|Microsoft's Machine Learning for Beginners|
|Written by Nikos Vaggalis|
|Tuesday, 17 August 2021|
A free, self-paced online course about Machine Learning is on offer from Microsoft's Azure Cloud Advocates. Its 24-lesson curriculum, expected to take 12-weeks to complete is targeted at those new to Machine Learning.
There are plenty of advantages in attending Machine Learning for Beginners. First you learn about the, currently trending, concepts of ML, acquiring skills highly sought after by employees. On top of that you learn them in conjunction with Python, the most popular and versatile language, also highly sought after.
This role of the middleman between Python and Machine Learning is played by none other than scikit-learn, which is chosen for good reason. As I explained in "Introduction to Machine Learning with Scikit-Learn".
Python certainly is the most popular language of doing ML, mainly due to the number of relevant libraries available. scikit-learn is one of the top Machine Learning libraries alongside PyTorch, NumPy, SciPy, TensorFlow and Theano. Additionally, scikit-learn is one of the easiest to learn as such perfect for beginning one's ML journey. That doesn't mean that it lacks functionality though; it is perfectly capable of pulling off many ML tasks such as classification, clustering, pre-processing, regression, etc.
It is also important to note that the authors have made a clear distinction between Machine Learning and AI. This course is about "classic machine learning" and does not concern itself with artificial intelligence, something that its sibling course AI for Beginners covers. This separation of topics means that ML for Beginners is not as complicated as it otherwise would be.
With that out of the way let's focus on the course itself.
The course is hosted on GitHub with links to You Tube videos intermixed with the actual textual lessons and is comprised of 24 lessons:
It is evident from that list that the course teaches a lot of practical applications of ML, mostly focused on its data science side, such as:
However, if you're looking for the Neural Networks side of it then it's best to go with "AI for Beginners".
After going through it, you'll be looking for the next steps. The instructors advise that you continue with the forthcoming Data Science for Beginners and, as already mentioned, AI for Beginners.
All in all, this course offers a first class opportunity to start your journey in Machine Learning!
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|Last Updated ( Tuesday, 17 August 2021 )|