Subject archive for "data-science," page 4

Data Science

Polars - A lightning fast DataFrames library

We have previously talked about the challenges that the latest SOTA models present in terms of computational complexity. We've also talked about frameworks like Spark, Dask, and Ray, and how they help address this challenge using parallelization and GPU acceleration.

By Nikolay Manchev7 min read

Data Science

Top High Impact Machine Learning Applications by Industry

In the last decade, machine learning (ML) models have made organizations all over the world and in every industry more productive, more profitable and better able to serve their clients.

By David Weedmark7 min read

Data Science

MATLAB for Data Science and Machine Learning

The opportunities to solve problems with the use of data are greater than ever, and as different industries embrace them, the available data has been steadily increasing and the number of tools expanded. A typical question that new data scientists ask is related to the best programming language to learn, either to get a good understanding of coding or to future-proof their skills. Typically, the question is centered around some usual suspects such as R and Python. I have also been asked about Java and I have provided an answer to that query elsewhere. In reality, there may not be a single best tool to use, and I have long argued for using a toolbox approach to the data science practice. I would like to advocate for one of those tools: MATLAB.

By Dr J Rogel-Salazar9 min read

Data Science

Getting Data with Beautiful Soup

Data is all around us, from the spreadsheets we analyse on a daily basis, to the weather forecast we rely on every morning or the webpages we read. In many cases, the data we consume is simply given to us, and a simple glance is enough to make a decision. For example, knowing that the chance of rain today is 75% all day makes me take my umbrella with me. In many other cases, the data provided is so rich that we need to roll up our sleeves and we may use some exploratory analysis to get our heads around it. We have talked about some useful packages to do this exploration in a previous post.

By Dr J Rogel-Salazar13 min read

Data Science

Data Exploration with Pandas Profiler and D-Tale

We all have heard how data is the new oil. I always say that if that is the case, we need to go through some refinement process before that raw oil is converted into useful products. For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with.

By Dr J Rogel-Salazar15 min read

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