5 Applications of Deep Learning

 

It is now clear that Artificial intelligence will be at the center-stage of the so-called 4th industrial revolution. AI and its subsets, deep learning and machine learning (ML), are being applied in almost every sector of business intelligence. It is widely accepted that every modern application now and in the future must have some form of AI baked in or as a foundation.

Deep learning, a relatively new subset of ML, aims to teach computers how to use previous information to learn and make intelligent decisions with the use of neural networks. There are several ways that you can apply deep learning techniques in your business applications.

 

Customer Care

 

This is one of the hottest areas where businesses are applying deep learning techniques to personalize customer care. With the help of data mining, analysis and self-learning algorithms in your CRM, your business can streamline the way you approach solving customer’s problems. Deep learning can also make it possible to craft tailormade solutions for your customers’ problems based on past interactions.

 

Recruitment

 

The success of your business is highly dependent on the quality of the staff you bring on board. Recruitment of staff can be quite tedious and time-consuming due to the number of applicants and other factors. Deep learning is being applied to automate the process of shortlisting candidates and even assessing the ones selected.

 

Marketing

 

Most businesses already collect and store lots of data about their customers. That data is translated by deep learning algorithms to generate recommendations based on one’s interests. There are applications available out there that can analyze the performance of your marketing/advertising campaigns and generate recommendations.

 

Fraud Detection

 

This is an important application if you are in the financial sector. Algorithms present in new fraud detection systems can use previously acquired knowledge to detect fraudulent activity. Patterns and anomalies are observed in real-time transactions. Deep learning makes it possible to process lots of data and do it faster than humans.

Competitor Analysis

 

Analyzing competitors has become a data-intensive undertaking in the age of big data and e-commerce. It is impossible to keep track of what your competitors are up to with traditional tools and analysts. Deep learning-based tools and applications available today can help you keep a close eye on competitors and even suggest ways to beat them.

Conclusion

Finally, recent advancements in mathematics and computing power have given birth to deep learning. It’s bringing us closer to the original idea of intelligent machines and practical applications of AI in the real world. Making use of AI-driven applications will give your business a competitive edge by making smarter decisions and streamlining processes.

 

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