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Is Machine Learning a Rewarding tool for CIOs?

Construction Tech Review | Saturday, August 31, 2019

You might have probably heard about Machine Learning (ML). Do you know what it is and how it can add value to your business by resolving the problems? Let's have a look at some insights on this innovative invention.

FREMONT, CA: Machine learning (ML) is an essential application of artificial intelligence that is geared towards the development of computer programs to manage new situations through self-analysis, observation, self-training, and experience.

ML facilitates the advancement of the computer systems by exposing them to new scenarios, adapting and testing simultaneously using trend and pattern identification for better decision making in subsequent situations.

ML should not be confused with data mining and knowledge discovery in data (KDD) basis, which are of identical methodology.

It is a natural human tendency to learn and execute tasks and take decisions unconsciously. Thus, it becomes complex for a machine to mimic humans in an exact way.

Just like children, a machine needs extensive training for developing broad algorithms for its future behavior. The training techniques comprises rote learning, macro-operations, parameter adjustment, chunking, case recording, backpropagation, clustering, multiple model management, mistake correction, genetic algorithms, reinforcement learning, and learning based on explanation.

In a nutshell, the primary aim is to enable the machines to learn involuntarily without any human intervention or assistance and react to different scenarios accordingly.

Here are some of the ways CIOs can use Machine Learning for their business:

1. Recommending the right product: If you are an online retail business, then you know very well that the customers like to have personalized recommendations delivered to them. ML models evaluate the purchase history of the customer and the algorithms through the unsupervised learning process, detect the hidden patterns among the products, and then group them into clusters. Such models assist the organizations in making better item recommendation to their clients, hence motivating product purchase.

2. Predictive maintenance: Manufacturing firms keep a regular check on the on their corrective and preventive maintenance practices. However, these are very costly and inefficient. This is where ML emerges as the savior. ML enables the companies in this sector to pull out meaningful insights and patterns cloaked in their factory data. This particular process is known as predictive maintenance. It allows the companies to reduce the chances of unexpected failures and also to help in cutting down costs.

3. Easy detection of spam: Earlier email service providers used to adopt rule-based techniques to filter out spam. ML made it possible to eliminate spam mails by inventing new rules by making neural networks like the human brain. These networks identify phishing messages and junk mail and thus making it simple for the CIOs and IT teams to keep everything clean and simple.

4. Improvising precision of financial rules: ML is an expert in the field of financial analysis as well.  It is currently being used in algorithmic trading, fraud detection, portfolio management, and loan underwriting. Moreover, based on a report on 'The Future of Underwriting' published by Ernst and Young, continual data assessments are facilitated by ML for the detection and evaluation of anomalies and nuances. This enables the companies to improvise the precision of their financial models and rules.

5. Enhancing cybersecurity: ML helps improve the security systems of the business against cyber attacks. It enables new generation providers to build advanced technologies for quick and effective detection of unknown threats.

6. Facilitating correct medical predictions: In the healthcare sector, ML has provided significant help in identifying high-risk patients through advanced diagnostic tools and impactful treatment plans. ML can assist doctors in making an accurate diagnosis, recommend best medicines at affordable costs, and also predict readmissions. These insights and predictions are based on the availability of datasets of anonymous patient records along with their symptoms. Thus, ML helps in patient's fast recovery without any extraneous medicines. In a nutshell, it has brought a massive change in the healthcare domain by improving the patients' health at minimal costs.

7. Eliminating manual data entry: Today, CIOs can avoid significant issues like duplicate and inaccurate data with the predictive modeling algorithms of ML. ML enhances the performance of these processes by using the discovered data. Hence, it becomes easier for the workers also to utilize their time efficiently by carrying out the tasks in the same time period.

All the above applications make the machine learning a huge revolution in the digital innovation trend. Businesses can now operate their system more effortlessly and can take evidence-based decisions. Therefore, adopting ML can be a lucrative decision for your business.

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