?? We’re moving! ??? IMSL has officially moved under Perforce Software on LinkedIn! ?? Going forward, your favorite content, updates, and insights can be found under the Perforce Software LinkedIn profile.? At Perforce, we are committed to delivering a unified brand. By moving IMSL under Perforce LinkedIn, you’ll see our suite of tools designed to give you the DevOps Edge – from code to business-ready. Why follow? ?? This is where the DevOps outperformers are! If you want to stay ahead in the DevOps space, drive efficiency, and lead the charge in cutting-edge tech, you’ll want to be here. ???? #DevOps #Innovation???
Perforce IMSL
软件开发
Get actionable insights with IMSL Libraries, the largest, most tested, and trusted set of math & statistical functions.
关于我们
For 50 years, IMSL has provided the largest collection of commercially available mathematical and statistical functions for data mining and analysis. Organizations in finance, telecommunications, oil and gas, government, aerospace, and manufacturing depend on the robust and portable IMSL Libraries to efficiently build high-performance, mission-critical applications. Today, IMSL is a part of Perforce Software, a global leader in end-to-end software tools that include development, lifecycle-management, version-control, and code-analysis technologies and services.
- 网站
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https://www.imsl.com
Perforce IMSL的外部链接
- 所属行业
- 软件开发
- 规模
- 501-1,000 人
- 总部
- Minneapolis
- 领域
- Embedded Software、Data Mining、C++ Libraries、Java Libraries、Fortran Libraries、Python Libraries、Mathematical and Statistical Algorithms和Data Analysis
动态
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Predictive maintenance can reveal new insights, but it also generates massive amounts of data. From among these data streams, predictive maintenance uses statistical analysis to find Condition Indicators, i.e., sensor measurements that indicate a failure condition or are predictive of a failure condition.? Learn more in this blog post. >> https://ter.li/99yroj
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Find the minimum cost shipping routes between supply locations and demand locations. >> https://ter.li/u87fjq #transportationplanning #inventorymanagement
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What is parallel programming and how can numerical libraries help optimize your application performance? https://ter.li/rj7m5k #dataanalysis
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Take a high-level look at credit risk modeling, how it's used, and various models and algorithms commonly used by lending institutions to analyze and manage risk. https://ter.li/wggvvz #creditrisk #bankingtechnology #datascience
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Are you familiar with maintenance strategies used in manufacturing, industrial, and operational processes??? -Run to failure (R2F) is a simple but risky strategy where problems are addressed only after failure.??? -Preventative or routine maintenance reduces some risk but introduces extra costs and waste, since good components might be needlessly replaced.? -Condition-based maintenance (CBM) relies on sensors to indicate degradation of equipment, which improves costs since only degraded components are replaced.? -Predictive maintenance (PdM) combines CBM sensor technology and predictive modeling to predict time-to-failure or remaining useful life (RUL) of different components of a system, attempting to replace components at an optimal time.? Learn more about the intersection of these maintenance strategies in this blog post. >> https://ter.li/eqstqo
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Methods and functions to help you with pre-processing raw time series data before doing any formal analysis. https://ter.li/ljwrc1 #dataanalysis #statisticaldataanalysis
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ARIMA can be a valuable tool for extracting meaningful insights from time series data. Learn more about the ARIMA model and the auto_arima functions in IMSL. https://ter.li/jcwoi6 #timeseriesanalysis #ARIMA
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What is regression modeling and when should you use it? Find out as we explore this topic in-depth >> https://ter.li/8ptbn2
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How 3rd party numerical libraries can be incorporated into a Docker application to support writing advanced servlets. https://ter.li/kwgzx1 #docker #microservices