In this post, an approach to detecting malware using machine learning is presented. System call activity is processed and analyzed by a classification model to detect the presence of malicious applications.
In this chapter, vital statistics for the United States of America are explored. The Center for Disease Control maintains several datasets containing vital statistics for the nation. These datasets contain records of deaths organized by year. Each record includes age, gender, race, cause of death, and other details. This chapter explores data for the year 2016.
In this chapter, forenames in the USA are considered. The United States Social Security Administration (SSA) makes available a dataset containing information about Social Security records. The dataset contains counts of the number of records that exist for a specific first name and birth year.
An intermediate activation volume produced by a convolutional neural network predicting the attractiveness of a person.
Does beauty truly lie in the eye of its beholder? This chapter explores the complex array of factors that influence facial attractiveness to answer that question or at least to understand it better.
This post explores the distribution of wealth among nonempty addresses on the Bitcoin network.
All addresses on the Bitcoin network are queried. The number of addresses with at least one satoshi is 24,473,765 at the time of the query. The resulting addresses are sorted by the amount of Bitcoin they contain. The list is divided into quantiles and the wealth of each quantile is plotted in a bar plot.
This post is an introduction to using the TFANN module for classification problems. The TFANN module is available here on GitHub. The name TFANN is an abbreviation for TensorFlow Artificial Neural Network. TensorFlow is an open-source library for data flow programming. Due to the nature of computational graphs, using TensorFlow can be challenging at times. The TFANN module provides several classes that allow for interaction with the TensorFlow API using familiar object-oriented programming paradigms.
Is the recent surge in Bitcoin’s price a speculative bubble?
By definition, an economic bubble is a situation in which an asset is traded within a price range that far exceeds its intrinsic value. So, the question is: what is the intrinsic value of Bitcoin? The purpose of this post is to explain some of the technical details of Bitcoin so as to gain a better idea of its value.
In this post, deep learning neural networks are applied to the problem of optical character recognition (OCR) using Python and TensorFlow. This post makes use of TensorFlow and the convolutional neural network class available in the TFANN module. The full source code from this post is available here.
This post is made in introduction of a new YouTube series titled Deep Learning Deathmatch. In this series, a deep learning based AI that relies only on visual input is pitted against video game bosses. The resulting battle is recorded, edited, and compiled into a video. In the first video in the series, the AI fights the Oasis boss in Path of Exile.
More videos are available on my YouTube channel.