Machine Learning for Multi-purpose Business Applications
When you visit YouTube or Netflix to watch a movie or a video, you will find content similar to the content that you have watched before. When you misspell a word in a search engine, you will receive the intended word as a suggestion almost all the time. How is it possible? That’s Machine learning working behind the scenes. So first, let’s take a look at what Machine Learning is about.
What is Machine Learning?
It’s all about understanding data and statistics, roughly speaking, it’s a process of using algorithms to find patterns in data to predict possible outcomes based on the perceived data. Let’s take a look at how your email service identifies SPAM emails. These spam filters identify patterns that look suspicious based on previous spam occurrences to generalize the procedure for SPAM identification, further the attachments and the links included in the email and the domain reputation where the email is originated will be considered by these algorithms when
identifying suspicious emails. These algorithms are constantly “learning” from what they experience and adapt to changes along the way.
Machine Learning goes well beyond SPAM filtering. Google translate uses Machine learning algorithms to translate what is said into actionable text. Facebook uses computer vision to scan photos and identify faces. Video Streaming websites use recommendation models to provide video recommendations to their users. ML algorithms can predict transportation traffic patterns, identify weather patterns, detection of manufacturing defects, fraud detection using ML models, banks and other financial institutions can identify unusual activity when attempting transactions, companies utilize ML models in the early stages of recruitment procedures to filter the ideal candidates for job postings, in the health sector, these algorithms can be used for medical diagnosis. The uses are just immense, ML has been adopted by many organizations that operate in different fields of work to make significant impacts on their needs and requirements.
Should your organization adopt Machine Learning?
With precise implementation, your organization can harness the power of Machine learning to solve a multitude of problems and to make significant growth in a minimal time frame. Your organization might have an enormous amount of data that has not been utilized for beneficial purposes and for substantial gains. Customer usage data and demographics, purchase behavior, pricing, inventory, delivery procedures these areas have a direct impact on customer behavior and organizational growth. Understanding these unexplored data and performing analytics may not sound as simple as it may, though thanks to the rapid improvement of computing power and cloud server capacity, it is possible to mine enormous amounts of data to analyze and make helpful predictions, as more data is analyzed by these models better they perform.
To make a good Machine Learning system to understand the unexploited data of your organization, you need human resources who are specialized in data science/Machine Learning and Artificial Intelligence.
What are the benefits your organization can get by adopting Machine Learning?
With the myriad applications of machine learning, all kinds of businesses can yield profits in terms of exponential gains and collective improvements in different areas of your organization.
Machine Learning facilitates your organization to make instantaneous decisions that could be beneficial in the long run by allowing organizations to process and analyze information quicker than ever before. As an example, ML systems trained to detect anomalies in your organization’s security scope can identify suspicious behaviors like attempts of data breaches; therefore, the tech teams who are responsible for the security of the organization can take preemptive measures to prevent these types of data breaches or mitigate the impact of a security breach. This could lead your organization to avoid costly corrective actions and maintain your organization’s reputation.
In the present day marketplace, personalized customer interaction is more effective in improving sales and building a reputation by driving more traffic towards your online business platforms. Machine learning systems are capable of analyzing user behavior and providing tailored product recommendations to drive more sales and improve customer satisfaction.
Businesses often struggle to cope with the rapid changes of the business landscape, as a result, your organization could be under enormous pressure in predicting market trends and customer behavior. By adopting machine learning technologies, your organization can meet increasing forecasting demand with greater efficiency, which can help save unnecessary expenses and effective inventory management.
ML models with automation can help your organization’s human resources to be utilized more efficiently by eliminating the human interactions for repetitive tasks such as document searches, data extractions and cross-referencing. Companies can reduce expenses for information gathering activities while allowing their employees to engage in more value-added activities.
Predictive machine learning models can help manage and maintain capital assets of your organization more efficiently by collecting performance data from the devices/assets that require costly maintenance to forecast the remaining lifetime and predicting possible maintenance schedules to increase the sustainability of these assets.