Andres Mendez-Vazquez

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Andres Mendez-Vazquez has participated in several projects for the USA Army, Mexican Air Force, Oracle MDC, IBM Mexico, and several startups. As a professional of Machine Learning and Artificial Intelligence, his main task is to propose, design, develop and program algorithms for specific solutions on those areas. Additionally, he is an associate research professor at Cinvestav Guadalajara where he leads a Machine Learning Research Group. He got his PhD in Computer Engineering doing Machine Learning at the University of Florida, USA . His research and interests are in applying, designing and developing Machine Learning, Deep Learning and Computational Mathematics algorithms.

machine learning analysis of algorithms data structures artificial intelligence linear algebra algorithms neural networks complexity deep learning bayesian networks probability map bayesian estimation automatic differentiation backpropagation company profiles reinforcement learning deep heuristic search tensors data sciences unsupervised learning clustering k-means learning boosting statistical learning risk functional loss functions function approximation feature selection convex optimization data analytics semi-supervised unsupurvised supervised data mining logistic regression markov chains monte carlo math for intelligent systems b-trees divide and conquer skip list genetic algorithms schema theorem amortized analysis binary trees hash tables search median statistics linear sorting sorting dual problem lagrangian's

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Andres Mendez-Vazquez

24 Multithreaded Algorithms

03 Analysis of Algorithms: Probabilistic Analysis

03 Machine Learning Linear Algebra

07.2 Holland's Genetic Algorithms Schema Theorem

14 Skip Lists

07 Analysis of Algorithms: Order Statistics

18 Basic Graph Algorithms

21 All Pairs Shortest Path

14 Machine Learning Single Layer Perceptron

26 Machine Learning Unsupervised Fuzzy C-Means

17 Machine Learning Radial Basis Functions

07 Machine Learning - Expectation Maximization

08 Hash Tables

13 Amortized Analysis

01 Analysis of Algorithms: Introduction

23 Machine Learning Feature Generation

26 Computational Geometry

15 Machine Learning Multilayer Perceptron

02 Analysis of Algorithms: Divide and Conquer

06 Analysis of Algorithms: Sorting in Linear Time