dipespandey

dipespandey's Stars

• radionovanorge/radionova-project

  Language:JavaScript3

• khoj-ai/khoj

  Your AI second brain, open and self-hostable. Get answers to your questions, whether they be online or in your own notes. Use online AI models (e.g gpt4) or private, local LLMs (e.g llama3).

  Language:Python12.7k649

• NextJSTemplates/startup-nextjs

  Startup is free Next.js template for SaaS startups comes with all the essential pages, components, and sections you need to launch a complete business website.

  Language:TypeScript1.2k360

• frefrik/norway-finance-statistics

  🏦 A collection of Norwegian financial data

  Language:Python3

• nikita-stha/pneumonia-detector

  Template for Flask project deployment

  Language:HTML10

• danielgatis/rembg

  Rembg is a tool to remove images background

  Language:Python16.5k1.8k

• pdaian/flashboys2

  Flash Boys 2; frontrun.me web code, data gathering, and public data.

  Language:Go42488

• mitesh77/Best-Flutter-UI-Templates

  completely free for everyone. Its build-in Flutter Dart.

  Language:Dart20.3k4.5k

• blockchain-etl/ethereum-etl

  Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Google BigQuery https://goo.gl/oY5BCQ

  Language:Python2.9k841

• bjohanne/ig-coder

  IG Coder is a web application that facilitates the interactive encoding of regulations in the Institutional Grammar syntax.

  Language:TypeScript72

• vintasoftware/django-production-launch-checklist

  A checklist we use here at Vinta before launching a product we've been working on.

  3815

• SystangoTechnologies/DjangoUnboxed

  Production ready django based starter kit

  Language:Python8336

• dotkom/onlineweb4

  Web pages for Online, Linjeforeningen for Informatikk at NTNU

  Language:Python4823

• condemane/cookiecutter-airflow-ha

  This cookiecutter generates a high availability airflow(webserver, scheduler, workers) application. The generated application uses celery, redis, postgres sql and runs on a highly scalable docker/kubernetes environment. It also uses slack for realtime notifications.

  Language:Python31

• GjjvdBurg/labella.py

  Python 3 clone of labella.js that generates SVG and TikZ PDF output

  Language:Python666

• iamsusmitha/E-Dressing

  Virtual Trial Room

  Language:JavaScript3127

• mortezamg63/Accessing-and-modifying-different-layers-of-a-pretrained-model-in-pytorch

  35065

• andrewjong/SwapNet

  Virtual Clothing Try-on with Deep Learning. PyTorch reproduction of SwapNet by Raj et al. 2018. Now with Docker support!

  Language:Jupyter Notebook377117

• luuuyi/CBAM.PyTorch

  Non-official implement of Paper：CBAM: Convolutional Block Attention Module

  Language:Python1.3k286

• wasimusu/python_project

  A simple setup for a python project

  Language:Python64

• mitmath/computational-thinking

  Course 18.S191 at MIT, Fall 2022 - Introduction to computational thinking with Julia

  Language:Julia2.6k479

• SonarSystems/Modern-OpenGL-Tutorials

  Language:C260147

• Atcold/NYU-DLSP20

  NYU Deep Learning Spring 2020

  Language:Jupyter Notebook6.7k2.2k

• josephlimtech/linkedin-profile-scraper-api

  🕵️‍♂️ LinkedIn profile scraper returning structured profile data in JSON.

  Language:TypeScript548147

• dilipthakur87/todo-list

  Small todo-list app using React Hooks

  Language:JavaScript1

• ManishChandra12/iJoRMS

  Language:JavaScript1

• taeho-kil/Document-Image-Dewarping

  Document Image Dewarping

  32749

• nicholaskajoh/ivy

  Video-based object counting software.

  Language:Python425170

• binoydutt/Resume-Job-Description-Matching

  The purpose of this project was to defeat the current Application Tracking System used by most of the organization to filter out resumes. In order to achieve this goal I had to come up with a universal score which can help the applicant understand the current status of the match. The following steps were undertaken for this project 1) Job Descriptions were collected from Glass Door Web Site using Selenium as other scrappers failed 2) PDF resume parsing using PDF Miner 3) Creating a vector representation of each Job Description - Used word2Vec to create the vector in 300-dimensional vector space with each document represented as a list of word vectors 4) Given each word its required weights to counter few Job Description specific words to be dealt with - Used TFIDF score to get the word weights. 5) Important skill related words were given higher weights and overall mean of each Job description was obtained using the product for word vector and its TFIDF scores 6) Cosine Similarity was used get the similarities of the Job Description and the Resume 7) Various Natural Language Processing Techniques were identified to suggest on the improvements in the resume that could help increase the match score

  Language:Python16384

• iamtrask/Grokking-Deep-Learning

  this repository accompanies the book "Grokking Deep Learning"

  Language:Jupyter Notebook7.4k1.6k