krishnakumarsekar / awesome-machine-learning-deep-learning-mathematics

A curated list of mathematics documents ,Concepts, Study Materials , Algorithms and Codes available across the internet for machine learning and deep learning

awesome machine learning and deep learning mathematics

A curated list of awesome machine learning and deep learning mathematics and advanced mathematics descriptions,documents,concepts,study materials,videos,libraries and software (by language).

Table of Contents

• INTRODUCTION
  • Why Maths Important for Machine Learning?
• BASICS
  • What is Machine Learning?
  • What is Deep Learning?
  • Applications of Mathematics in Machine and Deep Learning?
  • Machine and Deep Learning with Mathematics vs without Mathematics
• MATHEMATICAL TOPICS FOR MACHINE AND DEEP LEARNING
  • Linear Algebra
  • Probability and Statistics
  • Linear Calculus
  • Vector Calculus
  • Tensor Calculus
  • Other Calculus Topics
  • Graphs Theory
  • Complexity Theorems
  • Number Theory
  • Optimization Theorems
  • Topology
• ADVANCED MATHEMATICAL TOPICS FOR MACHINE AND DEEP LEARNING
  • Hamiltonian Calculus
  • Halleys Calculus
  • Complex Numbers
  • Quaterinions
  • Sedenions
  • Qudratic Function
  • Advanced Probability and Statistics
  • NP Problem
• LINEAR ALGEBRA
  • Linear Equations
  • Polynomial Equations
  • Vectors
  • Matrices
  • Tensors
  • Vector Space
  • eigenvalues and eigenvectors
  • Cartesian Coordinate System
  • Matrix Decomposition
  • Tensor Decomposition
  • Structural Geometry
  • Factorial
• PROBABILITY AND STATISTICS
  • Probability
  • Rules of probability
  • Mean
  • Median
  • Mode
  • Variance
  • Standard Deviation
  • Random Variables
  • Probability Distribution
  • Conditional Probability
  • Probability Density Function
  • Cumulative Probability Distribution
  • Sample or Sampling
  • Population
  • Statistical Inference
  • Maximum likelihood
  • Binomial Distribution
  • Normal Distribution
  • Gaussian Distribution
  • Statistical Models
  • Expectation Maximization
  • Central Limit Theorem
  • Adequality
  • Local Minima and Maxima
  • Regression
  • Linear Regression
  • Stochastic Process
  • Hypothesis
  • Bayesian Probability
  • Null Hypothesis
  • Confidence Interval
  • Correlation
  • Correlation Coefficient
  • Histogram
  • Z-Score
  • Covariance
  • Least Square Fitting
  • Posterior Probability
  • Bootstrapping
  • Cross Validation
  • Muller Theorem
• ADVANCED PROBABILITY AND STATISTICS
  • Linear Regression
  • Tangent
  • Hyperbolic Tangent
  • Gompertz curve
  • ogee curve
  • Sigmoid function
  • Activation function
  • Generalized logistic curve
  • Gompertz function
  • Heaviside step function
  • Hyperbolic function
  • Logistic distribution
  • Logistic function
  • Logistic regression
  • Logit
  • Modified hyperbolic tangent
  • Softplus function
  • Smoothstep
  • Softmax function
  • Weibull distribution
  • Netoid function
  • Monte Carlo Method
  • Empirical Mean
  • Stationary Probability Distribution
  • Empirical Measures
  • McKean-Vlasov Processes
  • Nonlinear Filtering Equation
  • Hessian Matrix
  • Ising Model
• APPROXIMATION TECHNIQUE or OPTIMIZATION THEOREMS
  • Taylor Series
  • Gradient Descent
  • Newtons Theorem
  • Newtons Law of Approximation
  • Root Finding Algorithms
  • Householder's Method
  • Rational Approximation
  • Halleys Approximation
  • Padé Approximation
  • Diophantine Approximation
  • Transcendental Number Theory
  • Simulated Annealing
  • Steepest Descent
• OTHER CALCULUS TOPICS
  • Differential Calculus
  • Integral Calculus
  • Propositional calculus
  • Ricci Calculus
  • Lambda Calculus
  • Stochastic Calculus
  • Hamiltonian Calculus
  • Taylor's Theorem
  • L'Hôpital's rule
• TOPOLOGY
  • Set Theory
  • Axioms
  • General Topology
  • Topological Space Theory
  • Algebraic Topology
  • Differential Topology
  • Tensor Space Theory
  • Low Dimensional Space Theory
  • Knot Theory
  • Continuous Functions
  • Homeomorphisms
  • Klein Bottle
  • Topological Invariants
  • Topological Data Analysis
  • Proximity Parameters
  • Betti Number
  • Persistent Homology
  • Klein bottle
• TYPES OF MECHANICS FOR MATHEMATICS AND MACHINE LEARNING
  • Analytical mechanics
  • Lagrangian mechanics
  • Hamiltonian mechanics
  • Routhian mechanics
  • Koopman–von Neumann mechanics
• FACTORIAL
  • Gamma Function
• MEETUPS
• GOOGLE GROUPS
• COMPANIES DOING PRODUCTS
• LINKEDLIN GROUPS
• DEGREES
• CONSOLIDATED BOOKS
• CONSOLIDATED VIDEOS
• CONSOLIDATED Reserach Papers
• CONSOLIDATED Reserach Scientist

License

Dedicated Opensources

• Source code of plenty of Algortihms in Image Processing , Data Mining ,etc in Matlab, Python ,Java and VC++ Scripts
• Good Explanations of Plenty of algorithms with flow chart etc
• Comparison Matrix of plenty of algorithms

Contribution

awesome-machine-learning-deep-learning-mathematics's Issues

What's the point of this?

Pardon me for asking, but what is the point of this repository? There appears to be nothing here but a list of topics, albeit relevant to machine learning, but no actual references---the links are merely anchors to things that don't exist! I understand that this is probably a work in progress, but it appears to be little more than a placeholder for something yet to come. If so, it would be courtesey to include a disclaimer stating that there is nothing yet avaiable so that others, similar to me, do not waste their time.

Not able to open the mention topics.

Hi sir,
If these topics are assumed to redirect to other webpages then it's not working. Please check the links again.