Introduction to Scala for Java Developers

Jan 20, 200931 likes5,837 views

This is brief presentation on the Scala programming language. It is aimed at Java developers who are curious about Scala. It was given at a San Francisco Java User Group in January 2009.

Introduction to Scala for Java Developers

Scala is a functional and object-oriented programming language that runs on the Java Virtual Machine. It features type inference, immutable collections, pattern matching, and functions as first-class values. The document provides an overview of Scala's features such as its static typing, traits for multiple inheritance, and case classes for value objects. It also demonstrates Scala's collections API and use of functions and pattern matching.

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National Fuels Treatments Initiative: Building a Seamless Map of Hazardous Fu...Safe Software

The National Fuels Treatments Initiative (NFT) is transforming wildfire mitigation by creating a standardized map of nationwide fuels treatment locations across all land ownerships in the United States. While existing state and federal systems capture this data in diverse formats, NFT bridges these gaps, delivering the first truly integrated national view. This dataset will be used to measure the implementation of the National Cohesive Wildland Strategy and demonstrate the positive impact of collective investments in hazardous fuels reduction nationwide. In Phase 1, we developed an ETL pipeline template in FME Form, leveraging a schema-agnostic workflow with dynamic feature handling intended for fast roll-out and light maintenance. This was key as the initiative scaled from a few to over fifty contributors nationwide. By directly pulling from agency data stores, oftentimes ArcGIS Feature Services, NFT preserves existing structures, minimizing preparation needs. External mapping tables ensure consistent attribute and domain alignment, while robust change detection processes keep data current and actionable. Now in Phase 2, we’re migrating pipelines to FME Flow to take advantage of advanced scheduling, monitoring dashboards, and automated notifications to streamline operations. Join us to explore how this initiative exemplifies the power of technology, blending FME, ArcGIS Online, and AWS to solve a national business problem with a scalable, automated solution.

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Mastering AI Workflows with FME - Peak of Data & AI 2025Safe Software

Harness the full potential of AI with FME: From creating high-quality training data to optimizing models and utilizing results, FME supports every step of your AI workflow. Seamlessly integrate a wide range of models, including those for data enhancement, forecasting, image and object recognition, and large language models. Customize AI models to meet your exact needs with FME’s powerful tools for training, optimization, and seamless integration

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GIS and FME: The Foundation to Improve the Locate Process of UtilitiesSafe Software

Locate requests is an important activity for utility companies to prevent people who are digging from damaging underground assets. At Energir, locates were historically treated by our internal field technicians. It’s a very intensive and time-sensitive task during the summer season and it has a significant financial and environmental cost. Since locate requests tend to increase from year to year, it became clear that improvements were needed to keep delivering a quality service to requestors and keeping Energir’s assets safe. This presentation will explain how transformative projects done in the past years allowed to start sending locate plans to requestors without the intervention of field technicians. The analysis of the GIS data through FME workbenchs allows to filter some locate request types and process them semi-automatically. However, the experience gained so far shows that this process is limited by the fact that Energir’s is missing precise information about the spatial accuracy. Future plans are to precisely locate most of Energir’s gas network and FME will again be a huge help to integrate all the data that will be produced.

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Oracle Cloud Infrastructure AI FoundationsVICTOR MAESTRE RAMIREZ

Your startup on AWS - How to architect and maintain a Lean and Mean account J...angelo60207

Prevent infrastructure costs from becoming a significant line item on your startup’s budget! Serial entrepreneur and software architect Angelo Mandato will share his experience with AWS Activate (startup credits from AWS) and knowledge on how to architect a lean and mean AWS account ideal for budget minded and bootstrapped startups. In this session you will learn how to manage a production ready AWS account capable of scaling as your startup grows for less than $100/month before credits. We will discuss AWS Budgets, Cost Explorer, architect priorities, and the importance of having flexible, optimized Infrastructure as Code. We will wrap everything up discussing opportunities where to save with AWS services such as S3, EC2, Load Balancers, Lambda Functions, RDS, and many others.

Oracle Cloud Infrastructure Generative AI ProfessionalVICTOR MAESTRE RAMIREZ

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Domino IQ – Was Sie erwartet, erste Schritte und Anwendungsfällepanagenda

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Scaling GenAI Inference From Prototype to Production: Real-World Lessons in S...Anish Kumar

Presented by: Anish Kumar LinkedIn: https://www.linkedin.com/in/anishkumar/ This lightning talk dives into real-world GenAI projects that scaled from prototype to production using Databricks’ fully managed tools. Facing cost and time constraints, we leveraged four key Databricks features—Workflows, Model Serving, Serverless Compute, and Notebooks—to build an AI inference pipeline processing millions of documents (text and audiobooks). This approach enables rapid experimentation, easy tuning of GenAI prompts and compute settings, seamless data iteration and efficient quality testing—allowing Data Scientists and Engineers to collaborate effectively. Learn how to design modular, parameterized notebooks that run concurrently, manage dependencies and accelerate AI-driven insights. Whether you're optimizing AI inference, automating complex data workflows or architecting next-gen serverless AI systems, this session delivers actionable strategies to maximize performance while keeping costs low.

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