Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • RunPod Reviews & Ratings
    116 Ratings
    Company Website
  • Vertex AI Reviews & Ratings
    673 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    1,730 Ratings
    Company Website
  • Google Cloud Speech-to-Text Reviews & Ratings
    373 Ratings
    Company Website
  • BytePlus Recommend Reviews & Ratings
    1 Rating
    Company Website
  • Google AI Studio Reviews & Ratings
    4 Ratings
    Company Website
  • Qloo Reviews & Ratings
    23 Ratings
    Company Website
  • Snowflake Reviews & Ratings
    1,389 Ratings
    Company Website
  • Stack AI Reviews & Ratings
    16 Ratings
    Company Website
  • PESTBOSS Reviews & Ratings
    2 Ratings
    Company Website

What is Core ML?

Core ML makes use of a machine learning algorithm tailored to a specific dataset to create a predictive model. This model facilitates predictions based on new incoming data, offering solutions for tasks that would be difficult or unfeasible to program by hand. For example, you could create a model that classifies images or detects specific objects within those images by analyzing their pixel data directly. After the model is developed, it is crucial to integrate it into your application and ensure it can be deployed on users' devices. Your application takes advantage of Core ML APIs and user data to enable predictions while also allowing for the model to be refined or retrained as needed. You can build and train your model using the Create ML application included with Xcode, which formats the models for Core ML, thus facilitating smooth integration into your app. Alternatively, other machine learning libraries can be utilized, and Core ML Tools can be employed to convert these models into the appropriate format for Core ML. Once the model is successfully deployed on a user's device, Core ML supports on-device retraining or fine-tuning, which improves its accuracy and overall performance. This capability not only enhances the model based on real-world feedback but also ensures that it remains relevant and effective in various applications over time. Continuous updates and adjustments can lead to significant advancements in the model's functionality.

What is Amazon SageMaker Clarify?

Amazon SageMaker Clarify provides machine learning practitioners with advanced tools aimed at deepening their insights into both training datasets and model functionality. This innovative solution detects and evaluates potential biases through diverse metrics, empowering developers to address bias challenges and elucidate the predictions generated by their models. SageMaker Clarify is adept at uncovering biases throughout different phases: during the data preparation process, after training, and within deployed models. For instance, it allows users to analyze age-related biases present in their data or models, producing detailed reports that outline various types of bias. Moreover, SageMaker Clarify offers feature importance scores to facilitate the understanding of model predictions, as well as the capability to generate explainability reports in both bulk and real-time through online explainability. These reports prove to be extremely useful for internal presentations or client discussions, while also helping to identify possible issues related to the model. In essence, SageMaker Clarify acts as an essential resource for developers aiming to promote fairness and transparency in their machine learning projects, ultimately fostering trust and accountability in their AI solutions. By ensuring that developers have access to these insights, SageMaker Clarify helps to pave the way for more responsible AI development.

Media

Media

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Apple tvOS
Apple watchOS
Xcode

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Apple tvOS
Apple watchOS
Xcode

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Apple

Company Location

United States

Company Website

developer.apple.com/documentation/coreml

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/clarify/

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Popular Alternatives

Create ML Reviews & Ratings

Create ML

Apple

Popular Alternatives

UnionML Reviews & Ratings

UnionML

Union