Machine Learning & Data Science Foundations Masterclass

Machine Learning & Data Science Foundations Masterclass

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 demos 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.

Who this course is for:

  • You use high-level software libraries (e.g., scikit-learn, Keras, TensorFlow) to train or deploy machine learning algorithms, and would now like to understand the fundamentals underlying the abstractions, enabling you to expand your capabilities
  • You’re a software developer who would like to develop a firm foundation for the deployment of machine learning algorithms into production systems
  • You’re a data scientist who would like to reinforce your understanding of the subjects at the core of your professional discipline
  • You’re a data analyst or A.I. enthusiast who would like to become a data scientist or data/ML engineer, and so you’re keen to deeply understand the field you’re entering from the ground up (very wise of you!)
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