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• It allows users to build ML models without having to write any code.
• It simplifies the process of using machine learning by providing a visual, drag-and-drop interface along with
tools that support the entire machine learning lifecycle, from data preparation to model deployment.
• Whether you’re a beginner with no coding experience or an experienced data scientis, Azure’s diverse set of
features can help you effectively use machine learning in your projects.
It can be used for:
• Predictive Analytics: Predict future trends such as customer demand, sales forecasting, and inventory
management.
• Image and Speech Recognition: Train models to recognise images or speech for various applications like
medical imaging or voice assistants.
• Natural Language Processing (NLP): Build models for sentiment analysis, chatbots, and language
translation.
Google Cloud AutoML
Google Cloud AutoML is a suite of machine learning tools provided by Google Cloud that allows users to build
custom machine learning models with minimal coding experience. It was released in January 2018.
Google Cloud AutoML makes it easy for users who don’t have much knowledge of machine learning (ML) to create
powerful and accurate models tailored to their specific business needs, with very little effort.
With AutoML, users can quickly build their own custom machine learning models, even in just a few minutes.
Once the model is ready, they can deployed and integrated into their applications or websites, allowing them to
make predictions, automate tasks, or solve problems using AI—without needing to write complex code or be an
expert in machine learning. This simplifies the process and makes AI accessible to everyone, even those without a
technical background.
21 st Century #Media Literacy
Skills
Video Session
Watch this video on "Introducing Cloud AutoML" at the given ink:
https://www.youtube.com/watch?v=GbLQE2C181U or scan the QR code and answer
the following question:
What is the need for creating Cloud AutoML Vision?
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Orange Data Mining
Orange Data Mining was developed at the University of Ljubljana, Slovenia in October 1996. It is an open-source,
user-friendly data analysis and machine learning software suite. It provides a wide range of tools for data mining,
machine learning, data visualization, and statistical analysis. Orange is designed to be accessible to both beginners
and advanced users, and it is especially popular for those interested in exploring and analysing data with a visual
programming interface.
Brainy Fact
Orange Data Mining was initially designed for bioinformatics, helping researchers analyse biological data. Over
time, it evolved into a general-purpose data mining and machine learning tool used across various industries.
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