Math for Intelligence

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• Causation vs. Correlation
• Dot Product
• Animated Math | Grant Sanderson @ 3blue1brown.com
• Google's Crash Course
• Introduction to Matrices and Matrix Arithmetic for Machine Learning | Jason Brownlee
• Brilliant.org
• Varient: Limits
• Probability Cheatsheet
• Neural Networks and Deep Learning - online book | Michael A. Nielsen
• Bloomberg Lectures
• Statistical Learning | T. Hastie, R. Tibshirani - Stanford
• Essential Math for Data Science:  ‘Why’ and ‘How’ | Tirthajyoti Sarkar
• Gentle Dive into Math Behind Convolutional Neural Networks | Piotr Skalski - Towards Data Science
• Fundamental Statistics Jupyter Notebook | Jon Tupitza

• Fundamentals:
  • Linear Algebra | MIT
  • Linear Algebra | Khan Academy
  • Statistics and Probability | Khan Academy
  • Differential Calculus | Khan Academy
  • Multivariable Calculus | Khan Academy

3blue1brown

• Animated Math | Grant Sanderson @ 3blue1brown.com
  • Essence of linear algebra
  • Essence of calculus

Explained

Dot Product

• Kernel Trick
• [1] Dot Product | Wikipedia]

Dot Product =

• Algebraically, the dot product is the sum of the products of the corresponding entries of the two sequences of numbers.
• Geometrically, it is the product of the Euclidean magnitudes of the two vectors and the cosine of the angle between them.

Take a moment to understand how the computation above is being done. We slide the orange matrix over our original image (green) by 1 pixel (also called ‘stride’) and for every position, we compute element wise multiplication (between the two matrices) and add the multiplication outputs to get the final integer which forms a single element of the output matrix (pink). Note that the 3×3 matrix “sees” only a part of the input image in each stride. In CNN terminology, the 3×3 matrix is called a ‘filter‘ or ‘kernel’ or ‘feature detector’ and the matrix formed by sliding the filter over the image and computing the dot product is called the ‘Convolved Feature’ or ‘Activation Map’ or the ‘Feature Map‘. It is important to note that filters acts as feature detectors from the original input image. | ujjwalkarn

Josh Starmer - StatQuest

• StatQuest

Gilbert Strang (MIT) - Linear Algebra

• MIT Open Courseware - Linear Algebra
• Gilbert Strang's Books
• YouTube Playlist