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Logistic Regression with Python

Modeling Python Logistic Regression Pythonposted by Ralabs April 11, 2019

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... Read more

Creating Multiple Visualizations in a Single Python Notebook

Data Visualization Modeling Python Tools & Languages Data Visualization Pythonposted by Kailen Santos April 10, 2019

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... Read more

From Pandas to Scikit-Learn — A New Exciting Workflow

Featured Post Modeling Pandas Pythonposted by Ted Petrou February 28, 2019

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... Read more

The Anatomy of K-Means Clustering

Modeling Python Tools & Languages Machine Learning Pythonposted by Diego Lopez Yse February 22, 2019

Let’s say you want to classify hundreds (or thousands) of documents based on their content and topics, or you wish to group together different images for some reason. Or what’s even more, let’s think you have that same data already classified but you want to challenge... Read more

The Beginners Guide for Video Processing with OpenCV

Modeling Python Computer Vision Deep Learning Machine Learning Pythonposted by Ralabs January 23, 2019

Computer vision is a huge part of the data science/AI domain. Sometimes, computer vision engineers have to deal with videos. Here, we aim to shed light on video processing – using Python, of course. This might be obvious for some, but nevertheless, video streaming is not... Read more

Which Conference is Best? — College Hoops, Net Rankings and Python

Python Tools & Languages Python Sportsposted by Steve Miller January 18, 2019

For college basketball junkies like me, the season is now shifting into high gear as teams begin serious conference play. At the end of the regular season and conference tournaments, 66 D1 teams — 32 league champions and 34 at large — will receive invitations to... Read more

Handling Missing Data in Python/Pandas

Conferences Modeling Python Tools & Languages Conferences ODSC West Pandas Pythonposted by Daniel Gutierrez, ODSC November 21, 2018

Key Takeaways: It’s important to describe missing data and the challenges it poses. You need to clarify a confusing terminology that further adds to the field’s complexity. You should take the time to review methods for handling missing data. You need to learn how to apply... Read more

Exploring Scikit-Learn Further: The Bells and Whistles of Preprocessing

Python Tools & Languages Machine Learning model preprocessing Python Scikit-Learnposted by Spencer Norris, ODSC October 25, 2018

In my previous post, we constructed a simple cross-validated regression model using Scikit-Learn in 35 lines. It’s pretty amazing that we can perform machine learning with so little effort, but we just did the bare minimum in order to get a working model. Frankly, it didn’t even... Read more

All the Best Parts of Pandas for Data Science

Python Pandas Pythonposted by Spencer Norris, ODSC October 15, 2018

Pandas has been hailed by many in the data science community as the missing link between Python and analysis, a tool that can be leveraged in order to dramatically reduce overhead in data science projects, increase understandability and speed up workflows. Pandas comes loaded with a... Read more

Snakes in a Package: Combining Python and R with Reticulate

Python R Tools & Languages Python Rposted by Adnan Fiaz September 18, 2018

When I first started working as a data scientist (or something like it) I was told to program in C++ and Java. Then R came along and it was liberating; my ability to do data analysis increased substantially. As my applications grew in size and complexity,... Read more