Sarthak (sarthakkmishraa)

sarthakkmishraa

Geek Repo

Company:Tata Consultancy Services

Location:New Delhi

Home Page:linkedin.com/in/sarthak-mishra-31909a172/

Twitter:@sarthakkmishraa

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Sarthak 's repositories

Flight-Price-Prediction-With-Deployment

I have built a simple web app that predicts the price of flights based on inputs such as Departure date and time, Source and destination, etc. The model is trained on "Random Forest Regressor" and deployed using "Streamlit" on Heroku. The accuracy of the model was found out to be 95% on the train data and about 80% on the test data.

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Stock_Market_Prediction

The aim of this project is to analyse the stock market data and predict the stock closing price using Long Short Term Memory(LSTM ) deep learning algorithm and evaluate the accuracy of the model. Also, the trained data is used to predict the stock closing prices for the next 30 days in future.

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Face-Detection-Using-Open-CV

This is a simple demonstration of face detection using the OpenCV library in python (in a few lines of code). Face detection using Haar cascades is a machine learning based approach where a cascade function is trained with a set of input data. OpenCV already contains many pre-trained classifiers for face, eyes, smiles, etc.. We will be using the face classifier.

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Image-Classification-Using-CNN-in-Pytorch

The aim of this project is to predict the label of the object given the image data using Convolutional Neural Networks(CNN) in Pytorch. The dataset used is CIFAR-10 dataset which is a subset of the 80 million tiny images dataset and consists of 60,000 32x32 color images containing one of 10 object classes, with 6000 images per class.

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ReducingMarketWaste_HackerearthCompetition

Problem Statement: The company has products that can be used for hiring assessments. The task is to predict the probability percentage that a client will purchase a product from the features provided in the dataset.

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The-Sparks-Foundation-Tasks

This repository contains the tasks that I completed while working as an intern for The Sparks Foundation. Internship Category - Data Science and Business Analytics Internship Duration - 1 Month ( October-2020 ) Internship Type - Work from Home In this internship, we were provided a list of tasks and I was able to successfully complete 4 tasks within the given time-frame.

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500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

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awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

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DateToDaysMaker

Converts Date to ithDay of year

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DSA-Bootcamp-Java

This repository consists of the code samples, assignments, and the curriculum for the Community Classroom complete Data Structures & Algorithms Java bootcamp.

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fastbook

The fastai book, published as Jupyter Notebooks

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first-contributions

🚀✨ Help beginners to contribute to open source projects

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GitHubGraduation-2021

Join the GitHub Graduation Yearbook and "walk the stage" on June 5.

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googlekeepclone

A clone of Google Keep with its original Material Design aesthetics

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MathInspector

A visual programing environment for scientific computing with python

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MONAI

AI Toolkit for Healthcare Imaging

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NOvid-20

An amazing PWA which is a solution to foretell the likelihood of being in vicinity of COVID-19

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Polynomial-Regression

Data analysis and visualization on Polynomial Regression using EA Sports FIFA 19 player roster database.

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py

Repository to store sample python programs for python learning

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pytorch-Deep-Learning

Deep Learning (with PyTorch)

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Sentiment-Analysis-Using-Twitter-API

The objective of this program is to analyse Donald Trump's tweets and classify the sentiment as either positive, negative or neutral. I have used the Twitter API to fetch the tweets and TextBlob library for performing the NLP task. It includes tokenisation, removing special character and irrelevant nouns and pronouns(stopwords) and passing the tokens to the sentiment classifer which assigns the tweets polarity of positive, negative and neutral by the values 1, -1 and 0 respectively.

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tez

Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch.

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