Machine Learning is the Solution to your Business Problems

By CIOReview | Monday, July 8, 2019

While sometimes it is possible to design a set of rules to handle the problem entirely without the need of ML, there are also well-set conditions where choosing ML over its traditional counterparts seems imperative.

FREMONT, CA: Despite the inquisitiveness for machine learning (ML) for the sake of business-related queries, most of the executives are finding it a challenge to deploy ML-based solutions for their business problems. It’s a challenge because the wide range of capabilities offered by ML can leave the companies in dilemma of where to deploy it for maximum gains while others are partly aware of the potential of the technologies like ML.

Business Problems within the Grasp of ML

While sometimes it is possible to design a set of rules to handle the problem entirely without the need of ML, there are also well-set conditions where choosing ML over its traditional counterparts seems imperative.

There are specific scenarios where ML can be effectively deployed to gain better results as compared to conventional methods. Here are some of them:

•  Face Detection

Designing a set of rules for machines to detect faces is an extremely uphill task; however, an algorithm trained to recognize faces can be highly effective in such cases.

•  Spam Filters

Though a bit of spam filtering is possible by rules, for instance, blocking IP addresses associated explicitly with spam, but most of the screening is contextual, involving the inbox content relevant to the specific user. ML can leverage the enormous volumes of spam that will prepare it as an effective spam filter.

•  Personalized Recommendations

Everyone is unique and so are their preferences for product, music, or movies. Major companies like Netflix, Amazon, and Spotify leverage rating and engagement from multitudes of items based on the past user behavior to predict and recommend the products that he may like.

•  Speech Recognition

It is challenging to identify human sounds based on rules or using a combination of sounds for the purpose. However, with ML, it is possible to identify patterns of speech while also allowing conversion of speech into text.

•  Purchase and Credit Card Fraud Detection

Rules can only be useful for a small portion of fraud detection as the fraudsters are using newer techniques to exploit the vulnerabilities of a system. ML can understand such patterns and prepare the systems better against future fraud cases.