Introduction to Applications of Machine Learning
Artificial Intelligence is a very popular topic which has been discussed around the world. Machine learning is one of the most exciting technologies of AI that gives systems the ability to think and act like humans. machine learning is a subfield of AI and has its various application which helps to make a prediction, analysis, classification, etc. that is recognized by the companies across several industries(like Financial Service, Government, Healthcare, Transportation, etc.) that deal with huge volumes of data needed by the organizations in running their business effectively and to get an edge over their competitors.
Applications based on Line of Business
Let’s categorized the uses of machine learning based on the line of business.
1. Manufacturing
As an Industry, Manufacturing is the backbone of any healthy economy.From optimized resource planning to cut short the time to market, Machine learning is helping the transformation of the manufacturing sector.
2. Marketing
In a world of 25 billion-plus connected devices, machine learning plays a vital role in personalized digital marketing. Ads click prediction, showing relevant Ads to customers, identifying target customers, churn analysis, etc., are important applications of machine learning in the marketing sector.
3. Healthcare
Healthcare is probably the sector where the impact of artificial intelligence will be miraculous. As a sector historically, healthcare is highly dependent on manual intervention and highly skilled professionals. But in today’s world, machine learning enables us to make data-driven decisions that can prevent diseases, helps in better patient diagnosis, faster root cause detection, etc. Tech giants Google, Facebook, Qualcomm, etc., are investing billions in ML-based healthcare research.
4. Digital Media and Entertainment
Machine learning has tremendous applications in digital media, social media and entertainment. Personalized recommendation (i.e. Youtube video recommendation), user behavior analysis, spam filtering, social media analysis, and monitoring are some of the most important applications of machine learning.
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5. E-commerce
Advancements in machine learning is also a key stakeholder in today’s e-commerce transformation. When we are browsing an e-commerce site, we can see personalized recommendations, which is achieved through content-based or collaborative filtering. The availability of large-scale user data is probably what keeps e-commerce giants ahead in the race than retailers. Machine learning is also used in fashion designing.Indian E-Commerce giant Myntra has multiple brands that are designed by deep learning systems.
6. Energy
Energy is one of the core sectors where machine learning solutions are bringing huge differences. Power consumption and requirements prediction, dynamic per unit cost maintenance, hardware lifespan analysis are part of machine learning applications in this sector.It is also being used for managing alternate energy resources.
7. Banking and Financial
In a digital economy, machine learning helps banks and other financial organizations to safeguard from frauds, money laundering, illegal financial detection, identifying valuable customers, etc. It also helps financial organizations with stock market predictions, demand forecasting, offering personalized banking solutions to the customers, etc.
8. Automobile
An automobile is another sector where the impact of machine learning is huge. Almost every automobile manufacturer uses artificial intelligence to optimise fuel consumption, breakdown prediction, and even self-driving. Tesla, Nvidia, etc., are investing a lot over self-driving cars.
9. Customer Service
Almost every organization is using chatbots for customer services. Chatbots are cost-effective and changing the customer service landscape to a large extent. Automated translation and state-of-the-art text-to-speech and speech to text systems are helping to overcome the language barrier.
10. Governance and Surveillance
Machine learning is reshaping modern Governance and defense systems. With the help of the state of the art deep learning algorithms and infrastructures, security agencies are now enabled with real-time image detection, drone surveillance, automated social network monitoring, etc.
11. Insurance
Insurance is sitting on a gold mine of data that is traditionally being used only at the application level as an industry. With the help of artificial intelligence and machine learning, Insurers are now empowered with valuable insights from the data they possess. Machine learning is being used for faster claims recovery, fraud detection, renewal prediction, churn analysis, etc. From New new business today two transactions, it can be used at every stage of the policy life cycle.
12. Human Resource Management
Though it is at an early age, machine learning is now also being used to manage human resources. Organizations like Amazon, HDFC bank, etc., are using bots and video analytics at various phases of their recruitment process. IBM Watson is also used for human resource optimization.
13. Transportation
While using app cab rides, you must have observed the dynamic pricing and surge charges at some point in time. This is also an application of machine learning. User data is also being used to predict the shortest path.
14. Art and Creativity
Machine learning is no longer being used to automate the mundane jobs for humans; it is also being used for creative purposes. Artistic style transfer, text to image synthesis, automated soundtrack and video creation, image colouring, social media chatbots, etc., are some of the cool applications of machine learning in this sector.
Trends in Machine Learning
From the beginning of the internet era, the applications of machine learning are increasing exponentially. Let’s look at the world wide google trends for machine learning for the period of 2004 to 2019.
Source: https://trends.google.com
Conclusion
Machine learning and artificial intelligence are no longer science fiction or part of Hollywood movies; their applications are everywhere in our day to day life. Every innovation has a positive and negative side; machine learning is also not an exception. Though in this article, we discussed mainly the positive applications of machine learning, it can also be used as evil. Deep learning systems like Deep Fakes have a huge impact on human life and privacy. As a growing field of study and applications, the need for strong data governance is also emerging as a necessity.
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