An Introduction to Software Testing

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Reports and data visualizations put critical information into the hands of the business. But while the experience of designing reports and visualizations has improved, the method of providing them to users has not. Until now. Microservices and container technologies managed by DevOps processes is the new norm for many of today’s software builders. So how does reporting and data visualization fit into this new world? Join our three-part interactive workshop to learn the ins and outs of TIBCO JasperReportsⓇ IO, an engine designed to churn out reports and visualizations with the efficiency and flexibility of today’s latest cloud technologies. Workshop 1: Intro to JasperReportsⓇ IO and how to build your first report In this workshop we’ll walk you through: -Intro into JasperReports IO features & how to use them -The basics of how JasperReports IO and Jaspersoft Studio (report & visualization design tool) work together -How to design report or data visualizations in Jaspersoft Studio Watch The Webinar Here: https://www.jaspersoft.com/event/part-1-intro-jasperreports-io-and-how-build-your-first-report

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Learn how Deloitte is integrating machine learning with native Elasticsearch functionality to help a large federal agency expedite document review for a variety of eDiscovery use cases. This talk will focus on integrating machine learning (ML)/natural language processing (NLP) into ingest pipelines to add metadata to an index and how Deloitte uses Elasticsearch queries to dynamically sort documents based on an iterative user feedback loop.

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When working with big data or complex algorithms, we often look to parallelize our code to optimize runtime. By taking advantage of a GPUs 1000+ cores, a data scientist can quickly scale out solutions inexpensively and sometime more quickly than using traditional CPU cluster computing. In this webinar, we will present ways to incorporate GPU computing to complete computationally intensive tasks in both Python and R. See the full presentation here: 👉 https://vimeo.com/153290051 Learn more about the Domino data science platform: https://www.dominodatalab.com

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RSVP Webinar: https://www.eventbrite.com/e/webinarkubeflow-tensorflow-tfx-pytorch-gpu-spark-ml-amazonsagemaker-tickets-45852865154 Talk #0: Introductions and Meetup Announcements By Chris Fregly and Antje Barth Talk #1: Ray Overview, Ray AI Runtime on AWS using Amazon SageMaker, EC2, EMR, EKS by Chris Fregly, Principal Specialist Solution Architect, AI and Machine Learning @ AWS Talk #2: Deep-dive Blueprints for Amazon Elastic Kubernetes Service (EKS) including Ray and Spark by Apoorva Kulkarni, Sr. Specialist Solution Architect, Containers and Kubernetes @ AWS RSVP Webinar: https://www.eventbrite.com/e/webinarkubeflow-tensorflow-tfx-pytorch-gpu-spark-ml-amazonsagemaker-tickets-45852865154 Zoom link: https://us02web.zoom.us/j/82308186562 Related Links O'Reilly Book: https://www.amazon.com/dp/1492079391/ Website: https://datascienceonaws.com Meetup: https://meetup.datascienceonaws.com GitHub Repo: https://github.com/data-science-on-aws/ YouTube: https://youtube.datascienceonaws.com Slideshare: https://slideshare.datascienceonaws.com

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Episode 3: The LLM / GPT / AI Prompt / Data Engineer Roadmap In this episode, we'll discuss the history, fundamentals, and the different flavors of LLMs available, beyond GPT/ChatGPT. This is a dry run of a session that will be on a LLM Bootcamp ( Fill out the survey on the link if you are interested in an in-person vs. virtual session) Intro / Fundamentals of LLM LLM Foundations History of LLMs Tuning, Training, or "In Context Learning" with LLMs What is "Prompt Engineering" Case for Augmenting LLMs Series: Using AI / ChatGPT at Work - GPT Automation Are you a small business owner or web developer interested in leveraging the power of GPT (Generative Pretrained Transformer) technology to enhance your business processes? If so, Join us for a series of events focused on using GPT in business. Whether you're a small business owner or a web developer, you'll learn how to leverage GPT to improve your workflow and provide better services to your customers. GPT Automation: What it is and How it Works How Time-Saving GPT Automation Can Improve Your Business Cost-Effective GPT Automation: How it Can Save Your Business Money Using GPT Automation for Customer Service: Benefits and Best Practices The Power of GPT Automation for Content Creation Data Analysis Made Easy with GPT Automation Top GPT-3 Automation Tools for Businesses The Ethical Considerations of GPT Automation Overcoming Bias in GPT Automation: Best Practices The Future of GPT Automation: Trends and Predictions Since we focus on "no code" here, we'll explore the tools that are already out there such as ChatGPT plugins for Chrome, OpenAI GPT API, low-code/no-code platforms like Make/Integromat and Zapier, existing apps like Jasper/Rytr, and ecosystem tools like Everyprompt. We'll also discuss the resources available for those interested in learning more about GPT, including other people’s prompts.

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One of the biggest challenges for software developers is the need to make informed choices about the external software and products they use in their own software systems. Evaluating whether a given system is appropriately secured can be challenging, especially if it’s external or owned by a third party. This so-called software supply chain has been under increasing scrutiny in recent years, with attacks on software systems being responsible for damages to both public and private interests. In collaboration with the Open Source Security Foundation (OpenSSF), Google has proposed Supply-chain Levels for Software Artifacts (SLSA). The new SLSA framework formalizes criteria around software supply chain integrity, to help the industry and open-source ecosystem secure the software development lifecycle. SLSA (pronounced "salsa") is a security framework from source to service, giving anyone working with software a common language for increasing levels of software security and supply chain integrity. It’s how you get from safe enough to being as resilient as possible, at any link in the chain. This SlideShare explores the concept of SLSA in brief.

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Short overview of the XML-RPC protocol for XML-based RPC services. XML-RPC is a remote procedure call protocol using XML as data format and HTTP as transport protocol. It is a simple mechanism to call remote procedures on a machine with a different operating system. XML-RPC is language and platform independent. XML-RPC libraries are available in Java and other languages. XML-RPC is not more than its name implies and thus is very simple and lean. This means that it lacks most of the features that SOAP/WSDL web services provide.

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We often optimize our software for performance, but what also optimizing our development teams for happiness? Take a look at how the tools you choose for your development team can impact developer happiness, and learn how to keep your teams happier and more productive. *The graph on slide 3 is fabricated data, because studies also show that people are more likely to believe statements accompanied by scientific data.*

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Data spaces in distributed environments should be allowed to evolve in agile ways providing data space owners with large flexibility about which data they store. Agility and heterogeneity, however, jeopardize data exchanges because representations may build on varying ontologies and data consumers may not rely on the semantic correctness of their queries in the context of semantically heterogeneous, evolving data spaces. Graph data spaces are one example of a powerful model for representing and querying data whose semantics may change over time. To assert and enforce conditions on individual graph data spaces, shape languages (e.g SHACL) have been developed. We investigate the question of how querying and programming can be guarded by reasoning over SHACL constraints in a distributed setting and we sketch a picture of how a future landscape based on semantically heterogeneous data spaces might look like.

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In the past six months, the AI landscape has undergone a massive transformation, ushering in a new era of productivity with the latest in Large Language Models (LLMs) and AI technology. This deep dive unlocks how to: Create CustomGPT Models: No coding needed to tailor AI for your unique projects. Integrate your own data, including PDFs and Excel sheets, making information handling a breeze. Plus, discover how to call your own actions/integrations for even more personalized utility. Navigate Advanced Prompting: Overcome AI's memory limits and utilize Retrieval-Augmented Generation for accessing your personalized data, streamlining how you interact with AI. Stay Ahead with AI Trends: Peek into the evolving world of LLMs, featuring newcomers like Google Gemini, Anthropic Claude, Open Sora, and Twitter Grok, and understand what their advancements mean for your productivity. Witness Real-Life Transformations: Through examples and prompt demonstrations, see firsthand how these AI strategies revolutionize routine tasks, from data analysis to content creation. Learn to leverage image output and input for advanced practical use cases, adding a new dimension to your productivity toolkit. No previous coding or AI experience is needed for this talk. Stay ahead in the fast-evolving world of work. Embrace the AI revolution and transform your workflow with advanced LLM techniques. Join us to ensure you're not left behind in the productivity race.

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