Software Alternatives, Accelerators & Startups
Register | Login

SAS JMP VS Amazon Machine Learning

Compare SAS JMP VS Amazon Machine Learning and see what are their differences

SafeBet.ai
Daily AI sports picks generated by artificial intelligence. SafeBet.ai helps you analyze all NBA, NFL, MLB, UFC and soccer games. It has a massive database by having analyzed all the games in the past 3 years. Use AI to improve your sports bets. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

SAS JMP logo SAS JMP

Interactive, visual statistical data analysis from SAS.

Amazon Machine Learning logo Amazon Machine Learning

Machine learning made easy for developers of any skill level
  • SAS JMP Landing page
    Landing page //
    2023-03-31
  • Amazon Machine Learning Landing page
    Landing page //
    2023-03-13

SAS JMP features and specs

  • User-Friendly Interface
    JMP has an intuitive drag-and-drop interface that makes it accessible for users who might not be well-versed in programming, allowing them to perform complex analyses without writing code.
  • Interactive Data Visualization
    JMP offers powerful interactive data visualization tools that allow users to explore data dynamically, making it easier to identify patterns and insights.
  • Comprehensive Statistical Tools
    The software provides a wide range of statistical analyses, from basic descriptive statistics to advanced multivariate methods, suitable for various research and business needs.
  • Integration Capabilities
    JMP can integrate with other tools and software, such as R and Python, allowing users to extend its functionality and incorporate external scripts and functions.
  • Strong Support and Community
    SAS offers robust customer support and JMP has an active user community, providing resources and assistance to help users maximize their use of the software.

Possible disadvantages of SAS JMP

  • Cost
    JMP is a commercial product and can be quite expensive, which might be a barrier for small businesses or individual users with limited budgets.
  • Learning Curve
    While JMP is user-friendly, mastering all its features and functionalities can require time and training, particularly for users new to statistical software.
  • Limited Advanced Customization
    For users who require deep customization or need to perform highly specialized analyses, JMP's offerings might be limiting compared to more flexible platforms like R.
  • Resource Intensive
    JMP can be resource-intensive, requiring significant system resources and potentially causing performance issues on less powerful hardware.
  • Proprietary Software
    Being proprietary software, users do not have access to its source code, limiting the ability to modify or optimize the software beyond what is allowed by SAS.

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.

Analysis of Amazon Machine Learning

Overall verdict

  • Amazon Machine Learning is a good fit for businesses that need a reliable cloud-based machine learning platform, especially those already utilizing AWS services. Its scalability and integration capabilities make it suitable for a wide range of machine learning tasks.

Why this product is good

  • Amazon Machine Learning offers scalable solutions integrated with AWS services, making it a strong choice for users already within the AWS ecosystem. Its tools are built to handle large datasets and provide robust infrastructure, contributing to ease of deployment and management. Additionally, the service enables developers and data scientists to build sophisticated models without requiring deep machine learning expertise.

Recommended for

  • Developers and data scientists seeking seamless integration with AWS cloud services.
  • Organizations handling large-scale data analyses and machine learning projects.
  • Enterprises that prioritize scalability and flexibility in their machine learning operations.
  • Teams looking for a platform that supports both novice and expert users with varying levels of machine learning expertise.

SAS JMP videos

No SAS JMP videos yet. You could help us improve this page by suggesting one.

Add video

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 SAS JMP and Amazon Machine Learning)

SAS JMP

Amazon Machine Learning

Data Science And Machine Learning
18 18%
Data Science And Machine Learning
82% 82
AI
0 0%
AI
100% 100
Text Editors
100 100%
Text Editors
0% 0
Developer Tools
0 0%
Developer Tools
100% 100

User comments

Share your experience with using SAS JMP and Amazon Machine Learning. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Amazon Machine Learning seems to be more popular. It has been mentiond 2 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.

SAS JMP mentions (0)

We have not tracked any mentions of SAS JMP yet. Tracking of SAS JMP recommendations started around Mar 2021.

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 SAS JMP and Amazon Machine Learning, you can also consider the following products

Design-Expert - Design of Experiment software.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

Minitab - Minitab helps businesses increase efficiency and improve quality through smart data analysis.

Apple Machine Learning Journal - A blog written by Apple engineers

Develve - Statistical software for fast and easy interpretation of experimental data in science and R&D...

Lobe - Visual tool for building custom deep learning models

Loading...