As a matter of fact, Big data analytics has driven the past few years of machine learning. However, there are many things which remain unexplored. One needs to have knowledge and skills of frameworks such as the Hadoop Ecosystem to implement most big data projects. This MapReduce framework under Hadoop can scalability for distributed computing. As well as, big data projects require immense processing power. There are two common ways one could get such processing power such as cloud computing and parallel computing.
List of Big Data Analytics Projects
- Density-Based Clustering using MapReduce
- A Big data – AI Integration Approach
- K-nearest Neighbors Search by Random Projection
- Transfer to Rank for Top-N Recommendation
- Cyber security in Big Data
Interesting Big Data Use cases
Crime Prediction: Â Machine learning has the best scope for predicting crime. Historical data of crime locations, subjects, victim descriptions, time, and more will be used to model machine learning frameworks.
Fraud Detection: Be it text messages, emails, transactions or spoken word, fraud detection can be used. To evaluate that an email is fake or a transaction is shady requires more than human intelligence. This application has potential uses in a lot of domains and is mostly important part of any service.
Simulating and Predicting Traffic: The problem is that has been a long-standing problem. Models for simulating traffic with real-time data have been made. Moreover, taking it further, there is a need to make models that can properly predict traffic. No one in the field has been able to do it perfectly.
Final Thoughts
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