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Before ML can be applied the key concepts of machine learning need to be discussed.
This training has no Python prerequisites. So first the basics of Python are covered.
In data science its crucial to deal with tables: Loading, manipulating, data quality checks, … Dataframes can help out with that, and in this module the two most important Python packages for data manipulation are inspected: Numpy and Pandas.
Some pictures express more than a 1000 words. This holds in data science as well, so visualizing data is a crucial data science skill. Matplotlib is the most popular library for this. But there are additional libraries which build further upon this.
Many business problems can be tackled by basic machine learning techniques. In this module the most common machine learning approaches such as linear regression and random forests are implemented, as well as model inspection.
Machine learning on a local machine and a small dataset is one thing, running this on larger datasets or more CPU-hungry techniques can become a challenge. Another problem is deploying your model: How can we easily call the resulting model from within other applications? Azure Machine Learning Services helps answering these questions.
From all the machine learning techniques there is one that gets popular for more challenging problems: Multiple layers of neural networks, better known as deep learning. For problems such as image recognition, speech understanding etc. this is currently the way to go. But it’s from a mathematical point of view a very challenging technique. In this module the basics of deep learning are introduced.
Data science converts data into insights by applying techniques from the field of artificial intelligence and machine learning. This field has received a lot of attention lately, resulting in a lot of possible techniques to tackle this problem. In this training you will gradually dive deeper in the use of Python and the Azure stack to apply machine learning on business data.
This course focusses on developers and data scientists who are considering the Azure stack for applying machine learning on their data. Prior knowledge of Python or machine learning is not needed to attend this training, but some basic coding skills are handy.