IBM on Thursday said that it was acquiring application modernization assets from Advanced in an effort to enhance the mainframe application and data modernization services of its consulting business.

Advanced, which is headquartered out of Birmingham, UK, provides mainframe modernization and OpenVMS and VME migration services.

The assets and services acquired from Advanced are expected to complement the capabilities of IBM watsonx Code Assistant for Z , the company said in a statement.

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Značky: #IBM, #Rozne, #Analytics

No question about it, Python is a crucial part of modern data science. Convenient and powerful, Python connects data scientists and developers with a galaxy of tools and functionality, in convenient and programmatic ways.

Still, those tools sometimes come with assembly required, sometimes a lot of it. Because Python is a general-purpose programming language, how it’s packaged and delivered doesn’t speak specifically to data scientists. But various projects deliver Python to that audience in a way that’s prepackaged, with little to no assembly required—something regular Python users can benefit from, too.

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Značky: #Rozne, #Analytics, #Python

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of acquiring data, training models, serving predictions, and refining future results.

Created by the Google Brain team and initially released to the public in 2015, TensorFlow is an open source library for numerical computation and large-scale machine learning. TensorFlow bundles together a slew of machine learning and deep learning models and algorithms ( aka neural networks ) and makes them useful by way of common programmatic metaphors. A convenient front-end API lets developers build applications using Python or JavaScript , while the underlying platform executes those applications in high-performance C++. TensorFlow also provides libraries for many other languages, although Python tends to dominate.

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Značky: #Analytics, #TensorFlow, #Rozne, #Google

The convergence of artificial intelligence and edge computing promises to be transformative for many industries. Here the rapid pace of innovation in model quantization, a technique that results in faster computation by improving portability and reducing model size, is playing a pivotal role.

Model quantization bridges the gap between the computational limitations of edge devices and the demands of deploying highly accurate models for faster, more efficient, and more cost-effective edge AI solutions. Breakthroughs like generalized post-training quantization (GPTQ), low-rank adaptation (LoRA), and quantized low-rank adaptation (QLoRA) have the potential to foster real-time analytics and decision-making at the point where data is generated.

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Značky: #Analytics, #Rozne

Are you learning the R programming language? Do you want to learn how to do more tasks with R? Check out our Do More With R tutorials below -- many with videos shorter than 10 minutes.

In the table below, you can easily search all the tutorials by task, general topic, and specific R packages.

Available categories: big data, collaboration, dataviz, data analysis, data export, data import, data wrangling, ggplot, GIS, Microsoft, programming, RStudio, and vscode.

Some examples:

ggplot and other R data visualizations

Do you need to make static plots with R? Interactive graphs? Animations? Search below for terms such as ggplot, dataviz, and color. You'll get results such as Add color to ggplot2 visualization with the ggtext package , How to create interactive visualizations and linked interactive graphics with ggiraph and How to use built-in R colors and external palettes

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Značky: #Analytics, #Rozne

Many organizations reach a stage in their growth where the monolithic applications that once served them well start to hold them back. Perhaps the business needs new functionality that the existing architecture can’t support, or more flexible ways to store and access data for their apps. Team growth, conflicting performance requirements, and new competitive technologies can also pose a challenge to a singular, monolithic codebase. Adopting an event-driven microservices architecture can help you address these challenges.

Microservices overcome the limitations of monolithic apps by dividing those apps into small, purpose-built services, which can be custom tailored to the business problem they’re meant to solve. They provide you with the freedom to choose your own programming languages, frameworks, and databases as you see fit. Microservices can remodel, manage, and store data according to their own needs, providing you with complete control over how best to solve your business problems.

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Značky: #Rozne, #Microservices, #Containers, #Kubernetes, #Analytics

Whether we realize it or not, most of us deal with artificial intelligence (AI) every day. Each time you do a Google Search or ask Siri a question, you are using AI. The catch, however, is that the intelligence these tools provide is not really intelligent . They don’t truly think or understand in the way humans do. Rather, they analyze massive data sets, looking for patterns and correlations.

That’s not to take anything away from AI. As Google, Siri, and hundreds of other tools demonstrate on a daily basis, current AI is incredibly useful. But bottom line, there isn’t much intelligence going on. Today’s AI only gives the appearance of intelligence. It lacks any real understanding or consciousness.

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Značky: #Analytics, #Rozne

Aerospike Database has been outfitted with native support for JSON document models in the latest, version 6 release. The update also adds massively parallel secondary indexes.

Aerospike Database is the NoSQL database underlying the Aerospike Real-time Data Platform. Aerospike Database 6, unveiled April 27, both introduces support for JSON document data models, and promises to deliver sub-millisecond performance at gigabyte-to-petabyte scale. The JSON and JSONPath query support enable storage, searching, querying, and management of richer and more varied data.

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Značky: #Database, #Analytics, #Rozne

In 2011, James Dixon, then CTO of the business intelligence company Pentaho, coined the term data lake . He described the data lake in contrast to the information silos typical of data marts , which were popular at the time:

If you think of a data mart as a store of bottled water—cleansed and packaged and structured for easy consumption—the data lake is a large body of water in a more natural state. The contents of the data lake stream in from a source to fill the lake, and various users of the lake can come to examine, dive in, or take samples.

Data lakes have evolved since then, and now compete with data warehouses for a share of big data storage and analytics . Various tools and products support faster SQL querying in data lakes , and all three major cloud providers offer data lake storage and analytics. There's even the new data lakehouse concept, which combines governance, security, and analytics with affordable storage. This article is a high dive into data lakes, including what they are, how they're used, and how to ensure your data lake does not become a data swamp.

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Značky: #Rozne, #Analytics