Dropout with Theano
Almost everyone working with Deep Learning would have heard a smattering about Dropout. Albiet a simple concept (introduced a couple of years ago), which sounds like a pretty obvious way for model averaging, further resulting into a more generalized and regularized Neural Net; still when you... Read more
How the Logistic Regression Model Works in Machine Learning
In this article, we are going to learn how the logistic regression model works in machine learning. The logistic regression model is one member of the supervised classification algorithm family. The building block concepts of logistic regression can be helpful in deep learning while building the... Read more
Maps and sets can have quadratic-time performance
Swift is a new programming language launched by Apple slightly over two years ago. Like C and C++, it offers ahead-of-time compilation to native code but with many new modern features. It is available on Linux and macOS. Like C++, Swift comes complete with its own... Read more
An Introduction to Object Oriented Data Science in Python
A lot of focus in the data science community is on reducing the complexity and time involved in data gathering, cleaning, and organization. This article discusses how object oriented design techniques from software engineering can be used to reduce coding overhead and create robust, reusable data... Read more
Social media has fundamentally changed the way in which we interact with each other, and with the World Wide Web. Our web activities are now inherently social. We can keep in touch with close friends on facebook without ever needing to pick up a phone or... Read more
Over time, Python and R have established themselves as the leading languages for Data Science. The rise of both has not been frictionless, though, as the two communities have ‘clashed’ over philosophical differences as each side recruits Data Science newcomers. R users will recommend that R... Read more
Data science is an interdisciplinary endeavor, and it serves the purpose of extracting insight from varying sources of information. Various communities come together at Data Science Conferences to share their knowledge and promote innovation. It is not surprising, then, that the tools showcased by data scientists... Read more
Standard software development practices for web, Saas, and industrial environments tend to focus on maintainability, code quality, robustness, and performance. Scientific programing in data science is more concerned with exploration, experimentation, making demos, collaborating, and sharing results. It is this very need for experiments, explorations, and... Read more
Riding on Large Data with Scikit-learn
What’s a Large Data Set? A data set is said to be large when it exceeds 20% of the available RAM for a single machine. Which for your standard MacBook Pro with 8Gb of RAM, corresponds to a meager 2Gb dataset — size that is becoming... Read more
Saul Diez-Guerra at ODSC Boston 2015
What We Learned While Teaching Python and Data Science Pedagogy and lessons learned from teaching an online introductory Python and Data Science courses. This is how we approached the matter, what we learned and where we want to go next. Presenter Bio: Saul Diez-Guerra works as... Read more