CHERISHMA MEDHA VARMA VEGESNA

Motivated and detail-oriented SAP fresher with a solid understanding of SAP modules such as MM, SD, and FICO. Strong academic background in B.Tech in Computer Science, with hands-on experience in SAP through coursework, online training. Eager to apply theoretical knowledge to real-world business scenarios and contribute to organizational success. Quick learner with excellent analytical, problem-solving, and communication skills.

Traffic Sign Detection Using CNN and ML, In this project, the main goal is to implement a traffic sign detection system using a Convolutional Neural Network (CNN) and specifically leveraging the VGG-19 model. The process starts by downloading the road-sign-detection.zip file from the Kaggle website, which presumably contains a dataset of road sign images along with their corresponding labels., Overall, the combination of the VGG-19 model, the preprocessed dataset, and the CNN training process enables the creation of an accurate and reliable traffic sign detection system, which can be crucial for enhancing road safety and assisting autonomous vehicles or driver assistance systems

• Microsoft word
• Power point
• Excel

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