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Hi👋, I'm Yasharth

Kartavyam Anvatma

💫About Me :

🔭 I’m currently pursuing my Bachelor's in Computer Science and Engineering.

🌱 I’m currently learning Web-development and ML.

👯 I’m looking to collaborate on EDA,Web-Devlopment projects.

💬 Ask me about Data-Analytics,Bodybuilding,CSGO,Naruto,FMA-Brotherhood.

📫 How to reach me [email protected]

⚡ My motto Shramena Sarvam Sadhyam

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💻Tech Stack

C C++ CSS3 HTML5 JavaScript Octave Python Anaconda Bootstrap Express.js NPM NodeJS React MySQL Neo4J MongoDB NumPy Pandas Plotly scikit-learn SciPy Arduino Notion Postman ESLint jQuery Heroku

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Yasharth's Projects

budget-app icon budget-app

A Finances application made to manage all your day to day expenses

competitive_coding icon competitive_coding

This repository contains some useful codes, techniques, algorithms and problem solutions helpful in Competitive Coding.

cpp icon cpp

Implementation of All ▲lgorithms in C++ Programming Language

currency_converter icon currency_converter

It is a python program that uses the forex-python library to convert currency. A tkinter GUI is also made for better experience

drum-kit icon drum-kit

Mini Project which includes some work with audio and Vanilla JS.

hacktoberfest-2021 icon hacktoberfest-2021

A platform for developers 👩‍💻 who wants to participate in Hacktoberfest 2021 👕

hacktoberfest-21 icon hacktoberfest-21

A mentorship initiative to help beginners kickstarting their open-source journey by completing Hacktoberfest'21 challenge | Curated list of beginner-friendly issues for Hacktoberfest 2021 | Raise PR to add your issues

mini_python_projects icon mini_python_projects

This repository will help beginners kickstarting their open-source journey by completing Hacktoberfest'21 challenge || Just need to make a mini python project that can be done within an hour also || Can also add programming questions and their solutions only in Python || Make sure you add everything in the right directory || HAPPY HACKING!!!

plant-disease-detection-web-application icon plant-disease-detection-web-application

Deep learning with convolutional neural networks (CNNs) has achieved great success in the classification of various plant diseases. However, a limited number of studies have elucidated the process of inference, leaving it as an untouchable black box. Revealing the CNN to extract the learned feature as an interpretable form not only ensures its reliability but also enables the validation of the model authenticity and the training dataset by human intervention. In this study, a variety of neuron-wise and layer-wise visualization methods were applied using a CNN, trained with a publicly available plant disease image dataset. We showed that neural networks can capture the colors and textures of lesions specific to respective diseases upon diagnosis, which resembles human decision-making. While several visualization methods were used as they are, others had to be optimized to target a specific layer that fully captures the features to generate consequential outputs. Moreover, by interpreting the generated attention maps, we identified several layers that were not contributing to inference and removed such layers inside the network, decreasing the number of parameters by 75% without affecting the classification accuracy. The results provide an impetus for the CNN black box users in the field of plant science to better understand the diagnosis process and lead to further efficient use of deep learning for plant disease diagnosis.

python_scripts icon python_scripts

It contains all the Python Programs, whether it's a GUI, basic, Data Structures, etc. It's a collection of some great Python scripts from basic to advance levels for automating some monotonous tasks.

stalin-sort icon stalin-sort

Add a stalin sort algorithm in any language you like ❣️ if you like give us a ⭐️

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