Adnan Masood, a Machine Learning Phd's musings on Life, Technology, Research & Development
"I'm not an outlier; I just haven't found my distribution yet!" -Ronan Conroy Infer.NET is a .NET library for machine learning which provides state-of-the-art algorithms for probabilistic inference from data. Due to its capability of seamlessly integrating with the .NET code, I have used this library frequently and wrote about Infer.Net in the past; however,…
Cloud camp LA happened couple of weeks ago at the coresite campus in downtown LA. The highlights of the evening were Dave Nielsen's intro, Lynn Langit's NOSQL session, Bret Statham's CQRS (Command Query Responsibility Segregation) talk and coresite's datacenter tour. Slides from Bret's lightning talk can be downloaded here. NoSQL for the SQL Server DBA View more…
Even though every machine learning practitioner and researcher would like to modify and tweak both the algorithm and parameters, there are limited options for automated code generation in the machine learning world. SamIam by Automated Reasoning Group, UCLA is the tool designed for “Sensitivity Analysis, Modeling, Inference and more”. Currently the sensitivity, MAP, MPE and EM Learning…
This Wednesday April 25th, I will be part of a panel at the OWASP LA Security Summit where Jerry Hoff VP, Static Code Analysis Division at WhiteHat Security, will be speaking about Webgoat. Shakeel Tufail, Federal Practice Director for HP Enterprise Security Solutions, will be speaking on "Software (In)Security - Challenges to securing software". Noa Bar Yosef, Senior…
Since calling this post just On the history of Bayesian inference will be non sequitur. Judea Pearl won the ACM Turing Award, widely considered the "Nobel Prize in Computing" for his contribution in the areas of developing "Novel Framework for Reasoning under Uncertainty that Changed How Scientists Approach Real World Problems". This framework is the notion of Bayesian Networks aka Bayesian Belief Networks…
Discovering meaningful, explainable and interesting rules from mined data has been a challenging research problem due to its highly subjective nature. It is deemed as the central task in knowledge data and discovery to explore and analyze relationship between features. For most practical applications, it is quite difficult to determine the most relevant rule for…
Bayesian Network without tears by Eugene Charniak of Brown university, is a classical introductory writing by the author of seminal texts like Statistical Language Learning, Introduction to Artificial Intelligence, Artificial Intelligence Programming and Computational Semantics. It has repeatedly been (officially or unofficially) made part of PhD comprehensive exam reading lists. This short and well-written 14 page paper published…
CloudCamp is an unconference where early adopters of Cloud Computing technologies exchange ideas. With the rapid change occurring in the industry, we need a place we can meet to share our experiences, challenges and solutions. At CloudCamp, you are encouraged you to share your thoughts in several open discussions, as we strive for the advancement…
Subjectivity of an interestingness measure has been a subject of discussion for a while in the data mining and machine learning communities. In their SIGKDD paper titled “A framework for mining interesting pattern sets”, authors Bie, Kontonasios and Spyropoulou have suggested a framework, which approaches the problem in a dual-attack manner. Assuming that the prior…
Time and again as you work through a technology, delta books become increasingly important i.e. the technological texts which are concrete, concise, and build upon earlier foundations of your learning without starting all-over again from the square one. Professional ASP.NET qualify as one of those books, which not only fit the above definition, but…