Interested in increasing your Machine Learning, Deep Learning expertise by effectively applying the mathematical skills?
Then, this course is for you.
With the growing learners of Machine Learning, Data Science, and Deep Learning.
The Common mistake by a data scientist is Applying the tools without the intuition of how it works and behaves.
Having the solid foundation of mathematics will help you to understand how each algorithm work, its limitations and its underlying assumptions.
With this, you will have an edge over your peers and makes you more confident in all the applications of Machine Learning, Data Science, and Deep Learning.
As a common saying:
It always pays to know the machinery under the hood, rather than being a guy who is just behind the wheel with no knowledge about the car.
Linear Algebra is one of the areas where everyone agrees to be a starting point in the learning curve of Machine Learning, Data Science, and Deep Learning.. Its basic elements Vectors and Matrices are where we store our data for input as well as output.
Any operation or Processing involving storing and processing the huge number of data in Machine Learning, Data Science, and Artificial intelligence, would mostly use Linear Algebra in the backend.
Courses : 4
Specification: Mathematics Linear Algebra for Machine Learning Data Science
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