Andres Mendez-Vazquez

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104 SlideShares 77 Followers 10 Folgens

104 SlideShares 77 Followers 10 Folgens

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

Aktivität
Info

01 Analysis of Algorithms: Introduction

Vor 9 Jahren • 1667 Aufrufe

02 Analysis of Algorithms: Divide and Conquer

Vor 9 Jahren • 1314 Aufrufe

03 Analysis of Algorithms: Probabilistic Analysis

Vor 9 Jahren • 6324 Aufrufe

An introduction to support vector machines

Vor 9 Jahren • 1010 Aufrufe

05 Analysis of Algorithms: Heap and Quick Sort - Corrected

Vor 9 Jahren • 1081 Aufrufe

06 Analysis of Algorithms: Sorting in Linear Time

Vor 9 Jahren • 1309 Aufrufe

07 Analysis of Algorithms: Order Statistics

Vor 9 Jahren • 3130 Aufrufe

02.03 Artificial Intelligence: Search by Optimization

Vor 9 Jahren • 1254 Aufrufe

08 Hash Tables

Vor 9 Jahren • 1712 Aufrufe

09 binary trees

Vor 9 Jahren • 405 Aufrufe

10 Red-Black Trees

Vor 9 Jahren • 1295 Aufrufe

12 Greeddy Method

Vor 9 Jahren • 638 Aufrufe

13 Amortized Analysis

Vor 9 Jahren • 2022 Aufrufe

07.2 Holland's Genetic Algorithms Schema Theorem

Vor 9 Jahren • 5722 Aufrufe

14 Skip Lists

Vor 9 Jahren • 3721 Aufrufe

Preparation Data Structures 01 introduction

Vor 8 Jahren • 274 Aufrufe

Preparation Data Structures 02 recursion

Vor 8 Jahren • 362 Aufrufe

Preparation Data Structures 03 abstract data_types

Vor 8 Jahren • 544 Aufrufe

Preparation Data Structures 04 array linear_list

Vor 8 Jahren • 441 Aufrufe

Preparation Data Structures 05 chain linear_list

Vor 8 Jahren • 391 Aufrufe

Preparation Data Structures 06 arrays representation

Vor 8 Jahren • 1212 Aufrufe

Preparation Data Structures 07 stacks

Vor 8 Jahren • 469 Aufrufe

Preparation Data Structures 08 queues

Vor 8 Jahren • 255 Aufrufe

Preparation Data Structures 09 hash tables

Vor 8 Jahren • 502 Aufrufe

Preparation Data Structures 10 trees

Vor 8 Jahren • 363 Aufrufe

Preparation Data Structures 11 graphs

Vor 8 Jahren • 456 Aufrufe

03 Probability Review for Analysis of Algorithms

Vor 8 Jahren • 436 Aufrufe

02 The Math for Analysis of Algorithms

Vor 8 Jahren • 399 Aufrufe

16 Fibonacci Heaps

Vor 8 Jahren • 1142 Aufrufe

15 B-Trees

Vor 8 Jahren • 1034 Aufrufe

01 Notes Introduction Analysis of Algorithms Notes

Vor 8 Jahren • 566 Aufrufe

02 Notes Divide and Conquer

Vor 8 Jahren • 510 Aufrufe

Simple Neural Network Python Code

Vor 8 Jahren • 1321 Aufrufe

03 notes

Vor 8 Jahren • 313 Aufrufe

Math for Intelligent Systems - 01 Linear Algebra 01 Vector Spaces

Vor 8 Jahren • 692 Aufrufe

Schedule Classes DataLab Community

Vor 6 Jahren • 367 Aufrufe

Introduction Machine Learning Syllabus

Vor 5 Jahren • 323 Aufrufe

Introduction Mathematics Intelligent Systems Syllabus

Vor 5 Jahren • 413 Aufrufe

A basic introduction to learning

Vor 5 Jahren • 260 Aufrufe

Analysis of Algorithms Syllabus

Vor 5 Jahren • 116 Aufrufe

Ideas about a Bachelor in Machine Learning/Data Sciences

Vor 5 Jahren • 97 Aufrufe

Ideas 09 22_2018

Vor 5 Jahren • 135 Aufrufe

Introduction to artificial_intelligence_syllabus

Vor 5 Jahren • 296 Aufrufe

Neural Networks and Deep Learning Syllabus

Vor 5 Jahren • 357 Aufrufe

Zetta global

Vor 4 Jahren • 162 Aufrufe

Cache aware hybrid sorter

Manchor Ko • Vor 11 Jahren

omp-and-k-svd - Gdc2013

Manchor Ko • Vor 11 Jahren

Mevia Introduction in Tegucigalpa, Honduras - Honduras Global

Dr. Edwin Hernandez • Vor 8 Jahren

Non-exhaustive, Overlapping K-means

David Gleich • Vor 8 Jahren

EGLA Licensing and Stadson Technologies

Dr. Edwin Hernandez • Vor 8 Jahren

Matrix methods for Hadoop

David Gleich • Vor 11 Jahren

Edwin Hernandez Presentation for Local Computer Networks n 2004

Dr. Edwin Hernandez • Vor 13 Jahren

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