Matematicapr

Complete Mathematics Masterclass

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What Will You Learn?

  • Understand the fundamentals of linear algebra and calculus, critical mathematical subjects underlying all of machine learning and data science
  • Manipulate tensors using all three of the most important Python tensor libraries: NumPy, TensorFlow, and PyTorch
  • How to apply all of the essential vector and matrix operations for machine learning and data science
  • Reduce the dimensionality of complex data to the most informative elements with eigenvectors, SVD, and PCA
  • Solve for unknowns with both simple techniques (e.g., elimination) and advanced techniques (e.g., pseudoinversion)
  • Appreciate how calculus works, from first principles, via interactive code demos in Python
  • Intimately understand advanced differentiation rules like the chain rule
  • Compute the partial derivatives of machine-learning cost functions by hand as well as with TensorFlow and PyTorch
  • Grasp exactly what gradients are and appreciate why they are essential for enabling ML via gradient descent
  • Use integral calculus to determine the area under any given curve
  • Be able to more intimately grasp the details of cutting-edge machine-learning papers
  • Develop an understanding of what’s going on beneath the hood of machine learning algorithms, including those used for deep learning

Course Content

Limits of functions

Derivatives in one dimension (Copy 1)

Integrals in one dimension (Copy 1)

Vectors in Cartesian coordinates (Copy 1)

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