Giter Club home page Giter Club logo

math-concepts's Introduction

Math Concepts

for Developers and base for machine learning algorithms

Links:
Khan Academy - online academy with videos
WolframAlpha - calculations online
statistika.bg - statistics basic concepts with videos btu.bg - statistics basic concepts matematika.bg - basic concepts with examples

More:
YouTube channel - 3Blue1Brown
Interesting Jupyter Notebooks

Binder

  • scientific method introduction;
  • solving linear equations and systems (the “slow” way);
  • trigonometry. Right triangle, unit circle, functions and graphs, identities;
  • high-School geometry, intro to computational geometry.
    => Basic concepts
    => Exercise
  • functions (in maths and programming);
  • polynomials – idea, representation, operations;
  • complex numbers, geometric intuition;
  • euler's formula;
  • fundamental theorem of algebra.
    => Basic concepts
    => Exercise
  • matrices. Operations with matrices;
  • vectors and vector spaces. Basis, change of basis;
  • inverse matrix;
  • determinant, oriented area and volume.
    => Basic concepts
    => Exercise
  • limits;
  • derivatives – intuition, slope of a function at a point;
  • table derivatives;
  • rules for calculating derivatives;
  • higher-order derivatives;
  • riemann sums and integrals. Intuition, oriented area;
  • fundamental theorem of calculus;
  • extension of calculus to many dimensions – intuition.
    => Basic concepts
    => Exercise
  • random variables;
  • probability. Definitions: frequency, chance of happening next time;
  • events and algebra of events;
  • combinatoric rules;
  • probability mass function, probability density function, cumulative distribution function;
  • central limit theorem.
    => Basic concepts
    => Exercise
  • definition. Descriptive and inferential statistics;
  • sample and population. Sampling rules;
  • moments of distributions;
  • covariance and correlation;
  • anscombe's quartet;
  • simpson's paradox.
    => Basic concepts
    => Exercise
  • confidence intervals, confidence level, alpha parameter;
  • null and alternate hypothesis
  • z-test, t-test, chi-squared;
  • ANOVA;
  • p-value;
  • p-value misconceptions.
    => Basic concepts
    => Exercise

online viewer of Jupyter Notebooks: https://gke.mybinder.org

math-concepts's People

Contributors

s-emanuilov avatar

Stargazers

Oleksandr Pronin avatar Hugo B. avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.