rich-sam Goto Github PK

-sentiment-analysis-model

academic_website

analysis-covid19-data-kenya

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people who fall sick with COVID-19 will experience mild to moderate symptoms and recover without special treatment. Kenyan government is taking this diseases seriously and its releasing daily update on the status of the disease. We analyse the data to visualize the status and predict the direction of the confirmed cases

analysis-geospatial-data-with-r

analysis-of-new-york-school-bus-break-down-

The Bus Breakdown and Delay program gathers real-time information from school bus vendors that work in the region. Bus workers facing delays along the trip are advised to contact the dispatcher to the central office of the bus supplier. To record the event and inform OPT, the bus vendor staff are then instructed to log into the Bus Breakdown and Delay program. This program is used by OPT customer service representatives to notify parents who are calling with bus service queries. The Bus Breakdown and Delay program is available to the public and provides alerts in real time. All information is entered by vendor employees of school buses in the network.

classification-of-iris-data-set

we use the Classification and Regression Trees (CART) decision tree algorithm to model the Iris flower datasets

climate_analysis-with-r

scripts for analysing the status of weather and climate

covid19_kenya_data_analytics_finalexam

Suppose you have been hired by your county government to as data scientist. Design a data pipeline model that uses data lake approach for collecting COVID-19 data from various hospitals that are treating COVID-19 patients. The design should include the following features: i) Data ingestion ii) ETL for data lake as a staging (landing) Area iii) Analytics database

credit-card-fraud-detection-

Credit card fraud is a wide-ranging term for theft and fraud committed using or involving a payment card, such as a credit card or debit card, as a fraudulent source of funds in a transaction. The purpose may be to obtain goods without paying, or to obtain unauthorized funds from an account. Credit card fraud is also an adjunct to identity theft.

credit-detection-model-with-python

Machine learning algorithms are being developed in the financial industry, to identify fraudulent transactions. This is just what we are trying to do in this project as well. Using a dataset of almost 28,500 credit card transactions and several unsupervised anomaly detection algorithms, we will identify transactions that are highly likely to be credit card frauds. We 're designing and implementing the following two machine learning algorithms in this project: 1.Local Outlier Factor (LOF) 2.Isolation Forest Algorithm

data-mining---imdb-5000-movie-dataset

exploring IMDB Movie data set with python

deafrica-sandbox-notebooks

Repository for Digital Earth Africa Sandbox, including: Jupyter notebooks, scripts, tools and workflows for geospatial analysis with Open Data Cube and xarray

deep-learning-keras

Sentiment detection with Keras, word embeddings and LSTM deep learning networks

descriptive-analytics-exercise-1

Descriptive text analytics is a group of descriptive analytics that process large volumes of unstructured text into quantitative data to provide hindsight from the data

detecting-fake-news-with-python-and-machine-learning

In this project we are using Machine learning in python to detect Fake news.The dataset we’ll use for this python project- we’ll call it news.csv. This dataset has a shape of 7796×4. The first column identifies the news, the second and third are the title and text, and the fourth column has labels denoting whether the news is REAL or FAKE.

evaluate-factorability-exercise

Evaluate Factorability

factor-analysis

Factor analysis is a linear statistical model. It is used to explain the variance among the observed variable and condense a set of the observed variable into the unobserved variable called factors. Observed variables are modeled as a linear combination of factors and error terms (Source).

geospatial-training-with-r

machine-learning-predict-flight-delays-with-python-2

Use of flight data to predict flight delays in python

mam-2023-rainfallanalysis

Review of MAM 2023 rainfall season of Makueni county

my_projects

mysql-projects-

Compilation of SQL, Tableau, PySpark data analysis related projects and challenges where I practice those skills.

qgis_examples

samsar4

tahmo.examples

tools-for-weather-and-climate-services-in-africa

Google Earth Engine

twitter-sentment-analysis-kenya-meteorological-services

I Analysed twitter accounts of Kenya Meteorological services,Rwanda Meteo,Southern sudan Meteo,Uganda Meteo. all these organisations are providers of weather and climate information in east africa. I was interested in evaluating and understanding sentiments of its target group. We wanted to know how effective as media of communication it is.