No need for commissioned development! We will introduce how to utilize machine learning software that provides ready-to-use features as standard, based on real examples!
Are you facing issues like these? ◆ Unable to understand or explain the content of algorithms built with machine learning ◆ Being told to consider machine learning, but there are few tools available for immediate use ◆ Receiving proposals for project implementation, but the costs are too high to afford... etc. In the "Seminar Materials on Machine Learning Using SPM and Predictive Analysis of Concrete Strength," we will take concrete as an example and explain: ◆ Why traditional statistical methods are not being effectively utilized? ◆ Why is machine learning being utilized? ◆ How has machine learning been applied?
Inquire About This Product
basic information
SPM (Salford Predictive Modeler) is a machine learning software developed by Salford Systems located in San Diego, USA. It is equipped with four powerful analytical engines: 1. CART 2. MARS 3. TreeNet 4. Random Forest Not only can it be used as a tool, but the analytical logic built using the analytical engines can also be output as programming languages such as C or Java, making it possible to integrate into your existing systems.
Price range
P5
Delivery Time
Applications/Examples of results
It is utilized across a wide range of industries, from financial institutions to manufacturing, logistics, and retail.
catalog（13）
Download All Catalogs
![[Case Study] Ideal for Lithium-Ion Battery Material Development 'Materials Studio' *Free case study available!](https://image.mono.ipros.com/public/catalog/image/01/853/582890/IPROS44299245369553055023.jpeg?w=120&h=170)
Company information
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.