About
A AIML Engineer dedicated to providing advanced solutions using different technologies.
I am proficient in developing scalable web APIs and designing custom user interfaces with the latest technologies, have a strong working knowledge of the full stack life cycle, from concept to implementation.
I am highly capable of responding to pressure situations and I always aim to bring innovative solutions to the table.
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Nick Name: Madhura
Email: madhuragurav95@gmail.com
Phone: +91) 9137291882
Address: Mumbai, Maharastra(INDIA)
- 3
Projects completed
- 2
Running Projects
My Skills
Experience Skill
My Projects
Arm Robot
Arms are devices that have been designed to do a given activity or job swiftly, correctly, and effectively. They're usually motor-driven consisting of a collection of joints, articulations, and manipulators, and are employed to accomplish heavy and/or repetitive processes quickly and consistently. They are particularly valuable in the industries of industrial production, manufacturing, machining, and assembly.
Touch Sensor with Arduino
A touch sensor with Arduino is a type of input device that detects touch or proximity without physical contact. It typically works by measuring changes in capacitance when touched. This information is then processed by the Arduino microcontroller, allowing you to trigger actions based on touch events. Main applications include interactive displays, touch-sensitive interfaces, and proximity detection systems. Touch sensors are widely used in electronic devices, such as smartphones, tablets, and touch-sensitive appliances.
DOBOT Magician
So similarly we can working on a Dobot.The Dobot Magician is a multifunctional robotic arm designed for educational, research, and industrial applications. It features a compact design with high precision and versatility, making it suitable for various tasks in fields such as STEM education, automation, and prototyping.
AI based model for prediction of heavy /high impact rain events
An AI-based model for predicting heavy/high impact rain events is crucial for early warning systems, disaster preparedness, and risk mitigation strategies. By analyzing historical weather data, atmospheric conditions, and geographical factors, the model can accurately forecast the likelihood and intensity of extreme rainfall events. It utilizes machine learning algorithms, such as neural networks or decision trees, to identify patterns and correlations in the data, enabling precise predictions. To develop such a model, one needs quality datasets containing weather parameters, advanced machine learning techniques, and domain expertise to interpret results effectively. Continuous refinement and validation of the model with real-world data are essential for improving its accuracy and reliability over time.
