ADVANCEMENTS IN ML ALGORITHMS FOR REAL TIME APPLICATIONS, KPR Institute Engineering and Technology, Autonomous Engineering Institution, Coimbatore, India

Lead to a wide range of outcomes, from a better understanding of how algorithms work to becoming proficient in building and deploying machine learning models.

Event started at 9.30 am by welcoming the guest and in First day of session we brainstormed the existing real time applications of artificial intelligence.
Machine learning is being increasingly used in real-time applications to automate and optimize processes, improve decision-making, and provide personalized experiences to users. Some of examples include
Fraud detection: Machine learning algorithms can analyze financial transactions in real-time and flag any suspicious activity, allowing fraud to be detected and prevented.
Predictive maintenance: Machine learning models can monitor equipment and predict when maintenance will be needed, helping to prevent downtime and reduce maintenance costs.
Personalized recommendations: Machine learning algorithms can analyze a user's browsing and purchase history in real-time to make personalized recommendations, increasing engagement and sales.
Autonomous vehicles: Machine learning models can analyze real-time data from sensors and cameras to control the movements of autonomous vehicles, ensuring safe and efficient driving.
Healthcare: Machine learning can be used to analyze patient data in real-time to detect health risks, diagnose illnesses, and provide personalized treatment recommendations.
studying machine learning can help individuals develop critical thinking and problem-solving skills, as well as deepen their understanding of statistics, mathematics, and computer science
In the second day of the session we did few hands-on session on real time capstone projects and updated our digital profile.Overall, machine learning in real-time applications is rapidly evolving and has the potential to revolutionize many industries by providing real-time insights and automating processes. on the second day session ended with little feedback and photography.