Topic – Data Science Applications in Real World | 2022
“Data science is the discipline of making data useful.”
To me, the idea of usefulness is tightly coupled with influencing real-world actions.
In this article, we will discuss the top 11 real-world applications of Data Science!
Before we start, let us look at the sectors h=where data science is used widely!
Data science applications in Engineering
Data Science has huge applications in engineering and research.
Ranging from recommendation systems, speech and object recognition to deploying dialog flow chatbots for making life easier for people, data science and artificial intelligence, has it all!
Some advantages of using data science in engineering are-
- Image and Speech Recognition systems
- Natural Language Generation
- Recommender Systems
- Large Scale Production of Predictive Software
- Business Intelligence
Data Science Applications in Finance
Data Science has become very important in the Finance Industry.
Companies analyze the trends in data through business intelligence tools. Anomaly detection in transactions, play a crucial role in Finance sectors.
So, Data Science and Finance is related shoulder to shoulder.
Some advantages of using data science in finance are-
- Fraud Detection and Analytics
- Risk Analytics
- Consumer Analytics
- Customer Churn Detection
- Algorithmic Trading
Data Science Applications in Healthcare
The use of Data Science and AI in consumer health applications is already helping people.
AI increases the ability for healthcare professionals to better understand the day-to-day patterns and needs of the people they care for.
With that understanding, they can provide better feedback, guidance, and support for staying healthy.
Some advantages of using data science in healthcare are-
- Cancer and Tumor Detection (Disease Prediction)
- Gene Pattern Recognition
- Fitness Prediction Systems
- Automated Systems to ensure Health and Fitness
- Mental Health Assistants
Data Science Applications in Education
Some innovative applications of Data Science in Education, range from student curriculum analysis to recruitment of the best candidate!
Data is everywhere, so is student data!
The student data generated from a competitive exam can help human being predict the best candidates for a certain institution or subject, thanks to data science!
Some advantages of using data science in education are-
- E-learning by Chatbot Systems
- Study Help Chatbot Assistants
- Efficient Design of Curriculum
- Student Recruitment
- Case Studies and Research
These are some of the most important industries where Data Science is used widely!
Let us now look at 11 breathtaking applications of Data Science!
1. Speech Recognition
One key component of a Voice user interface (VUI) is automated speech recognition (ASR) that enables users’ speech to be translated into text.
Many studies show that automated speech recognition tools have an accuracy of more than 90%.
Speech recognition, also known as automatic speech recognition (ASR), computer speech recognition, or speech–to-text, enables a program to process human speech into a written format.
2. Augmented and Virtual Reality
The terms “virtual reality” and “augmented reality” get thrown around a lot.
Virtual Reality completely take over your vision to give you the impression that you’re somewhere else.
Whereas virtual reality replaces your vision, augmented reality adds to it. AR devices, such as the Microsoft HoloLens are transparent, letting you see everything in front of you.
VR replaces reality, taking you somewhere else. AR adds to reality, projecting information on top of what you’re already seeing. They’re both powerful technologies!
3. Image Recognition
Image recognition is classifying data into one bucket out of many. This is useful to work: you can classify an entire image or things within an image.
Image detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class in digital images and videos.
In the recent times of the pandemic, image recognition systems are widely used to proctor people wearing masks or not.
4. Recommendation Systems
A recommender system refers to a system that is capable of predicting the future preference of a set of items for a user, and recommend the top items.
One key reason why we need a recommender system in modern society is that people have too many options to use due to the prevalence of the Internet.
Be it website recommendation, movie recommendations by Netflix , product recommendations by Amazon and video recommendations by YouTube, Recommendation Systems is everywhere!
5. Virtual Assistance
The AI-powered Virtual assistance is a huge application in AI and Data Science.
From chatbots created to assist day to day needs of humans, to personal fitness and health assistant, mental health chatbots, virtual assistance is everywhere!
This approach promotes a healthy lifestyle by encouraging patients to make healthy decisions, saves their time waiting in line for an appointment.
This allows doctors to focus on more critical cases.
6. Data Science in Biotechnology
For human beings, it is an extremely tedious and time-consuming process to analyze the vast amount of data that is present in a single person’s DNA.
Data Science can be made much more efficient and accurate by utilizing machines for their core purpose- to make tiresome tasks less challenging.
By using machine learning algorithms to compare the different gene expression levels in malignant and normal tissue samples of a patient diagnosed with cancer.
Predictions can be made about which genes have been mutated in that patient’s DNA.
The algorithms would train and make these predictions based on how often a gene is expressed in a malignant sample and compare this to the same gene in a normal sample, adding new information with each new set of data that it is fed.
7. Natural Language Generation
Natural-language generation is a software process that produces natural language output.
Automated NLG can be compared to the process humans use when they turn ideas into writing or speech.
NLG has existed since ELIZA was developed in the mid-1960s, but the methods were first used commercially in the 1990s.
The popular media has paid the most attention to NLG systems which generate jokes, data-to-text systems, textual summaries and much more!
8. Anomaly Detection Systems
An anomaly-based intrusion detection system (IDS) is any system designed to identify and prevent malicious activity in a computer network.
A common need when you analyzing real-world data-sets is determining which data point stand out as being different to all others’ data points. Such data points are known as anomalies.
The goal of anomaly detection (also known as outlier detection) is to determine all such data points in a data-driven fashion.
Anomalies can be caused by errors in the data but sometimes are indicative of a new, previously unknown, underlying process.
In video games, artificial intelligence (AI) is used to generate responsive, adaptive or intelligent behaviors primarily in non-player characters (NPCs) similar to human-like intelligence.
Artificial intelligence has been an integral part of video games since its inception in the 1950s.
Blockchain is a decentralized network of computers that records and stores data to display a chronological series of events on a transparent system.
Data Science and Blockchain when combined, can provide some robust outcomes.
These merges of tech can be used for various purposes including financial security, supply chain logistics, creating diverse datasets and more.
11. Stock Market Analysis and Prediction
The stock market is one of the most dynamic and volatile sources of data. The data is generated every second as the money never sleeps.
Stock market prediction aims to determine the future movement of the stock value of a financial exchange.
The accurate prediction of share price movement will lead to more profit investors can make.
Conclusion of Data Science Applications
Hope this helped you to get a better insight into how data science is used for the day-to-day tasks we do manually!
Start your career in Data Science and train your data to make such huge automated systems!
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