Discover @ashharr Open Source projects

Ashhar Shaikh (@ashharr)

ashharr

Stars
46
Global Rank 361,753 (Top 13 %)
Followers 17
Following 49
Registered almost 6 years ago
Most used languages

JavaScript
29.4 %

Java
17.6 %

Python
17.6 %

Jupyter Notebook
17.6 %

CSS
11.8 %

MATLAB
5.9 %
Location 🇮🇳 India
Country Total Rank 18,215
Country Ranking

MATLAB
1,572

Python
3,790

Jupyter Notebook
3,872

CSS
8,180

chatbot-ml-SIH-2019

A Customer Support Chatbot using Machine Learning for Smart India Hackathon 2019 ( Winning Idea)

quantum-neural-networks

Feed forward QNN

Jupyter Notebook

twitter-sentimental-analysis

Predicting the sentiments of the tweets such as Positive, Negative and Neutral. Classified using the SVM model after pre-processing and cleaning the data.

Jupyter Notebook

sleeves7-website

An e-commerce T shirt selling website I am building for my friends business. (Work In Progress 🔨)

t-shirt-e-commerce-full-stack-app

A full stack e-commerce website developed with Next.js and React.js with payment gateway.

minimalist-todo-app

A Minimalist Todo App built using Spring Framework.

crypto-tracker-india

A cryptocurrency tracker which shows INR price for all coins fetched from the CoinGecko API

spring-java-bootcamp

Java Spring Framework Projects Code and Concepts

javascript-bootcamp

My Code snippets of JavaScript bootcamp by Hitesh Choudhary.

dsa-bootcamp

Data Structures and Algorithms. LeetCode Problems Practice.

react-js

React JS exercises, practice code and challenges

ashharr.github.io

Innov8_problem_statement

machine-learning-stanford-assignments

quality-stocks-screener

A script that generates High quality stocks using a query on screener.in website gets the table and coverts and saves it as a CSV file.

detecting-fake-news-classifier

To build a model to accurately classify a piece of news as REAL or FAKE. The detection of fake news is done from saving oneselves from believing in false information. All the news that are read on social media cannot be trusted or relied upon. Hence the aim of our project is to detect such fake news by using tf-idf vectorization on news data sets, calculating the confusion matrix of our model and generating its accuracy for prediction of fake news. Using sklearn, we build a Tf-Idf Vectorizer on our dataset. Then, we initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.

Jupyter Notebook

ticktrack

Ticktrack is a minimal todo application using Spring Boot and React Stack.