Machine Learning is a comprehensive technology, which requires statistics and programming knowledge. It is a trending technology, too, an eye-catching word. We choose Azure Machine Learning as the product, and research community, audience, and product.
DEV is a community of software developers getting together to help one another out.
In DEV community, users around the world share their content, including
- Tutorial
- Personal experience
- New idea
- Recommendation
- Hackathon
- ...
Machine Learning is one of Top topics in this community.
In this section, we will discuss audience's mindset and their facing problems.
From the posts and comments, we find our audiences have following mindsets:
- embrace new things
- want to learn new things
- willing to share
When it comes to machine learning, they think:
- machine learning is hard to learn, sometimes
- machine learning means well-paid job
We collect common problems our audiences face about machine learning:
- How to start machine learning path
- How to master so many algorithms and mathematical knowledge
- How use use these knowledge to solve real world problems
Our focused product is Azure Machine Learning. It is a cloud service for accelerating and managing the machine learning project lifecycle.
Azure Machine Learning provides three options to build and deploy models:
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Automated ML (UI): This is a no-code solution. Automated machine learning rapidly iterates over many combinations of algorithms and hyper-parameters to help you find the best model based on a success metric of your choosing.
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Designer (drag-n-drop): Azure Machine Learning designer is a drag-and-drop interface used to train and deploy models in Azure Machine Learning.
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Notebooks (Python): Notebooks enable you to transfer local workspace to cloud, and easily deploy the model.
- AWS