codebrain001/zoom_topic_modelling

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Python
Created almost 4 years ago
Updated almost 4 years ago

codebrain001/zoom_topic_modelling

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customer-churn-prediction

Jupyter Notebook

Interactive-charts-for-frontend-data-visualization-using-flask-and-D3js

datafest22

Jupyter Notebook

DroneProjects

COVID19-forecasting-with-fbprophet

Jupyter Notebook

Catboost-tutorial

Jupyter Notebook

COVID19-time-series-analysis

Jupyter Notebook

INEC-web-scraping

To scrape citizens information from the INEC website using the Voters Identification Number

PDDA-Sonic-Log-Prediction

Jupyter Notebook

DSN-Staff-Algorithm

Abdullah’s Baba Yakub, 38, is the heir apparent to the highly revered Yakub business dynasty. The enterprise has spanned decades with vast investment interest in all the various sectors of the economy. Abdullah has worked for 16 years in Europe and America after his first and second degrees at Harvard University where he studied Engineering and Business Management. He is a very experienced technocrat and a global business leader who rose through the rank to become a Senior Vice President at a leading US business conglomerate. His dad is now 70 and has invited him to take over the company with a mandate to take it to the next level of growth as a sustainable legacy. Abdullah is trusted by his father and his siblings to lead this mandate. On resumption, he had an open house with the staff to share his vision and to listen to them on how to take the business to the next level. Beyond the general operational issues and increasing need for regulatory compliance, one of the issues raised by the staff was a general concern on the process of staff promotion. Many of the staff allege that it is skewed and biased. Abdullah understood the concern and promised to address it in a most scientific way. You have been called in by Abdullah to use your machine learning skills to study the pattern of promotion. With this insight, he can understand the important features among available features that can be used to predict promotion eligibility.

Jupyter Notebook

South-African-COVID-19-Vulnerability-Map-by-ZindiWeekendz

The task is to predict the percentage of households that fall into a particularly vulnerable bracket - large households who must leave their homes to fetch water - using 2011 South African census data. Solving this challenge will show that with machine learning it is possible to use easy-to-measure stats to identify areas most at risk even in years when census data is not collected.

Jupyter Notebook

Credit-Card-Fraud-detection

Jupyter Notebook

COVID19-data-scraping

Jupyter Notebook

Chime_Modelling

Spatial-Data-Engineering-using-Dask-in-ArcGIS-Pro

Performing Spatial Data Engineering operations using Dask in ArcGIS Pro

Jupyter Notebook

msc-dissertation

Utilising LLM agents for requirement analysis and specification from preliminary meeting notes

containerized-app

Jupyter Notebook

deepchecks_model_validation

Jupyter Notebook

A-tactile-guide-to-Python-Collections

Jupyter Notebook

Scientific-Computing-and-Python-for-Data-Science

Jupyter Notebook

EAGE_YP_PVC

Jupyter Notebook

spam_detection

SMS spam detection system using Machine Learning, Python, Flask and Vonage API

Jupyter Notebook

ML-Workflow-Breast-cancer-prediction

Jupyter Notebook

Whatsapp-spatial-mapping

Getting-started-with-Spatial-Data-Science-

Jupyter Notebook

layer_fraud_detection

Jupyter Notebook

jupyter-docker-workflow

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