Mon.Jul 22, 2024

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Enhancing LLM-as-a-Judge with Grading Notes

databricks

Evaluating long-form LLM outputs quickly and accurately is critical for rapid AI development. As a result, many developers wish to deploy LLM-as-judge methods.

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How to Use the pivot_table Function for Advanced Data Summarization in Pandas

KDnuggets

Let's learn to use Pandas pivot_table in Python to perform advance data summarization

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Introducing Mosaic AI Model Training for Fine-Tuning GenAI Models

databricks

Today, we're thrilled to announce that Mosaic AI Model Training's support for fine-tuning GenAI models is now available in Public Preview. At Databricks.

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Using Transfer Learning to Boost Model Performance

KDnuggets

Transfer learning can improve model performance by leveraging pre-trained models and adapting them to new, related tasks.

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Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

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Getting the Most From Your Modern Data Platform: A Three-Phase Approach

Snowflake

A robust, modern data platform is the starting point for your organization’s data and analytics vision. At first, you may use your modern data platform as a single source of truth to realize operational gains — but you can realize far greater benefits by adding additional use cases. In this blog, we offer guidance for leveraging Snowflake’s capabilities around data and AI to build apps and unlock innovation.

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5 Free Courses to Master Natural Language Processing

KDnuggets

Go from zero to 100 with these free NLP courses!

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Building App Excellence with Location and Data APIs

Precisely

Key Takeaways: Use location and data APIs to boost app reliability and user satisfaction with accurate, up-to-date geographic information Overcome common issues like failed deliveries and customer frustrations through advanced geo addressing solutions that enhance efficiency and data accuracy Leverage Precisely APIs to not only correct data but also enrich applications with essential functions including identity verification and points of interest location The demand for accurate and efficient l

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Data Versioning: A Comprehensive Guide for Modern Data Teams

Monte Carlo

Data doesn’t just flow – it floods in at breakneck speed. How do we track this tsunami of changes, ensure data integrity, and extract meaningful insights? Data versioning is the answer. It provides us with a systematic approach to tracking changes, ensuring data integrity, and enabling meaningful insights within today’s fluid and complex data environment.

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Direct Integration: Kinesis Firehose with Snowpipe Streaming

Cloudyard

Read Time: 2 Minute, 57 Second Previously, data engineers used Kinesis Firehose to transfer data into blob storage (S3) and then load it into Snowflake using either Snowpipe or batch processing. This introduced latency in the data pipeline for near real-time data processing. Now, Amazon Kinesis Data Firehose (Firehose) offers direct integration with Snowflake Snowpipe Streaming, eliminating the need to store data in an S3 bucket.

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Best DevOps Engineer Resume Example: Building an Impressive DevOps Resume

Knowledge Hut

As DevOps engineer, your responsibility is to bridge the gaps between software developments, testing, and support. As a DevOps engineer, you will regularly manage, monitor, and optimize an IT projects’ who, what, where, and how. DevOps engineering is not an easy field to work in, but it is a well-paying position with a promising future. To get ready for its interview, you will need expertise with various software applications and experience collaborating with other software engineering dep

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

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What are DevOps Artifacts and Its Best Practices in 2024?

Edureka

Artifacts in DevOps not only help produce the final software but also help the team of developers by storing all the necessary elements in the artifacts repository, where the developers can easily find them and perform necessary operations (add, move, edit, or delete) with them. Thus, the artifacts save the developers valuable time from finding and gathering resources from different places, improving their productivity.

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Maestro: Netflix’s Workflow Orchestrator

Netflix Tech

By Jun He , Natallia Dzenisenka , Praneeth Yenugutala , Yingyi Zhang , and Anjali Norwood TL;DR We are thrilled to announce that the Maestro source code is now open to the public! Please visit the Maestro GitHub repository to get started. If you find it useful, please give us a star. What is Maestro Maestro is a general-purpose, horizontally scalable workflow orchestrator designed to manage large-scale workflows such as data pipelines and machine learning model training pipelines.

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Resilience in Action: How Cloudera’s Platform, and Data in Motion Solutions, Stayed Strong Amid the CrowdStrike Outage

Cloudera

Late last week, the tech world witnessed a significant disruption caused by a faulty update from CrowdStrike, a cybersecurity software company that focuses on protecting endpoints, cloud workloads, identity, and data. This update led to global IT outages, severely affecting various sectors such as banking, airlines, and healthcare. Many organizations found their systems rendered inoperative, highlighting the critical importance of system resilience and reliability.