Azure Machine Learning - ML as a service from Microsoft

What can do:

Azure Machine Learning is an enterprise-grade AI service from Microsoft that enables the end-to-end machine learning lifecycle. It empowers data scientists and developers to build, deploy, and manage high-quality models faster and with confidence.

Top 5 Benefits:

  1. End-to-End Machine Learning Lifecycle: Azure Machine Learning supports the entire machine learning lifecycle, from data preparation to model deployment.
  2. Accelerated Time to Value: The platform accelerates time to value with industry-leading machine learning operations (MLOps), open-source interoperability, and integrated tools.
  3. Collaboration and Streamlining of MLOps: Azure Machine Learning enables quick ML model deployment, management, and sharing for cross-workspace collaboration and MLOps.
  4. Confidence in Development: The platform provides built-in governance, security, and compliance for running machine learning workloads anywhere.
  5. Responsible AI Design: Azure Machine Learning promotes responsible AI applications, enabling the building of explainable models using data-driven decisions for transparency and accountability.

Top 5 Use Cases:

  1. Data Labeling: Azure Machine Learning allows users to label training data and manage labeling projects.
  2. Data Preparation: The platform can be used with analytics engines for data exploration and preparation.
  3. Dataset Creation and Sharing: Users can access data and create and share datasets using Azure Machine Learning.
  4. Model Development and Deployment: Azure Machine Learning supports the development, deployment, and management of high-quality models.
  5. MLOps: The platform enables the streamlining of machine learning operations, promoting collaboration and efficiency.

Prompt type:

Analyse data


Azure Machine Learning enables end-to-end machine learning lifecycle with confidence.


Denis Williams@denis_williams
20 min ago
The token limit is for the whole chat, including history (as far as I know). You could combine all the summaries, save them in a DB, and feed the smaller summaries back in ChatGPT. Not sure if that will yield great results though. Maybe GPT-4 will improve?
Upvoted (25)
Denis Williams@denis_williams
50 min ago
How to use ChatGPT to build Business Ideas, Sites & Personal Projects?
Adam Blob@adam_blob
3 min ago
@Denis_Williams Congrats on the launch! Very interesting approach to an ever growing problem. Use ChatGPT Tutorial - A Crash Course on Chat GPT for Beginners.
Upvoted (76)