[ FreeCourseWeb ] Machine Learning & Data Science Foundations Masterclass (Updated 3 - 2021)

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[ FreeCourseWeb.com ] Machine Learning & Data Science Foundations Masterclass (Updated 3/2021)

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Duration: 6h 15m | Video: .MP4 1280x720, 30 fps(r) | Audio: AAC, 48000Hz, 2ch | Size: 2.18 GB
Genre: eLearning | Language: English
The Theoretical and Practical Foundations of Machine Learning. Master Matrices, Linear Algebra, and Tensors in Python
What you'll learn
Understand the fundamentals of linear algebra, a ubiquitous approach for solving for unknowns within high-dimensional spaces.
Manipulate tensors using the most important Python tensor libraries: NumPy, TensorFlow, and PyTorch
Possess an in-depth understanding of matrices, including their properties, key classes, and critical ML operations
Develop a geometric intuition of what's going on beneath the hood of ML and deep learning algorithms.
Be able to more intimately grasp the details of cutting-edge machine learning papers

Requirements
All code s will be in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples.
Familiarity with secondary school-level mathematics will make the class easier to follow along with. If you are comfortable dealing with quantitative information – such as understanding charts and rearranging simple equations – then you should be well-prepared to follow along with all of the mathematics.

Description
To be a good data scientist, you need to know how to use data science and machine learning libraries and algorithms, such as Scikit-learn, TensorFlow and PyTorch, to solve whatever problem you have at hand.

To be an excellent data scientist, you need to know how those libraries and algorithms work under the hood.

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[ FreeCourseWeb ] Machine Learning & Data Science Foundations Masterclass (Updated 3 - 2021)


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[ FreeCourseWeb ] Machine Learning & Data Science Foundations Masterclass (Updated 3 - 2021)


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