Prashant Verma (@Vprashant)

Top repositories

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Analytics

Jupyter Notebook
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Python_Machine_Learning

Machine Learning tutorial provides basic and advanced concepts of machine learning. Machine learning is a growing technology which enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook auto-tagging, recommender system, and many more.
Jupyter Notebook
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Tools-Image-Classification

Python
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LangGPTEval

LangRAGEval is an evaluation library designed to support Langchain, focusing on assessing response quality based on faithfulness, context recall, answer relevancy, and context relevancy criteria.
Python
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fancybbox

Fancy Bounding Box - Rectangle for Object Detection
Python
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Eulerchain

A Generative AI Framework
Python
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Gstreamer_FaceDetection

Python
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Artificial-Inteligence

Deep learning networks for object detection to the task of optical character recognition in order to build image features taylored for documents. In contrast to scene text reading in natural images using networks pretrained on ImageNet, our document reading is performed with small networks inspired by MNIST digit recognition challenge, at a small computational budget and a small stride. The object detection modern frameworks allow a direct end-to-end training, with no other algorithm than the deep learning and the non-max-suppression algorithm to filter the duplicate predictions. The trained weights can be used for higher level models, such as, for example, document classification, or document segmentation.
Jupyter Notebook
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