likarajo/covid19

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Python
Created over 4 years ago
Updated over 4 years ago

likarajo/covid19

likarajo

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Analysing COVID19 (Novel Coronavirus) data

language_translation

Deep Learning LSTM language translation model built with Keras using Neural Machine Translation with seq2seq encoder-decoder architecture

Jupyter Notebook

covid19Sentiments

Using Twitter data to perform sentiment analysis on the tweets on the COVID-19 virus

premier_league

Predictions for the English Premier League season

Jupyter Notebook

passengers_count

Time Series Prediction to predict the count of traveling passengers based on historical data using Long Short Term Memory (LSTM) Neural Network

Jupyter Notebook

devops-helloworld

Continuous Integration and continuous deployment using Jenkins

searchengine

Search engine using ElasticSearch and Python

cv

Resume https://likarajo.github.io/cv/resume, Portfolio: https://likarajo.github.io/cv/portfolio, Curriculum Vitae

website_v3

Built with Gatsby | Hosted with Netlify

simOS

Implementation of a Simulated Operating System

business_reviews

Multi-Input Classification Model to classify user reviews regarding different businesses, including restaurants, bars, dentists, doctors, beauty salons, etc.

Jupyter Notebook

titanic_survival

Create Titanic survival prediction model using Decision Tree. Ref: https://www.kaggle.com/c/titanic/data

glass_type

Identification of the type of glass based on their oxide content i.e. Na, Fe, K, etc using Dimensionality Reduction with Principal Component Analysis and Linear Discriminant Analysis

Jupyter Notebook

topics

Topic modelling

Jupyter Notebook

currencynote_authenticity

Classification to predict whether a bank currency note is authentic or not based on variance of the image wavelet transformed image, skewness, entropy, and curtosis of the image using Machine Learning classifiers.

Jupyter Notebook