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Are LLMs making StackOverflow irrelevant?

The Pragmatic Engineer

Before the rise of this technology, StackOverflow was the superior option to Googling in the hope of finding a blog post which answered a question. And if you couldn’t find an answer to a problem, you could post a question on StackOverflow and someone would probably answer it.

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An educational side project

The Pragmatic Engineer

for the simulation engine Go on the backend PostgreSQL for the data layer React and TypeScript on the frontend Prometheus and Grafana for monitoring and observability And if you were wondering how all of this was built, Juraj documented his process in an incredible, 34-part blog series. You can read this here. Serving a web page.

Education 364
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Event time skew and global watermark in Apache Spark Structured Streaming

Waitingforcode

A few months ago I wrote a blog post about event skew and how dangerous it is for a stateful streaming job. Since it was a high-level explanation, I didn't cover Apache Spark Structured Streaming deeply at that moment.

IT 130
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Azure Databricks: A Comprehensive Guide

Analytics Vidhya

In this blog post, we will take a closer look at Azure Databricks, its key features, […] The post Azure Databricks: A Comprehensive Guide appeared first on Analytics Vidhya. Introduction Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform that is built on top of the Microsoft Azure cloud.

Big Data 312
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Enhancing Neural Network Training at Yelp: Achieving 1,400x Speedup with WideAndDeep

Yelp Engineering

This blog post delves into our journey of optimizing training time using TensorFlow and Horovod, along with the development of ArrowStreamServer, our in-house library for low-latency data streaming and serving. These models handle large tabular datasets with small parameter spaces, requiring innovative data solutions.

Datasets 104
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Explore the World of Data-Tech with DataHour

Analytics Vidhya

In this blog post, we […] The post Explore the World of Data-Tech with DataHour appeared first on Analytics Vidhya. Current professionals seeking to transition into the data-tech domain or data science professionals seeking to enhance their career growth and development can also benefit from these sessions.

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How Meta discovers data flows via lineage at scale

Engineering at Meta

In this blog, we will delve into an early stage in PAI implementation: data lineage. This took Meta multiple years to complete across our millions of disparate data assets, and well cover each of these more deeply in future blog posts: Inventorying involves collecting various code and data assets (e.g.,