sureshmecad / domain_wise_projects

All Domains Projects at one place

Domain-Projects

Projects handled Domain wise

Data Science Applications:

1. Banking
     banks can make smarter decisions through fraud detection, management of customer data, risk modeling, real-time predictive
     analytics, customer segmentation, etc. In case of fraud detection, banks allow the companies to detect frauds that involve
     a credit card, insurance, and accounting. Banks are also able to analyze investment patterns and cycles of customers and
     suggest you several offers that suit you accordingly.
     
     
2. Finance

     Data Science has played a key role in automating various financial tasks. Just like how banks have automated risk analytics,            finance industries have also used data science for this task. Financial industries need to automate risk analytics in order to          carry out strategic decisions for the company. Using machine learning, they identify, monitor and prioritize the risks. These            machine learning algorithms enhance cost efficiency and model sustainability through training on the massively available                customer data. Similarly, financial institutions use machine learning for predictive analytics. It allows the companies to              predict customer lifetime value and their stock market moves.

3. Manufacturing

     Data Science is being extensively used in manufacturing industries for optimizing production, reducing costs and boosting the
     profits. 
     
     
4. Transport

            Data Science is actively making its mark in making safer driving environments for the drivers. It is also playing a key
     role in optimizing vehicle performance and adding greater autonomy to the drivers. Furthermore, in the transport sector, Data
     Science has actively increased its manifold with the introduction of self-driving cars.
     
            Also, various transportation companies like Uber is using data science for price optimization and providing better
     experiences to their customers. Using powerful predictive tools, they accurately predict the price based on parameters like a
     weather pattern, availability of transport, customers, etc.
     
     
5. Healthcare

        Medical Image Analysis
        Genetics and Genomics
        Drug Discovery
        Predictive Modeling for Diagnosis
        Health bots or virtual assistants
        
        
6. E-Commerce

       Data Science is also being heavily used in collaborative filtering, where it forms the backbone of advanced recommendation              system. Using this technique, the e-commerce platforms are able to provide insights to the customers based on their                      historical purchases and purchases made by people of the same style. These type of hybrid recommendation systems, consisting            of both collaborative and content-based filtering are helping the industries to provide better services to their customers.