08/02/2022
Introduction about Data Science Second Batch
Introduction to Data Science Second Batch on Feb 20222
This video is about providing information about Data Science Second Batch To View Syllabus of Data Science class, click here https://drive.google.com/file/d/...
06/02/2022
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17/01/2022
Edge computing -
Edge computing is a form of computing that is done on site or near a particular data source, minimizing the need for data to be processed in a remote data center.
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is expected to improve response times and save bandwidth. A common misconception is that edge and IoT are synonymous. Edge computing is a topology- and location-sensitive form of distributed computing, while IoT is a use case instantiation of edge computing.
Edge computing use cases.
1) Autonomous vehicles
Autonomous platooning of truck convoys will likely be one of the first use cases for autonomous vehicles. Here, a group of truck travel close behind one another in a convoy, saving fuel costs and decreasing congestion. With edge computing, it will be possible to remove the need for drivers in all trucks except the front one, because the trucks will be able to communicate with each other with ultra-low latency.
2)Traffic management
Edge computing can enable more effective city traffic management. Examples of this include optimising bus frequency given fluctuations in demand, managing the opening and closing of extra lanes, and, in future, managing autonomous car flows.
With edge computing, there is no need to transport large volumes of traffic data to the centralized cloud, thus reducing the cost of bandwidth and latency.
3)Virtualised radio networks and 5G (vRAN)
Operators are increasingly looking to virtualise parts of their mobile networks (vRAN). This has both cost and flexibility benefits. The new virtualised RAN hardware needs to do complex processing with a low latency. Operators will therefore need edge servers to support virtualizing their RAN close to the cell tower.
4) Predictive maintenance
Manufactures want to be able to analyse and detect changes in their production lines before a failure occurs. Edge computing helps by bringing the processing and storage of data closer to the equipment. This enables IoT sensors to monitor machine health with low latencies and perform analytics in real-time.
5)In-hospital patient monitoring
Healthcare contains several edge opportunities. Currently, monitoring devices (e.g. glucose monitors, health tools and other sensors) are either not connected, or where they are, large amounts of unprocessed data from devices would need to be stored on a 3rd party cloud. This presents security concerns for healthcare providers.
16/01/2022
Hello All,
I am providing freelance services as technical trainer for Web app development with LAMP, WAMP, JAM, MEAN or MERN stack; Android Mobile App Development using Java, Hybrid Mobile App Development using React Native; AI based Chatbot development using AWS Lex,Lamda,S3 and DynamoDB; Data Science, Artificial Intelligence(AI) & Machine Learning; Big Data: Hadoop and Spark, Dashboard Designing with Tableau or Microsoft PowerBI; logic development for Programming languages; Digital Marketing: SEO, SMM and SEM as well as Soft Skills trainer for Personality development, Mockup Interviews ,Communication skills ,Group Discussions, Work Ethics and Emotional Intelligent.
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Yogesh Raje,
9923723839 / 7887374776
https://www.linkedin.com/in/yogesh-raje/
Hadapsar, Pune.