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Natural-Language-Processings-NLP-on-Swahili-News-Classification-
Develop a multi-class classification model to classify news content according to their specific categories i.e. Kimataifa News (International), Kitaifa news (National), Burudani News (Entertainment), Michezo News (Sports), and Biashara News (Biashara).Detection-of-Anxiety-and-Depression
Football-Game-Results-Prediction-
Am a football analyst tasked with predicting results of a game between team 1 and team 2, based on who's home and who's away, and on whether or not the game is friendlySpotify-Prediction-whether-a-newly-uploaded-song-on-Spotify-will-make-to-be-a-hit-song-ML
Music is considered an art but have you ever thought of what happens probably behind the scenes to make it an art. May be it's the beats, energy, liveliness, and the ability to dance brought about by a tune. If all these factors work out right then a song is conisidered the most lively probably making it among the top hits. Using a spotify dataset we would like to know among which factors affect whether a song will be a hit song or not. Moreover, we will build a model that predicts whether a song will be a hit song based on the nature of it's beats, energy, danceablity, liveness, and loudness.Prediction-model-of-individuals-that-are-most-likely-to-own-a-bank-account-in-Eastern-Africa
The research problem is to figure out how we can predict which individuals are most likely to have or use a bank account. The solution will help provide an indication of the state of financial inclusion in Kenya, Rwanda, Tanzania, and Uganda, while providing insights into some of the key demographic factors that might drive individuals’ financial outcomes.Using-Computer-Vision-to-Classify-Chest-X-Ray-Images-in-real-time-using-CNN
Our solution, entails using Convolutional Neural Network (CNN) to classify chest X-ray images in real time to return immediate results to a Digital Radiography reducing a patient’s wait time facilitating immediate treatment reducing TB deaths in Africatomeliud
Unsupervised-learning-usin-r-
test_project
Explatory-analysis-using-r-
tomeliud_covid-19-estimator-py
Neural-Network-Basic-Needs-Basic-Rights-Kenya---Tech4MentalHealth
This was a zindi challenges where we were tasked with indenfying mental health complications especially diversly due to the great pandemic Covid- 19. The expectation is to recieve raw data and categorize the disorders to either sucide, depression, Alcholosim, or Drug abuse.Naive-Bayes-and-KNN-modeling-
On this repo we will model data using Naive Bayes and KNN modeling.Machiene-models-using-r-
Plant_Diseases_Classification
Classifying plant diseasesRegression-Models-to-predict-House-Prices
Hass Consulting Company which is a real estate leader with over 25 years of experience. I have been tasked to study the factors that affect housing prices using the given information on real estate properties that was collected over the past few months. Later onwards, create a model that would allow the company to accurately predict the sale of prices upon being provided with the predictor variables.Times-Series-to-Predict-Teenage-Pregancies-in-Kenya--KNN-and-Random-Forest
To analyze factors that influence teenage pregnancies in Kenya identifying which regions recorded the highest number of cases and building a Machine Learning Model to study such factors modeling a Time series to predict future cases.Hypothesis-testing-on-the-usage-of-Blue-cars-versus-Utilib-cars-over-the-weekend
Autolib electric car-sharing service company seeks to investigate a claim about the blue cars from the provided Autolib dataset and would like to do a hypothesis testing on whether Blue cars are the most preffered unlike Utilib CarsHypothyroidism-Prediction-in-Patients-using-Random-Forest-Decision-Tree-Gradient-Boosting-SVC-
Nairobi Hospital conducted a clinical camp to test for hypothyroidism. The data collected focused on Thyroid patients. Am tasked with building a model that determines whether or not the patient's symptoms indicate that the patient has hypothyroid.Expresso-Telecomunnication-Prediction-model-on-whether-a-user-will-churn-from-using-the-Network-Zind
In this Zindi Challenge we were tasked with analysing factors that affect a user thus ceasing from been an Expresso Telecommunication Customer. We will analyse the factor(s) that most influnced a cusomer to leave the serivce provider. However, we will give suggestions of which factors are most essential to ensure that customers are satisfied reducing the possibility that a customer will churn from Expresso Telecommunications. Moreover, I will build a Machine Learning model that Predicts wheteher a customer is likely to churn or not based on the above analyzed factorsLove Open Source and this site? Check out how you can help us