In recent years, technological advancement has contributed significantly to business growth and efficient management of available resources. Studies have shown that human beings are unique creatures and may have the ability to store memories and experiences. In simple terms, it means that you can gather data around you and create ideas of how to complete tasks or acknowledge new information effectively.
Deep learning (DL), a branch of artificial intelligence (AI), is a technological advancement that aims to replicate a human's ability to learn and advance in machines. It's a technology that allows computers to collect new data, change it, and present a helpful output with no human intervention.
There are many deep learning applications, as can be seen in self-drive cars, cancer detection monitors, and much more. This article walks you through the major deep learning benefits to a business, but before that, you need to understand what deep learning is.
Deep learning is a subset of machine learning in artificial intelligence that tries to imitate how the human brain operates. It drives several AI applications without human intervention.
However, it tries to draw similar conclusions as a human being could do by continually analyzing data or information with a logical structure. So, if you want to utilize deep learning, you can check out here to learn more about it and its impact on the digital business world.
It's important to understand that, while the Internet may positively impact your business, it also exposes your enterprise to criminal and villainous activities more than ever before. For instance, where do you store your sensitive data?
Data stored in servers may have higher chances of cyber-attack and illegal access. A study conducted in 2017 showed that businesses in the US lost an average of USD$3.6 million due to cyber-attack and swindling activities. The amount may increase as the years pass by.
One of the ways you can reduce losses is through prevention and early detection of fraud activities. It's important to understand that any fraudulent activity will not only cost you money but can also taint your business's reputation.
Thanks to deep learning, now you can utilize the AI-driven system to detect and prevent fraudulent activities, saving your customers and brand's reputation. Manual detection might be tricky on the flip side, considering that most fraudulent activities typically don't have a consistent pattern.
After detecting and classifying any dubious activity or transactions, the DL may advise taking the best course of action.
As a business owner, you depend on correct information to make accurate decisions at the desired time. However, it might be hard to get the right information from the ever-changing big data without utilizing artificial intelligence capabilities in recent years.
Deep learning makes it easier for enterprises to convert large data sets into useful information and intelligence. You can incorporate the acquired information into day-to-day activities and respond to changes in market patterns (demand and supply).
Thus, you may utilize deep learning to have a competitive advantage and assist in taking enterprising measures to be on top of the competition in real-time, improving the profit margin.
Feature engineering can be described as the process of acquiring features from raw data to explain an underlying problem better. In machine learning, feature engineering is an essential aspect as it may help improve the model's accuracy.
Consider the following example to understand feature engineering.
Let's say you are selling an apartment. The location of the building may play an important role when determining its price. Suppose the location is presented in terms of latitudes and longitudes. In raw form, those figures may mean nothing, but when put together, they show the exact location of the structure. The process of combining the two data sets to determine location is referred to as feature engineering.
On the other hand, deep learning uses an algorithm that can execute feature engineering on its own. It scans data to discover features that match up and put them together to better understand data without being directed to do so. This allows you to save a lot of time and money, thus helping improve your profit margin.
In this case, deep learning might help your business in the following ways.
It's important to understand that DL may have the capacity to consume an inexhaustible amount of unstructured data virtually. You may use the extracted data to analyze and improve your sales and marketing plans as per the customer behavioral patterns. This helps improve the customers' experience.
In deep learning, algorithms scan data faster, discovering features that correlate for easy understanding, helping you undertake necessary measures at the right time.
For instance, deep learning may help perfect the best offer for your client. Thus, the client will access the right offer at any given time, without you investing time to scheme and make the right offer visible to your customers.
Deep learning makes it easier for you to understand past customer purchasing patterns. This is possible because, with deep learning, you can be able to collect customers' information about how they utilize your products or services. You may use the acquired information to produce customized products. This can help improve your customers' experience, which increases the chances of customer retention.
As discussed above, deep learning may help your business grow, improve customer experience, and increase chances of customer retention. It's one of the latest technologies that each business should strive to utilize.
It also plays an important role in improving fraud detection, assisting in decision-making, simplifying product and brand promotion, and making it easier to extract information from ever-changing big data.
(Must read: Machine learning vs deep learning)
However, although it may play an important role in your business, businesses still have a lot to learn about deep learning, such as challenges and drawbacks you may encounter when installing this technology. Understanding them will help you develop strategies that can ensure you implement deep learning with no much hassle.
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