SafeBet.ai
IBM Watson Studio
TensorFlow
Alteryx
Pega Platform
RapidMiner
Azure Machine Learning Studio
Salesforce Einstein
MATLAB
Amazon SageMaker
TensorFlow
Azure Machine Learning Studio
Pega Platform
Deepnote
GeoSpock
Salesforce Einstein
Saturn Cloud
IBM Watson Studio| Categories |
|
|---|---|
| Website | ibm.com |
Amazon SageMaker| Categories |
|
|---|---|
| Website | aws.amazon.com |
Based on our record, Amazon SageMaker seems to be more popular. It has been mentiond 35 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.
At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 13 days ago
Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 3 months ago
Amazon and Azure already have much of what you're talking about in AWS SageMaker and Azure MLOps. Source: 11 months ago
And there have been several platforms that help fine-tune pretrained models, such as Google Cloud AutoML and Amazon Sagemaker. These tools are often fairly easy to use, but they come at a cost. They can be expensive, depending on the size of your dataset. Another option is Finetuner+, that also fine-tunes like AutoML and Sagemaker. The big advantage is that you don't need to transfer your data to other GPUs,... Source: 12 months ago
In this blog, you will see how to ingest audio/video feeds from any live recording camera into the AWS Kinesis Video Stream and apply various machine learning algorithms on the video stream to analyze these video feeds using Amazon SageMaker. We'll also use a few other services like Lambda, S3, EC2, IAM, ECS, CloudFormation, ECR, CloudWatch, etc. To power our model. Source: 12 months ago
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Alteryx - Alteryx provides an indispensable and easy-to-use analytics platform for enterprise companies making critical decisions that drive their business strategy and growth.
Azure Machine Learning Studio - Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.
Pega Platform - The best-in-class, rapid no-code Pega Platform is unified for building BPM, CRM, case management, and real-time decisioning apps.
RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
Deepnote - A collaboration platform for data scientists