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Presentation materials for a seminar on explainable machine learning software!

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?

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

OTHER

Applications/Examples of results

It is utilized across a wide range of industries, from financial institutions to manufacturing, logistics, and retail.

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Seminar Materials: Predictive Analysis of Concrete Strength Using Machine Learning

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