Eventual's data processing engine Daft was inspried by the founders' experience working on Lyft's autonomous vehicle project.

The startup said today it has closed on the $20 million Series A funding round led by Astasia Myers from Felicis, with ...

When I refer to Python, I don’t mean to use a dedicated Python app in favor of Excel. Of course, it comes with several advantages, but nothing beats a direct Python integration ...

However, Python’s methods for parallelizing operations often require data to be serialized and deserialized between threads or nodes, while Julia’s parallelization is more refined.

There are many emotional and powerful stories hidden in gobs of data just waiting to be found. When these stories get told, they have the power to change careers, businesses, and whole groups of ...

Snowflake is also releasing Snowpark-optimized data platforms, initially on the Amazon Web Services Inc. cloud, so Python developers can run large-scale machine learning training models and other ...

The Post Graduate Program in Data Engineering focuses on distributed processing using the Hadoop framework, large-scale data processing using Spark, data pipelines with Kafka, ... It includes a ...

This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in ...

On Friday, Google debuted a new product developed with OpenMined that allows any Python developer to process data with differential privacy.. The two have been working on the project for a year ...

The guide takes a closer look at the open-source library PyTorch which allows a Python developer to quickly get up-to-speed with the features of CUDA that make it so appealing to researchers and ...