Note: original full article is here on my blog: https://www.pritamc.com/applications-of-data-science-machine-learning/
Let’s see how the different industries are implementing #DataScience techniques to bring efficiency to their operations
Some of the Industries Implementing Machine Learning
SocialMedia platforms, SearchEngines, Healthcare industry, Finance and banking industry, Public sector, Energy & Power sector, Oil and Gas, manufacturing, Retail and E-commerce, IT
- Optimize the overall user experience
- Recommendations about people, jobs, companies, potential buyers, things, and a lot more
They have a big share when it comes to implementing AI.
- Identify the spam or duplicate content
- Personalized search results
- Machine Learning helps search engines identify new ranking signal
- Proper ad targeting and ad quality.
- Improving the accuracy in diagnosis
- Making the use of Electronic Health Records (EHR) more effectively
- AI and ML to analyze medical images more effectively
- Make informed decisions
- Real-time analytics to track transactions, credit scores & other financial attributes.
- Provide personalized services and cross-sales.
- Detecting fraud transactions
- Identifying Dishonesty in tax reporting.
- Machine Learning and data analytics helps states to take security measures to prevent cyber attacks.
- Failure prediction
- Outage detection and prediction
- Dynamic Energy management
- Smart grid security and theft detection
- Preventive maintenance
- Improving operational efficiency
- Better models for drilling, exploration & for maintenance from historical data.
- Limiting the manpower in a very risky environment.
- Data management. O&G companies produce large data and big data is used to manage it.
- Predictive analysis of performance and quality.
- Fault detection & prediction.
- Final product price optimization
- Use of automation and robotics in factories to bring efficiency to work.
- Supply chain optimization
- Inventory management & demand forecasting
- Personalized product recommendation
- Leverage on predictive forecasting
- Understand and use the data on customer behavior and shopping patterns.
- Use the tools to improve and optimize the customer experience.
- Fraud prevention
- Intelligent Process Automation (IPA)
- Virtual digital assistants and chatbot
- ML can help in cybersecurity.
- Help enterprises to improve collaboration
There are endless possibilities when it comes to implementing AI in business. AI can solve the most complex problems.
AI and ML are useful to find the near future possibilities and useful insights based on historical data and trends. This is performed using machine learning techniques and statistical algorithms. These insights from historical data help businesses to make informed decisions to empower the organization and settle the profitable business.
Read the complete article here: https://www.pritamc.com/applications-of-data-science-machine-learning/
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Thanks 🙂