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A Data science and Analytics project with the main aim of doing some Descriptive and Exploratory Data Analysis and then applying predictive modelling for predicting why and which are the best and most experienced employees leaving prematurely?
Hospital Database Management System (DBMS) is a comprehensive SQL project designed to streamline and optimize the management of hospital operations. This project aims to provide an efficient and user-friendly solution for storing, retrieving, and manipulating various types of healthcare-related data.
This is a supply chain analytics project using Python, Tableau. In which conducted an analysis of supply chain inefficiencies, and developed informative dashboards to inform business stakeholders of potential issues, along with proposing strategic business enhancements.
Introduction to Data, Signal, and Image Analysis with MATLAB Welcome to Introduction to Data, Signal, and Image Analysis with MATLAB! MATLAB is an extremely versatile programming language for data, signal, and image analysis tasks, including hundreds if not thousands of functions. With such a comprehensive tool set, knowing where to start can be…
There are basic/advanced codes, notes and exercises for data analysis and data visualization. There are notes about statistic and advanced implement of statistic at python. There are some folders about exploratory data analysis, regex, linear algebra etc. Pandas, NumPy, Seaborn, Matplotlib, SciPy, Researchpy.
Hydro Analyser is is a first ever open source tool designed for hydrogeologists, engineers, and other professionals in the water resources industry to accurately analyze and optimize groundwater pumping tests
The dataset that we will be wrangling (and analysing and visualising) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog.
This project focuses on predicting diseases using various machine learning models. We import and clean the data, selecting features for our model. The dataset contains variables representing various clinical symptoms, with prognosis as the outcome, which is a result of the combination of symptoms.