Is there such a thing as too much data? We don't think so. Because the more data you have, the clearer a picture you can paint of how your software engineering team is doing. At the same time, you probably don't have a lot of time to do analysis. So VZBL makes your data accessible to an AI so you can answer your burning questions almost instantly.
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#day99 of #100daysofcode Mastering two complex problems: 1. Score after flipping matrix: Navigated through matrix transformations with finesse to maximize scores. 2. Find and replace pattern: Implemented efficient pattern matching algorithms to streamline data manipulation.
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Vice President @ Mechanical Orchard | Marketing I GTM I Customer Strategy I Partner Marketing
Understanding the behavior of legacy systems is critical for modernization success. While code is a key component its not all. Here are 8 different types of data that can help you comprehensively understand the exact behavior of a legacy system. Mechanical Orchard Mikey McCormackDan PodsedlyIrene Sandler #norisk #legacymodernization #cloudmodernization
How do you define legacy system behavior? Code alone isn't enough. In fact, we've identified 8 different types of data that, collectively, help us build a modern replica of the behavior of a deeply entrenched legacy system.
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How do you modernize a legacy system? Here is an interesting holistic approach.
How do you define legacy system behavior? Code alone isn't enough. In fact, we've identified 8 different types of data that, collectively, help us build a modern replica of the behavior of a deeply entrenched legacy system.
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At the Google Cloud Partner Summit keynote, Kevin Ichhpurani talked about the massive opportunity for Gen AI. Specifically, Kevin talked about Gen AI leading the cloud disruption. He talked about getting your data ready for Gen AI, having your data state in order, deduping data, getting rid of data silos, having your data labeled and that as a customer, you have to modernize your applications and move them to the cloud. At Mechanical Orchard, we appreciate and respect the opportunity of unlocking the true potential of legacy applications by “freeing” and unlocking the true potential of data.
How do you define legacy system behavior? Code alone isn't enough. In fact, we've identified 8 different types of data that, collectively, help us build a modern replica of the behavior of a deeply entrenched legacy system.
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Big Data Life Science Software Solutions. It has been recognised that harnessing the power of big data has become, perhaps essential. We explore here https://bit.ly/3Ew1eg1
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Big Data Life Science Software Solutions. The last number of years has brought unprecedented development in life science research. It has been recognised that harnessing the power of big data has become, perhaps essential. We discuss here https://bit.ly/3Ew1eg1
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🚀 Dive into the world of memory management in Go with this blog post! 💻 Learn how Go uses a neatly organized stack of plates 🍽️ for temporary, quick access and a flexible heap of grains 🌾 for long-term storage. Discover the philosophy: "For the swift, stack it neat; for the vast, heap it sweet." 🧠 Improve your coding efficiency and understand the human approach to handling data. #GoProgramming #MemoryManagement #StackAndHeap #EfficientCoding #TechEducation
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Rerun 0.19 is out! 🔥 It introduces a Dataframe API to view and query back Rerun data as dataframes, and initial video support. Read the release blog post here: rerun.io/blog/dataframe
Rerun
rerun.io
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Recommendation System is a set of algorithms that can analyze our likes and dislikes and recommend us with cool new items. And most of the time, all the recommendations are perfect! https://buff.ly/3SMkwWi In our latest article, we are going to build a movie recommendation system using vector search and Qdrant. Also, throughout the article, we discuss the following: What is a recommendation system? What is a Vector Database? How can RAG improve the traditional recommendation system pipeline? How can we build a movie recommendation system using Vector search? How does the movie recommendation system work in code?
