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adopt-me

An application on adopting pets based on the intro to intermediate React by Brian Holt .

ads-assignment

Africa Data School Jan -March 2022 Cohort Assignments.

africa-data-school

africa-economic-well-being-prediction-zindi-competition

ai4d-news-classification-challenge

The objective for this challenge was to develop a multi-class classification model to classify news content according to six specific categories.

awesome-credit-modeling

A collection of awesome papers, articles and various resources on credit and credit risk modeling

awesome-time-series

list of papers, code, and other resources

awesome_time_series_in_python

This curated list contains python packages for time series analysis

bankpolicysubscriptionads

ADS Project based on bank policy subscription .

basic-needs-basic-rights-kenya

The objective of this challenge is to develop a machine learning model that classifies statements and questions expressed by university students in Kenya when speaking about the mental health challenges they struggle with. The four categories are depression, suicide, alchoholism, and drug abuse.

bayesian-machine-learning

Notebooks about Bayesian methods for machine learning

big-mart-sales-prediction

The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and predict the sales of each product at a particular outlet. Using this model, BigMart will try to understand the properties of products and outlets which play a key role in increasing sales.

black-friday-sales-prediction

A retail company “ABC Private Limited” wants to understand the customer purchase behaviour (specifically, purchase amount) against various products of different categories. They have shared purchase summary of various customers for selected high volume products from last month. The data set also contains customer demographics (age, gender, marital status, city_type, stay_in_current_city), product details (product_id and product category) and Total purchase_amount from last month. Now, they want to build a model to predict the purchase amount of customer against various products which will help them to create personalized offer for customers against different products.

bookrepo

building-llm-powered-applications

Building Large Language Model Applications, Published by Packt

business-machine-learning

A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations (by @firmai)

cancer-detection-using-knn

This repository contains a machine learning project that aims to detect cancer using the k-Nearest Neighbors (k-NN) algorithm.

coding-interview-university

A complete computer science study plan to become a software engineer.

coffee-prediction-in-kenya

coffee prediction streamlit app

customer-churn

Machine Learning Model to determine which user is likely to churn from a subscription after a period of time

data-science

data-science-1

EDA and Machine Learning Models in R and Python (Regression, Classification, Clustering, SVM, Decision Tree, Random Forest, Time-Series Analysis, Recommender System, XGBoost)

data-science-projects

Repository containing data science projects.

data-science-projects-with-python

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

dataanalysiswithexcel

GitHub repo for Dave Langer's YouTube tutorials on data analysis with Excel

deep_and_machine_learning_projects

This Repository contains the list of various Machine and Deep Learning related projects. Related code and data files are available inside this folder. One can go through these projects to implement them in real life for specific use cases.

django-admin-watchdog-

A simple Django app to register logs in admin backoffice.

dla

Deep learning for audio processing

dsn-2019-insurance-prediction

build a predictive model to determine if a building will have an insurance claim during a certain period or not. You will have to predict the probability of having at least one claim over the insured period of the building. The model will be based on the building characteristics. The target variable, Claim, is a: 1 if the building has at least a claim over the insured period. 0 if the building doesn’t have a claim over the insured period.

expresso_churn_prediction

Expresso is an African telecommunications company that provides customers with airtime and mobile data bundles. The objective of this challenge is to develop a machine learning model to predict the likelihood of each Expresso customer “churning,” i.e. becoming inactive and not making any transactions for 90 days. This solution will help Expresso to better serve their customers by understanding which customers are at risk of leaving.