Microsoft Azure Machine Learning for Data Scientist

Dipam Goswami
Jun 17 · 3 min read

Well, as we all know that data science is a vast field covering multiple disciplines using various scientific methods and algorithms to extract insights from data, be it structured or unstructured, it is a very difficult task to learn and master it. It requires a lot of hands-on practice.

I will be discussing in details about the Microsoft Azure technologies which I have personally explored and found amazing.


Azure Machine Learning Studio:

Machine Learning Studio is a powerful browser-based, visual drag-and-drop environment where no coding is required. It is a completely free tool designed for applied machine learning, which you can try out different types of machine learning algorithms, once your data is prepared. It is a fully-managed cloud service that allows you to build, deploy and share predictive and analytic solutions. It is a completely GUI tool and all you need to do is pull and drop.


Azure Machine Learning Service:

Here, you can rapidly build and deploy machine learning models using various tools and a visual drag-and-drop interface. You can get built-in support for widely used open-source frameworks, including Python, PyTorch, ONNX, scikit-learn and TensorFlow. When I started doing my project, One thing that bothered me a lot was downloading the various heavy libraries and their dependencies which popped up a number of times. Thats where Azure Machine Learning Service comes to rescue and helps you to focus on the things that really matters without any obstacles. MLOps (DEvOps for machine learning) streamlines the entire lifecycle, from preparing the data to deployment and monitoring.


The Azure Data Science Virtual Machine for Linux is an Ubuntu-based virtual machine that makes it simple to start with deep learning on Azure. The Microsoft Cognitive Toolkit, TensorFlow, Chainer, NVIDIA DIGITS,Torch, PyTorch, Caffe, Caffe2, MXNet, Deep Water, Keras and Theano are built, installed and configured, which is ready to run immediately. Many Jupyter notebooks are also included.

Microsoft Azure ML is a great experience and you can also try building your applications using it.

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