Scikit Optimize: Bayesian Hyperparameter Optimization in Python
So you want to optimize hyperparameters of your machine learning model and you are thinking whether Scikit Optimize is the right tool for you? You are in the right place. In this article I will: show you an example of using skopt on a real problem, evaluate this library based on... Read more
Web Scraping News Articles in Python
This article is the second of a series in which I will cover the whole process of developing a machine learning project. If you have not read the first one, I strongly encourage you to do it here. The project involves the creation of a real-time web application that gathers data from several newspapers... Read more
Local Regression in Python
I love data visualization make-overs (like this one I wrote a few months ago), but sometimes the tone can be too negative (like this one I wrote a few months ago). Sarah Leo, a data journalist at The Economist, has found the perfect solution: re-making your own visualizations. Here’s her tweet.... Read more
Timing the Same Algorithm in R, Python, and C++
While developing the RcppDynProg R package I took a little extra time to port the core algorithm from C++ to both R and Python. This means I can time the exact same algorithm implemented nearly identically in each of these three languages. So I can extract some comparative “apples to apples” timings. Please read on for a... Read more
Building a Data Pipeline in Python – Part 2 of N – Data Exploration
Initial data acquisition and data analysis In order to get an idea of what our data looks like, we need to look at it! The Jupyter Notebook, embedded below, will show steps to load your data into Python and find some basic statistics to use them to identify potentially... Read more
Image Augmentation for Convolutional Neural Networks
Limited data is a major obstacle in applying deep learning models like convolutional neural networks. Often, imbalanced classes can be an additional hindrance; while there may be sufficient data for some classes, equally important, but undersampled classes will suffer from poor class-specific accuracy. This phenomenon is intuitive. If the... Read more
Jupyter Notebook: Python or R—Or Both?
I was analytically betwixt and between a few weeks ago. Most of my Jupyter Notebook work is done in either Python or R. Indeed, I like to self-demonstrate the power of each platform by recoding R work in Python and vice-versa. I must have a dozen active notebooks, some... Read more
Logistic Regression with Python
Logistic regression was once the most popular machine learning algorithm, but the advent of more accurate algorithms for classification such as support vector machines, random forest, and neural networks has induced some machine learning engineers to view logistic regression as obsolete. Though it may have been overshadowed by more... Read more
Creating Multiple Visualizations in a Single Python Notebook
For a data scientist without an eye for design, creating visualizations from scratch might be a difficult task. But as is the case with most problems, a solution awaits thanks to Python. Those drawn to using Python for data analysis have been spoiled, as more advanced libraries have made... Read more
From Pandas to Scikit-Learn — A New Exciting Workflow
Ted will present more on this topic at ODSC East 2019 this May in his presentation, “Integrating Pandas with Scikit-Learn, an Exciting New Workflow“ This article is available as a Jupyter Notebook on Google’s Colaboratory (open in playground mode to run and edit) and at the Machine Learning Github repository for the Dunder... Read more