[Video Example] Introduction to Pipeline Pilot Features and Analysis Case Studies

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A powerful tool essential for massive data processing and complex analysis.

In this video, we will introduce the features of "Pipeline Pilot" and provide analysis examples. Pipeline Pilot is a tool that enables large-scale data processing and analysis, automation of tasks, and visualization of workflows. [Content] - Why Pipeline Pilot is necessary - Features and characteristics of Pipeline Pilot - Examples of analysis using machine learning with Pipeline Pilot If you have any questions or uncertainties, please feel free to contact us.

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[Video Example] Introduction to Pipeline Pilot Features and Analysis Case Studies

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- Why Pipeline Pilot is necessary - Features and characteristics of Pipeline Pilot - Examples of analysis using machine learning with Pipeline Pilot *If you have any questions or uncertainties, please feel free to contact us.*

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[Notice] We will hold an online seminar titled "Examples of Using Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

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The second installment of the online seminar that received a great response the other day! We will introduce case studies utilizing "tools" with the theme of the most frequently mentioned "keyword of interest" from the survey responses on the seminar day: [Machine Learning]. This seminar is recommended for those who want to know specific use cases such as "What can 'Machine Learning' actually do?" and "When should I use 'Machine Learning'?" This time, we will take a slightly different perspective and present case studies of "Machine Learning" applications using tools in a broad context, including "multi-objective optimization using Machine Learning" in 'Materials Informatics (MI)', "Data Science", and "Image Recognition Processing". ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪★

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[Notice] We will hold an online seminar titled "Examples of Utilizing Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

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The second installment of the online seminar that received a great response the other day! We will introduce case studies utilizing "tools" on the theme of the most frequently mentioned "machine learning" from the survey responses on the seminar day regarding "keywords of interest." This seminar is recommended for those who want to know specific use cases such as, "What can 'machine learning' actually do?" and "When should I use 'machine learning'?" This time, we will take a slightly different perspective and present case studies of "machine learning" applications using tools in a broad context, including "multi-objective optimization using machine learning" in "Materials Informatics (MI)," "data science," and "image recognition processing." ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪ ★

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[Notice] We will hold an online seminar titled "Examples of Utilizing Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

  • Company news

The second installment of the online seminar that received a great response the other day! We will introduce case studies using "tools" with the most frequently mentioned keyword from the survey responses on the seminar day: "Machine Learning." This seminar is recommended for those who want to know specific use cases such as "What can 'Machine Learning' actually do?" and "When should I use 'Machine Learning'?" This time, we will take a slightly different perspective and present case studies of "Machine Learning" applications using tools in "Materials Informatics (MI)," including "multi-objective optimization using Machine Learning," "data science," and "image recognition processing." ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page: www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪ ★

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[Notice] We will hold an online seminar titled "Examples of Utilizing Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

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The second installment of the online seminar that received a great response the other day! We will introduce case studies utilizing "tools" with the theme of the most frequently mentioned "keyword of interest" from the survey responses on the day of the seminar: [Machine Learning]. This seminar is recommended for those who want to know specific use cases such as "What can 'Machine Learning' actually do?" and "When should I use 'Machine Learning'?" This time, we will take a slightly different perspective and introduce case studies of "Machine Learning" using tools from a broad perspective, including "multi-objective optimization using Machine Learning" in 'Materials Informatics (MI)', "Data Science", and "Image Recognition Processing". ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪★

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Our company develops and sells a "Maintenance Management System" for managing and operating various plants, factories, and other facilities and assets. Currently, this system is undergoing significant evolution into one that incorporates IoT technologies, such as sensor information and input from tablet devices, as well as AI technologies like machine learning, featuring functions for failure prediction and automatic scheduling. Additionally, as part of the recent trend towards digital transformation (DX), there is a growing movement to digitize and automate manufacturing processes and research and development sites in factories to enhance operational efficiency. In line with this trend, our company provides a solution aimed at improving efficiency in research and development environments, known as the Laboratory Information Management System (LIMS), which includes features such as workflow management, data tracking, data management, data analysis, and integration of electronic lab notebooks.

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