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A system that is capable of automatically irrigating the agricultural field by sensing the parameters of soil in real-time and predicting crop based on those parameters using machine learning. The system also predicts the yield of the crop.
ASERSA is an agent-based system built on the Dynamic Force Index Algorithm (DFIA), simulating interactions in real-time using socio-economic attributes like wealth, influence, ambition, and competence. The system features a 3D interactive GUI for visualizing agent interactions and allows real-time adjustments of key parameters.
The objective of this project is the development and evaluation of recommendation algorithms based on the MovieLens dataset, one of the benchmark datasets for research into recommendation systems. User ratings, tags, and movie metadata are used in the dataset, allowing for simple and advanced recommendation techniques
In this project we are trying to solve a classification problem where we need to check that a particular wafer sensor is active or not after which we would do CICD using CircleCi
Developing an e-commerce recommendation system involves utilizing technologies such as Python for programming, Pandas for data manipulation, SQL for database management, FastAPI for building APIs, PostgreSQL for data storage, and Docker for containerization.