Video description
With the commercial successes of machine learning and cloud computing, many business people need just enough math to take advantage of open source frameworks for big data. This video course from Paco Nathan and Allen Day presents useful areas of advanced math in easy-to-digest morsels. If you’re familiar with high school Algebra 2 and basic statistics, you’re good to go.
You’ll learn newly introduced math concepts through business use cases, brief Python code examples, and lots of figures and illustrations. By the end of the course, you’ll understand how to leverage complex graphs, sparse matrices, Bayesian priors, optimization solvers, and other tools.
- Learn advanced math through simple equations and illustrations
- Get tangible examples such as Lego blocks for data workflows
- Explore the math examples through typical business use cases
- Understand how these concepts tie into common business frameworks
- Follow a case study of the Foobartendr.io company throughout the course
Table of Contents
Introduction
Introduction: Computational Thinking
Abstract Algebra
Abstract Algebra: Show Me the Monoid
Abstract Algebra: Data Workflows
Abstract Algebra: Functional Programming
Abstract Algebra: Performance Bottlenecks
Abstract Algebra: Monoids in Python
Abstract Algebra: Open Source Frameworks
Linear Algebra
Linear Algebra: The Red Pill
Linear Algebra: Linear Systems
Linear Algebra: Least Squares Approximation
Linear Algebra: Eigenvalues and Eigenvectors
Linear Algebra: Principal Component Analysis
Linear Algebra: Open Source Frameworks
Linear Algebra: Algebraic Graph Theory
Bayesian Statistics
Bayesian Statistics: Lies, Damn Lies Statistics, and Bayesian Statistics
Bayesian Statistics: Bayes Theorem
Bayesian Statistics: Algorithmic Modeling
Optimization
Optimization: Caterpillar Won’t Be Building a Social Network
Optimization: Gradient Descent
Optimization: Neural Networks
Optimization: Evolutionary Algorithms
Summary
Summary