shyamcody/jobathon-2020

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Python
Created over 3 years ago
Updated over 3 years ago

shyamcody/jobathon-2020

shyamcody

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nlp-experiments

I will try small experiments on older state of the art models like bart, t5 and others and also plan to work on gpt-3 once I get beta access. This repo will consist of all such experiments.

Jupyter Notebook

leetcode

contains all leetcode solutions

streamlit_experiments

will contain different streamlit app scripts.

spacy_streamlit_app

This is the spacy app repository created to deploy the app on streamlit.

youtube-bot

This bot is created to exploit selenium's power and login, search, and get a substantial number of http links and go through them to comment in each of the videos.

Jupyter Notebook

Data-structures-using-python

This repository will contain data structure implementations using python and will have codes stored from multiple online resources.

b4grad_ad

playable ad for b4grad

hackerEarth-easycodes

Here I am gonna dump my solved questions from hackerearth.

shyamcody

gst-calculator-app

A simple gst calculator tool for invoices.

upvotoBot

A basic bot which scraps multiple rss feeds and comments them into upvotocracy.com threads.

pong-game

This is a python code written to implement a minimal game of pong, although there is no score board. Explore the code to understand more.

Jupyter Notebook

TkinterMusicPlayer

this is a music player code, using the library Tkinter, which plays, stops musics loaded in the program.

datalemur-sql-solutions

solutions to my submissions to datalemur

portfolio-optimization-app

this is an application showcasing the power of pypfopt library to create portfolio with minimum risk and maximum gains. [not in advisement capacity]

Machine-Learning-Papers

This contains stats and machine learning related papers.

renchant

api to front end integration code

calculator

A very small html repo about bunch of on-page calculators

Housing-data-random-forest

this repo contains a example solution of the housing data using random forest. We have not done any feature engineering, but just created the raw variables and tuned the random forest to train and predict.

Jupyter Notebook

auto-model-trainer

this is automatic training app. just upload your numeric dataset and check results for different models.