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Build Better Data Pipelines with SQL and Python in Snowflake

Snowflake

As the core building blocks of any effective data strategy, these transformations are crucial for constructing robust and scalable data pipelines. Today, we're excited to announce the latest product advancements in Snowflake to build and orchestrate data pipelines. The resulting data can be queried by any Iceberg engine.

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10 Best CrewAI Projects You Must Build in 2025

ProjectPro

One of the primary motivations for individuals searching for "crew ai projects" is to find practical examples and templates that can serve as starting points for building their own AI applications. These components form the foundation for building robust and powerful AI agents.

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Behind the Scenes: Building a Robust Ads Event Processing Pipeline

Netflix Tech

At Netflix, we embarked on a journey to build a robust event processing platform that not only meets the current demands but also scales for future needs. This blog post delves into the architectural evolution and technical decisions that underpin our Ads event processing pipeline.

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Building Holiday Finds: How Pinterest Engineers Reimagined Gift Discovery

Pinterest Engineering

Personalization Stack Building a Gift-Optimized Recommendation System The success of Holiday Finds hinges on our ability to surface the right gift ideas at the right time. Unified Logging System: We implemented comprehensive engagement tracking that helps us understand how users interact with gift content differently from standardPins.

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Guide to OpenCV and Python-Dynamic Duo of Image Processing

ProjectPro

Whether you’re looking to track objects in a video stream, build a face recognition system, or edit images creatively, OpenCV Python implementation is the go-to choice for the job. At the core of such applications lies the science of machine learning, image processing, computer vision , and deep learning.

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Part 1: A Survey of Analytics Engineering Work at Netflix

Netflix Tech

Analytics Engineers deliver these insights by establishing deep business and product partnerships; translating business challenges into solutions that unblock critical decisions; and designing, building, and maintaining end-to-end analytical systems. DJ acts as a central store where metric definitions can live and evolve.

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PyTorch vs TensorFlow 2025-A Head-to-Head Comparison

ProjectPro

These frameworks simplify the process of humanizing machines with supremacy through accurate large-scale complex deep learning models. The reason for having computational graphs is to achieve parallelism and speed up the training process. There are usually two types of graphs – Static and Dynamic.