Oluwaleke

Project 1 Malnutrition in African children: Project Overview

An analysis of the state of nutrition in African children. The intention is to compare economic strength and its relationship with the state of malnutrition in various countries in Africa Data were gotten from different data sources which includes but not limited to : https://databank.worldbank.org/ , https://data.unicef.org/

Project 2 Google-Playstore-Dataset: Project Overview

Google PlayStore App analytics. (2.3 Million App Data) and 24 attributes. An EDA of the PlayStore Dataset inspired by @gauthamp10 Data was Downloaded from Kaggle: https://www.kaggle.com/gauthamp10/google-playstore-apps/

Project 3 Unsupervised-Predict-Streamlit

This repository forms the basis of Task 2 for the Unsupervised Predict within EDSA’s Data Science course. It hosts template code which will enable students to deploy a basic recommender engine based upon the Streamlit web application framework.

As part of the predict, students are expected to expand on this base template; improving (and fixing) the given base recommender algorithms, as well as providing greater context to the problem and attempted solutions through additional application pages/functionality.

Project 4 NLP-South-African-Language-Identification

South Africa is a multicultural society that is characterised by its rich linguistic diversity. Language is an indispensable tool that can be used to deepen democracy and also contribute to the social, cultural, intellectual, economic and political life of the South African society. The country is multilingual with 11 official languages, each of which is guaranteed equal status. Most South Africans are multilingual and able to speak at least two or more of the official languages. From South African Government. With such a multilingual population, it is only obvious that our systems and devices also communicate in multi-languages. We will take text which is in any of South Africa’s (lang_id) 11 Official languages and identify which language the text is in. This is an example of NLP’s Language Identification, the task of determining the natural language that a piece of text is written in.

Project 5 Regression- Spain Electricity Shortfall Challenge

In this project you are tasked to model the shortfall between the energy generated by means of fossil fuels and various renewable sources - for the country of Spain. The daily shortfall, which will be referred to as the target variable, will be modelled as a function of various city-specific weather features such as pressure, wind speed, humidity, etc. As with all data science projects, the provided features are rarely adequate predictors of the target variable. As such, you are required to perform feature engineering to ensure that you will be able to accurately model Spain’s three hourly shortfalls.

Project 6 classification-predict-streamlit

The collection of this data was funded by a Canada Foundation for Innovation JELF Grant to Chris Bauch, University of Waterloo. This dataset aggregates tweets pertaining to climate change collected between Apr 27, 2015 and Feb 21, 2018. In total, 43943 tweets were collected. The data was downloaded from: https://www.kaggle.com/c/edsa-climate-change-belief-analysis-2022/data

Each tweet is labelled as one of the following classes:

Class Description

2 News: the tweet links to factual news about climate change 1 Pro: the tweet supports the belief of man-made climate change 0 Neutral: the tweet neither supports nor refutes the belief of man-made climate change -1 Anti: the tweet does not believe in man-made climate change Variable definitions

sentiment: Sentiment of tweet message: Tweet body tweetid: Twitter unique id

My other projects: github.com/Oluwaleke

Website: google.com/view/oluwalekeoni/home

Hi there 👋