cuDF

May 19, 2023

Limit Order Book Dataset Generation for Accelerated Short-Term Price Prediction with RAPIDS

In the high-frequency trading world, thousands of market participants interact daily. In fact, high-frequency trading accounts for more than half of the US...

9 MIN READ

Mar 14, 2023

Accelerated Data Analytics: Speed Up Data Exploration with RAPIDS cuDF

This post is part of a series on accelerated data analytics. Digital advancements in climate modeling, healthcare, finance, and retail are generating...

11 MIN READ

Mar 14, 2023

Accelerated Data Analytics: Faster Time Series Analysis with RAPIDS cuDF

This post is part of a series on accelerated data analytics. Because it is generally constrained to a single core, a standard exploratory data analysis (EDA)...

9 MIN READ

Oct 17, 2022

Mastering String Transformations in RAPIDS libcudf

Efficient processing of string data is vital for many data science applications. To extract valuable information from string data, RAPIDS libcudf provides...

17 MIN READ

May 27, 2022

Boosting Data Ingest Throughput with GPUDirect Storage and RAPIDS cuDF

If you work in data analytics, you know that data ingest is often the bottleneck of data preprocessing workflows. Getting data from storage and decoding it can...

14 MIN READ

May 27, 2022

Prototyping Faster with the Newest UDF Enhancements in the NVIDIA cuDF API

Over the past few releases, the NVIDIA cuDF team has added several new features to user-defined functions (UDFs) that can streamline the development process...

8 MIN READ

May 05, 2022

Optimizing Access to Parquet Data with fsspec

As datasets continue to grow in size, the adoption of cloud-storage platforms like Amazon S3 and Google Cloud Storage (GCS) are becoming more popular. Although...

12 MIN READ

Jan 13, 2022

Accelerating Trustworthy AI for Credit Risk Management

On April 21, 2021, the EU Commission of the European Union issued a proposal for a regulation to harmonize the rules governing the design and marketing of AI...

13 MIN READ

Dec 08, 2021

Deep Learning vs Machine Learning Challenger Models for Default Risk with Explainability

Data Scientists and Machine Learning Engineers often face the dilemma of “machine learning compared to deep learning” classifier usage for their business...

18 MIN READ

Jul 30, 2021

RAPIDS Accelerator for Apache Spark v21.06 Release

Introduction RAPIDS Accelerator for Apache Spark v21.06 is here! You may notice right away that we’ve had a huge leap in version number since we announced our...

4 MIN READ

Mar 19, 2021

10 Minutes to Data Science: Transitioning Between RAPIDS cuDF and CuPy Libraries

RAPIDS is about creating bridges, connections, and clean handoffs between GPU PyData libraries. Interoperability with functionality is our goal. For example, if...

3 MIN READ

Mar 11, 2021

Python Pandas Tutorial: A Beginner's Guide to GPU Accelerated DataFrames for Pandas Users

This series on the RAPIDS ecosystem explores the various aspects that enable you to solve extract, transform, load (ETL) problems, build machine learning (ML)...

8 MIN READ

Mar 03, 2021

Pandas DataFrame Tutorial - Beginner's Guide to GPU Accelerated DataFrames in Python

This post is the first installment of the series of introductions to the RAPIDS ecosystem. The series explores and discusses various aspects of RAPIDS that...

7 MIN READ

Nov 12, 2020

Explaining and Accelerating Machine Learning for Loan Delinquencies

Machine learning (ML) can extract deep, complex insights out of data to help make decisions. In many cases, using more advanced models delivers real...

16 MIN READ

Oct 05, 2020

Making Python Data Science Enterprise-Ready with Dask

At NVIDIA, we are driving change in data science, machine learning, and artificial intelligence. Some of the key trends that drive us are as follows: The rise...

10 MIN READ