Ashish Yadav (ashudva)

ashudva

Geek Repo

Location:Lucknow, India

Home Page:ashishdev.tech

Twitter:@ashudva_ked

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Ashish Yadav's repositories

ML-6.86x

Machine Learning Projects Repository

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HAR

Comparative study of CNN and recently developed hABCPSO algorithm for the classification of Physican Human Activities, using Smartphones Data Set provided for Human Activity Recognition (HAR) by University of California Irvine (UCI)

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face_detector

OpenCV and Deep Learning based fast and accurate face detector

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KED

Keen Eye & Data

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SNV-Business

Front-End for SNV Business firm

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admin-dashboards

Admin Dashboards - Full-Stack Admin Panels | AppSeed

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authorship

Experimental study of performance of state of the art Deep Learning Architectures for Authorship Identification

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DR_web

Streamlit web app for multi digit recognition

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Case_Studies

This repository consists of case studies using Python, and R - 1. DNA Translation using NCBI Data 2. Language Analysis using data from Project Gutenberg 3. Classification using KNN

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cookiecutter-flask

A flask template with Bootstrap 4, asset bundling+minification with webpack, starter templates, and registration/authentication. For use with cookiecutter.

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coursera-gan-specialization

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

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CS50-PSets

Solutions for CS50 (2018,2019) Problem sets

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deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

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DNS-Challenge

This repo contains the scripts, models and required files for the Interspeech 2020 Deep Noise Suppression (DNS) Challenge. We are open sourcing clean speech and noise files as well. Participants of this challenge will use the scripts from this repo to create data to train their noise suppressors. They will compare their method with our baseline noise suppressor and report the results.

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DR-detection

Diabetic retinopathy is the leading cause of blindness in the working-age population of the developed world. It is estimated to affect over 93 million people. It is a very complex task to detect diagnose DR during its early stages. In this project, given a scanned eye image, I will try to predict if the person has DR and at what stage.

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Enigma-codeFest-Machine-Learning

Ranked 8th in Analytics Vidhya Enigma-codeFest-Machine-Learning Competition

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flask-apps

Flask - Free and commercial open-source apps | AppSeed

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homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

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LoRA

Code for "LoRA: Low-Rank Adaptation of Large Language Models"

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movie_recommender

The goal of this project is to assess the performance of Various Techniques of Collaborative Filtering through a Movie Recommender System.

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PythonAlgorithms

All Algorithms implemented in Python

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torch

R Interface to Torch

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