Tue.Jun 11, 2024

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Introducing AI/BI: Intelligent Analytics for Real-World Data

databricks

Today, we are excited to announce Databricks AI/BI , a new type of business intelligence product built from the ground up to deeply.

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Building Change Detection in the Region of Cataluña

ArcGIS

Revolutionizing GIS: Streamlining Change Detection for Mapping Agencies.

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Snowflake ML Now Supports Expanded MLOps Capabilities for Streamlined Management of Features and Models 

Snowflake

Bringing machine learning (ML) models into production is often hindered by fragmented MLOps processes that are difficult to scale with the underlying data. Many enterprises stitch together a complex mix of various MLOps tools to build an end-to-end ML pipeline. The friction of having to set up and manage separate environments for features and models creates operational complexity that can be costly to maintain and difficult to use.

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Top 5 Tips for Styling Published Layers and Maps

ArcGIS

The Living Atlas team publishes a lot of web layers. Here's some of our favorite tips and tricks for customizing your layers and maps.

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A Guide to Debugging Apache Airflow® DAGs

In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

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5 Free Competitions for Aspiring Data Scientists

KDnuggets

Improve your skills, creativity, and renown by participating in competitions.

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Building Open-Source Python Packages – SparklePop

Confessions of a Data Guy

One of the things I love about Python is its flexibility and huge community, a community that puts out a never-ending stream of useful packages for the average Software Engineer. In a show of solidarity to the open-source community, I thought I would publish a PYPI package that will probably be used by 5 people […] The post Building Open-Source Python Packages – SparklePop appeared first on Confessions of a Data Guy.

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Fueling Enterprise Generative AI with Data: The Cornerstone of Differentiation

Cloudera

More than two-thirds of companies are currently using Generative AI (GenAI) models, such as large language models (LLMs), which can understand and generate human-like text, images, video, music, and even code. However, the true power of these models lies in their ability to adapt to an enterprise’s unique context. By leveraging an organization’s proprietary data, GenAI models can produce highly relevant and customized outputs that align with the business’s specific needs and ob

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Unlocking the power of mixed reality devices with MobileConfig

Engineering at Meta

MobileConfig enables developers to centrally manage a mobile app’s configuration parameters in our data centers. Once a parameter value is changed on our central server, billions of app devices automatically fetch and apply the new value without app updates. These remotely managed configuration parameters serve various purposes such as A/B testing, feature rollout, and app personalization.

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Next-Gen Customer Loyalty Programs with Data Streaming

Confluent

Use Confluent’s data streaming platform to bring real-time insights to customer loyalty programs, creating personalized offers that drive greater retention and revenue.

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End-to-end spatial data science 5: Machine learning: Cluster analysis in Python and ArcGIS

ArcGIS

This is the fifth in a series of blogs that showcase an end-to-end spatial data science workflow for clustering US precipitation regions.

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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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Introducing Build with Confluent: Enabling Partners to Bring Data Streaming Use Cases to Market Faster

Confluent

Build with Confluent helps system integrators develop joint solutions faster, including specialized software bundles, support from data streaming experts to certify offerings, and access to Confluent’s Go-To-Market teams to amplify audience.

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Tasks Failure Recovery in Snowflake with RETRY LAST

Cloudyard

Read Time: 1 Minute, 48 Second RETRY LAST: In modern data workflows, tasks are often interdependent, forming complex task chains. Ensuring the reliability and resilience of these workflows is critical, especially when dealing with production data pipelines. Imagine you’re tasked with managing a critical data pipeline in Snowflake that processes and transforms large datasets.

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Real-Time AI-Powered Fraud Detection: Safeguarding FinServ Transactions

Striim

In today’s fast-paced financial landscape, robust security measures are not optional — they are essential. Financial services organizations face a constant onslaught of fraud attempts that threaten both their bottom line and the trust of their customers. That’s where real-time AI-powered fraud detection comes into the picture. Think of it as a game-changing solution designed to safeguard transactions and maintain customer confidence.

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PyTorch Introduction — Training a Computer Vision Algorithm

DareData

In this post, we’ll learn how to train a computer vision model using a convolutional Neural Network in PyTorch PyTorch is currently one of the hottest libraries in the Deep Learning field. Used by thousand of developers around the world, the library gained prominence since the release of ChatGPT and the introduction of deep learning into mainstream news headlines.

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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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Chain of Custody: Importance, Steps, Purpose and Examples

Knowledge Hut

In a digital era brimmed with interconnected devices, cybercrimes and security breach incidents have become ever so common, threatening the privacy and security of the users. The recent introduction of amenities such as ubiquitous internet access, the internet of things (IoT), and cloud computing to the general masses has inspired a new cybercrime wave, which has led security experts to make considerable advancements in digital forensics in order to keep up with evolving cyber-crimes.

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Best Platforms to Practice Ethical Hacking

Knowledge Hut

Ethical hacking is a method I've used to test website and application security by simulating attacks, and it serves the crucial purpose of identifying and rectifying vulnerabilities before malicious actors can exploit them. Whether provided as a free service or part of a paid contract, it's indispensable for companies and individuals to safeguard their accounts.

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Java for Data Science – When & How To Use

Knowledge Hut

In recent years, Machine Learning, Artificial Intelligence, and Data Science have become some of the most talked-about technologies. These technological advancements have enabled businesses to automate and operate at a much higher level. Companies of all sizes are investing millions of dollars in data analysis and on professionals who can build these exceptionally powerful data-driven products.

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