Machine Learning

Machine Learning - Artificial Intelligence Services

Machine learning (ML) is a branch of artificial intelligence that utilizes statistical approach and provides computer systems the ability to learn and improve performance from data without being explicitly programmed.

Machine learning is a field of computer science that mainly focuses on the development of computer programs that can access data and use it to learn for themselves. Today, machine learning is used in an extensive area of applications. The most popular example is Facebook’s News Feed that uses machine learning to personalize each member’s feed.

Machine learning involves processes that are similar to data mining and predictive analysis. Both involve searching through data to look for patterns and adjusting the program actions appropriately.

AQ4’s offer machine learning services that help organizations to develop custom solutions that help to process high volumes of data and run custom-made algorithms to act how to perform a specific task by themselves. 

Case: ML Implementation in Supply Chain Management by AQ4

Picture Credits DHL

AQ4 is working with partners and a set of clients to develop new age and on-the-edge solution to unlock cost savings and revenue potential in logistics business.

Discovering new insights from supply chain data and automation of operational process using set of Machine Learning and Image Processing algorithms can transform a business. Today the businesses are accumulating data not only through the Operational Data Stores of Enterprise Applications, but also contextual data, structured and unstructured, from several sensors, beacons, cameras, devices and mobile apps with the in-field workforce. Therefore, businesses will improve KPI's related to supplier quality, stock levels, demand, and logistics in the yards, warehouses and during transport. "Reducing freight costs, improving supplier delivery performance, and minimizing supplier risk are three of the many benefits machine learning is providing in collaborative supply chain networks", says a 2017 by Salliau & Verstrepen.
Large logistics operators like DHL are already investing in new technologies and demonstrating its benefits. Thus, Machine Learning is bringing about an extension to application of previously known computer and automation technologies.

Common use cases of machine learning services include:

  • Detection of fraudulent transactions
  • Detection of Network intruders
  • Spam filtering
  • Predictive maintenance like to predict weather patterns or to predict some other climatic conditions
  • To build the news feed
  • To categorize images such as MRI Studies, photos or satellite images
  • To enable software to respond accurately to voice commands
  • To translate languages in text or audio form.