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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 a continuous process,... 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 March’s national championship... 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 robust multiple imputation... 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 perform that well.... Read more

The Beginner’s Guide to Scikit-Learn

Python Tools & Languages Scikit-Learnposted by Spencer Norris, ODSC October 24, 2018

Scikit-Learn is one of the premier tools in the machine learning community, used by academics and industry professionals alike. At ODSC East 2019, Scikit-Learn author Andreas Mueller will host a training session to give beginners a crash course. As one of the primary contributors to Scikit-Learn, Mueller is one... 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 wide range... Read more

TensorLayer for Developing Complex Deep Learning Systems

Pythonposted by Daniel Gutierrez, ODSC October 4, 2018

This article describes TensorLayer, a modular Python wrapper library for TensorFlow allowing data scientists to streamline the development of complex deep learning systems. TensorLayer was released in September 2016 with a GitHub repo. A descriptive research paper followed in August 2017: TensorLayer: A Versatile Library for Efficient Deep Learning... 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, I started to... Read more

Machine Learning with H2O

Python Tools & Languagesposted by Shivayogi Biradar September 13, 2018

Big datasets pose computation problems for software such as R and python in addition to implementing basic machine learning algorithms that can seem like it would run forever. Most of the time it is difficult to even determine how much time it would take to run these algorithms. Enter H20,... Read more

Building SAGA optimization for Dask Arrays

Python Tools & Languagesposted by Matthew Rocklin August 20, 2018

This work is supported by ETH Zurich, Anaconda Inc, and the Berkeley Institute for Data Science At a recent Scikit-learn/Scikit-image/Dask sprint at BIDS, Fabian Pedregosa (a machine learning researcher and Scikit-learn developer) and Matthew Rocklin (Dask core developer) sat down together to develop an implementation of the incremental optimization algorithm SAGA on parallel Dask datasets. The... Read more