Mike Bowles

About Mike Bowles

Broad experience in businesses where machine learning is key to success. Provide consulting services and training on technical or general management problems and serve on BoD and advisory boards. Have founded several startups, initiated new businesses for large companies, done business evaluation, management consulting and corporate training. Technical expertise in machine learning and data science. Formal education in signal processing, finance and business. Excellent communications skills.Have designed machine learning systems for a number of applications including: algorithmic trading systems, content optimization for web site performance, bioinformatics applications. Deep understanding of modern machine learning algorithms including: regularized regression, boosted trees, support vector machines (SVM), neural nets, auto-encoders, deep belief networks (DBN), restricted Boltzmann machines (RBM), time series methods Kalman filtering, natural language processing, latent semantic analysis, topic modeling, big data techniques for machine learning on map reduce, recommender systems. Programming languages – Python, R, Tensor Flow, Theano, C++, Java, C, Unix, Fortran. Published work: Michael Bowles,\"Machine Learning with Spark and Python: Essential Techniques for Predictive Analysis with Spark\", 2nd Edition Wiley, Sept 2019Mike Bowles and Ron Shigeta,\"Statistical models for predicting liver toxicity from genomic data\" to appear in Systems Biomedicine 1:3, 1-6 July/August/Sept 2013, Landes Bioscience. Jeremy Howard and Mike Bowles \"The Two Most Important Algorithms in Predictive Modeling Today\" O\'Reilly Stata Conference 2012. ACM presentation using data mining to improve performance of a traditional trading system. The video and audio are on fora.tv: http://fora.tv/2009/05/13/Michael_Bowles_Neural_Nets_and_Rule-Based_Trading_Systems#post36919The slides for that talk are on slideshare the link is further down my profile.

Experience

1. Machine Learning Consultant

   Collaborative Drug Discovery - CDD Vault

   Aug 2018 — Present

   AI for computational drug discovery

Education

• Oklahoma State University

  BSME, Mechanical Engineering

  1967 — 1972

• Massachusetts Institute of Technology

  ScD, Instrumentation

  1975 — 1980

• Oklahoma State University

  MSME, Estimation and Control

  1973 — 1975

• UCLA Anderson School of Management

  MBA, Finance and New Ventures

  1989 — 1991

Skills

• Neural Networks
• Start-Ups
• Statistical Modeling
• Time Series Analysis
• Unix
• Artificial Intelligence
• Statistics
• Svm
• Distributed Systems
• C++
• Mapreduce
• Predictive Modeling
• R
• Java
• Ruby
• Sql
• Consulting
• Algorithms
• Business Development
• Software Development
• Python
• Latex
• Signal Processing
• Management
• Pattern Recognition
• Hadoop
• Regression
• Analysis
• Predictive Analytics
• Perl
• Data Science
• Amazon Web Services (Aws)
• Data Analysis
• Natural Language Processing
• Machine Learning
• Big Data
• Text Mining
• Fortran
• Data Mining
• Kalman Filtering