Siddhartha Shandilya's Projects
Dementia is a neurodegenerative disorder, using this web-app we can predict whether the person is suffering from dementia or not
# Denoising Dirty Documents Optical Character Recognition (OCR) is the process of getting type or handwritten documents into a digitized format. If you've read a classic novel on a digital reading device or had your doctor pull up old healthcare records via the hospital computer system, you've probably benefited from OCR. OCR makes previously static content editable, searchable, and much easier to share. But, a lot of documents eager for digitization are being held back. Coffee stains, faded sun spots, dog-eared pages, and lot of wrinkles are keeping some printed documents offline and in the past. This competition challenges you to give these documents a machine learning makeover. Given a dataset of images of scanned text that has seen better days, you're challenged to remove the noise. Improving the ease of document enhancement will help us get that rare mathematics book on our e-reader before the next beach vacation. We've kicked off the fun with a few handy scripts to get you started on the dataset. Acknowledgements Kaggle is hosting this competition for the machine learning community to use for fun and practice. This dataset was created by RM.J. Castro-Bleda, S. EspaΓ±a-Boquera, J. Pastor-Pellicer, F. Zamora-Martinez. We also thank the UCI machine learning repository for hosting the dataset. If you use the problem in publication, please cite: Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science ## AIM: * To Denoise the images using Encoder-Decoder Model ## Dataset: * https://www.kaggle.com/c/denoising-dirty-documents/data * We are provided two sets of images, train and test. These images contain various styles of text, to which synthetic noise has been added to simulate real-world, messy artifacts. The training set includes the test without the noise (train_cleaned). You must create an algorithm to clean the images in the test set.
container=httpd-server
π In this task you have to create a Web Application for Docker (one of the great Containerization Tool which provides the user Platform as a Service (PaaS)) by showing your own creativity and UI/UX designing skills to make the webportal user friendly. π This app will help the user to run all the docker commands like: πdocker images πdocker ps πdocker run πdocker rm -f πdocker exec π add more if you want. (Optional) π Make a blog/article/video explaining this task step by step. βοΈ Task 7.2 - π Write a blog explaining the use-case of javaScript in any of your favorite industries.
Exercises and supplementary material for the machine learning operations course at DTU.
this repo contains the integration of nlp and dvc
It uses DVC for CI/CD and classifies cats and dogs based on images
π When it recognize your face then - π It send mail to your mail id by writing this is face of your_name. π Second it send whatsapp message to your friend, it can be anything. π When it recognize second face, it can be your friend or family members face. π Create EC2 instance in the AWS using CLI. π Create 5GB EBS volume and attach it to the instance.
πβ¨ Help beginners to contribute to open source projects
Now you can get Flight ticket fare with this wonderful end to end project.
The project is about creating a model which predicts the flight fare price based on factors like distance, number of stops, total hours of flight as well as the type of seat
Join the GitHub Graduation Yearbook and "walk the stage" on June 11.
In this project , I have trained multiple model which predicts the probability of an user having the mentioned disease based on symptoms
Contains task of i_neuron tasks
The project will have a complete end-to-end pipeline for insurance fraud prediction model
All the Machine Learning program are here
The Covid Detection application
this is one of the projects from ineuron_AIOPS_course as an industry level
A project-based course on the foundations of MLOps with a focus on intuition and application.
Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng
This repo contains all the project and tasks done during the internship