexity of Machine Learning algorithms and models can be a barrier for novice users.
  • Vendor Lock-In
    Using Amazon Machine Learning extensively may lead to dependency on AWS services, making it difficult to switch providers or integrate with non-AWS services in the future.
  • Cost Management
    Although pay-as-you-go is cost-effective, if not managed properly, costs can quickly escalate especially with extensive use and large-scale data processing.
  • Limited Customization
    Prebuilt models and services may lack the level of customization needed for highly specialized use-cases requiring unique algorithms or configurations.
  • Data Privacy
    Storing and processing sensitive data on an external service may raise concerns regarding data privacy and compliance with data protection regulations.
  • Learning Curve
    Despite its ease of use, there is still a learning curve associated with mastering the AWS ecosystem and effectively utilizing its machine learning capabilities.

GitHub videos

+ Add

How to do coding peer reviews with Github

More videos:

Amazon Machine Learning videos

+ Add

Introduction to Amazon Machine Learning - Predictive Analytics on AWS

More videos:

  • Tutorial - AWS Machine Learning Tutorial | Amazon Machine Learning | AWS Training | Edureka

Category Popularity

0-100% (relative to GitHub and Amazon Machine Learning)

GitHub

Amazon Machine Learning

Software Development
100 100%
Software Development
0% 0
AI
0 0%
AI
100% 100
Code Collaboration
100 100%
Code Collaboration
0% 0
Developer Tools
80 80%
Developer Tools
20% 20

User comments

Share your experience with using GitHub and Amazon Machine Learning. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare GitHub and Amazon Machine Learning

GitHub Reviews

  1. Reinhard
    · Boss at CLOUD Meister ·
    perfect 4 open Source
Best Forums for Developers to Join in 2025
GitHub Discussions is a communication forum for the community around an open source or internal project. Discussions enable fluid, open conversation in a public forum. Discussions are transparent and accessible, but they are not related to code.
Source: www.notchup.com
The Top 10 GitHub Alternatives
However, like any (human) product, the platform has its limits, downsides, and critics. GitHub has been barred by certain governments, and even if that isn’t exactly the company’s fault, the users are the ones limited from pushing their code. Another criticism concerns the price tag: some users have pointed out that GitHub’s pricing model is too inflexible. Moreover, some...
Source: www.wearedevelopers.com
Top 10 Developer Communities You Should Explore
GitHub also has an extensive API that allows it to integrate workflows seamlessly. Continuous integration, code review tools, and project management features make GitHub an essential tool for any developer, and the community aspect adds a layer of connectivity that enriches the overall experience.
Source: www.qodo.ai
Top 7 GitHub Alternatives You Should Know (2024)
FAQs: Are there any cloud source repositories similar to GitHub?Is there a free alternative to GitHub?
Source: snappify.com
Best GitHub Alternatives for Developers in 2023
We may earn from vendors via affiliate links or sponsorships. This might affect product placement on our site, but not the content of our reviews. See our Terms of Use for details. Looking for an alternative to GitHub? Check out our in-depth list of the best GitHub competitors, covering their features, pricing, pros, cons, and more.
Source: www.techrepublic.com

Amazon Machine Learning Reviews

We have no reviews of Amazon Machine Learning yet.
Be the first one to post

Social recommendations and mentions

Based on our record, GitHub seems to be a lot more popular than Amazon Machine Learning. While we know about 2253 links to GitHub, we've tracked only 2 mentions of Amazon Machine Learning. 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.

GitHub mentions (2253)

  • Building Your First AI Agent: A Practical Guide for Developers
    Def search_github_issues(repo, query, state="open"): # Your GitHub API code here return {"issues": [{"title": "Example issue", "number": 42, "url": "https://github.com/..."}]}. - Source: dev.to / 1 day ago
  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    This post provides a comprehensive exploration of India’s dynamic open source development ecosystem. It delves into historical context, core concepts, community building, practical applications, challenges, and future innovations. We discuss how talented developers, vibrant communities, and supportive government initiatives converge to power open source growth in India. The article also integrates additional... - Source: dev.to / 6 days ago
  • Free custom domain for your projects 😉
    Sign Up: If you don’t have an account, go to github.com and click “Sign up.” Follow the prompts to create a free account. - Source: dev.to / 6 days ago
  • Unlocking Opportunities: How to Become a Sponsored Developer
    Becoming a sponsored developer is a multifaceted journey that blends technical excellence with strategic branding, robust networking, and clear communication. Developers must invest in building a detailed portfolio, leveraging digital platforms like GitHub, Twitter, and LinkedIn to present their work. The process involves researching potential sponsors, tailoring proposals, and engaging both online and offline... - Source: dev.to / 6 days ago
  • 🔐How to Fix GitHub Authentication Failed: Switch from Password to Token or SSH
    Fatal: HttpRequestException encountered. An error occurred while sending the request. Username for 'https://github.com': abcd Remote: Support for password authentication was removed on August 13, 2021. Fatal: Authentication failed for 'https://github.com/test/cr/. - Source: dev.to / 9 days ago
View more

Amazon Machine Learning mentions (2)

  • Rant + Planning to learn full stack development
    There’s also the ML as a service (MLaaS) movement that lowers the barrier for common ML capabilities (eg image object detection and audio transcription). Basically, you use APIs. See: https://aws.amazon.com/machine-learning/. Source: over 2 years ago
  • Ask the Experts: AWS Data Science and ML Experts - Mar 9th @ 8AM ET / 1PM GMT!
    Do you have questions about Data Science and ML on AWS - https://aws.amazon.com/machine-learning/. Source: about 4 years ago

What are some alternatives?

When comparing GitHub and Amazon Machine Learning, you can also consider the following products

GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.

Apple Machine Learning Journal - A blog written by Apple engineers

VS Code - Build and debug modern web and cloud applications, by Microsoft

Lobe - Visual tool for building custom deep learning models

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