Mangalis0
BSc Computational and Applied Mathematics (University Of The Witwatersrand (Wits)) Postgraduate Certificate In Education (Wits) Data Scientist
Johannesburg, South Africa
Pinned Repositories
classification-predict-streamlit-template
Template repository for the EDSA Classification Predict
Corona-Virus-Visualization
This project makes graphical exploratory data analysis of the Corona Virus from a South African database created and updated by Explore Data Science Academy in partnership with the South African Government
Decision-Tree-Regression-on-the-World-Population
Using Decision Tree Regression to predict world population
ETL-Pipeline
Extracting data from twitter, Transforming it in Python, Loading it in SQL. Please refer to Readme.md for more details
Image-Classification
In this challenge, we train the model with images of hand drawn numbers with their respective labels. Then use the classifier to predict the label given the image in pixels. Refer to README.md for more details
Linear-Regression-on-the-World-Population
In this project, we use Ridge Regression Model to predict the population of a certain country at a particular year having trained the data with the world population from 1960 to 2017
Logistic-Regression
This is an introductory use of Logistic Regression into solving classification problems. Refer to to README.md for more details
NLP_Project_First_Class
Natural Language Processing Classifcation Project analyzing Tweets for sentiment analysis
Titanic-Survival-Conditional-Probability
Simple statistical prediction of the survival chances of the passengers in the testing set, given certain conditions as input. Refer to README.md for more detail
Zindi-Regression-Hackathon
Sendy Logistics Zindi Competition
Mangalis0's Repositories
Mangalis0/Titanic-Survival-Conditional-Probability
Simple statistical prediction of the survival chances of the passengers in the testing set, given certain conditions as input. Refer to README.md for more detail
Mangalis0/ETL-Pipeline
Extracting data from twitter, Transforming it in Python, Loading it in SQL. Please refer to Readme.md for more details
Mangalis0/Linear-Regression-on-the-World-Population
In this project, we use Ridge Regression Model to predict the population of a certain country at a particular year having trained the data with the world population from 1960 to 2017
Mangalis0/NLP_Project_First_Class
Natural Language Processing Classifcation Project analyzing Tweets for sentiment analysis
Mangalis0/Image-Classification
In this challenge, we train the model with images of hand drawn numbers with their respective labels. Then use the classifier to predict the label given the image in pixels. Refer to README.md for more details
Mangalis0/Logistic-Regression
This is an introductory use of Logistic Regression into solving classification problems. Refer to to README.md for more details
Mangalis0/Zindi-Regression-Hackathon
Sendy Logistics Zindi Competition
Mangalis0/classification-predict-streamlit-template
Template repository for the EDSA Classification Predict
Mangalis0/Corona-Virus-Visualization
This project makes graphical exploratory data analysis of the Corona Virus from a South African database created and updated by Explore Data Science Academy in partnership with the South African Government
Mangalis0/Decision-Tree-Regression-on-the-World-Population
Using Decision Tree Regression to predict world population
Mangalis0/Parameter-Tuning
This project is using the Wine Quality Data Set to create a model that will predict the wine quality based on physicochemical tests, after tuning the hyperparameters. Refer to Readme.md for more details
Mangalis0/Random-Forest-Regression-on-the-World-Population
Using Random Forest Regression to predict world population. Refer to README.me for more details
Mangalis0/regression-predict-api-template
Template repository used for creating a simple regression-based API
Mangalis0/singularityteam10
The focus of this project is the building of functions for Eskom to preprocess Data from Eskom, and prepare it for Sentiment Analysis. Refer to README.md for more details
Mangalis0/Titanic-Data-Preprocessing
Exploratory Data Analysis on the raw data from the Titanic Kaggle Challenge. The purpose of this challenge is to predict the probability of survival for a given passenger, given their boarding details.