WaniaKhance/Real-Time_Data_Center_Energy_Management

This project is Master thesis research conducted at ENEA Portici Research Center, Italy. The data is obtained from the HPC CRESCO6 cluster at ENEA Portici Research Center. The aim is to identify energy consuming areas within the data center. In this project, real-time dataset from ENEA Portici Research Center is used. There are several techniques implemented including big data analytics and AI technology.

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ndcastillo/inferential-statistics-DS-AI

Contains inferential statistical practices for machine learning models and analyses. Using Python and developing statistical thinking to work with a limited sample of data and be able to generate predictions about it. Applying confidence intervals to estimate unknown values. Using bootstrapping to simulate data acquisition repeatedly. Development of hypotheses of their models. Sampling of populations to facilitate analysis.

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LatiefDataVisionary/inferential-statistics-college-task

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Alesarabandi/Inferential-Statistics-Analyzing-Gender-Differences-in-Climbing-Route-Grades

This project investigates whether there is a statistically significant difference in the average climbing route grades between males and females. Using R, the analysis employs both traditional (t-test) and non-traditional (bootstrap and permutation methods) inferential statistics to test the hypothesis.

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MarkzDG/Metodos_estadisticos

Una exhibición de algunos de los métodos estadísticos que he aprendido a lo largo de mi carrera. Explora métodos estadísticos clave y aplicaciones prácticas: regresión, pruebas de hipótesis, ANOVA, PCA y más.

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Anas436/Hypothesis-Testing-using-NHANES-Data-with-Python

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Anas436/Confidence-Intervals-for-Differences-between-Population-Parameters-with-Python

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WaniaKhance/Advance_Prediction_of_Electricity_Consumption_UK

In this project, an analytical approach on the large dataset is applied for advance prediction of average household electricity consumption located in different regions of United Kingdom. Several machine learning models are implemented and compared for the prediction analysis. This project also involves an estimation of the expected emission of CO2 in the environment using deep learning modelling based on the predicted usage of electricity.

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nishitpatel01/nyc-taxi-data-analysis

Analysis of human behaviour in NYC using taxi data

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chiajieh/gss 📦

Statistical Inference with the GSS Data

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selotape/G-PhoCS Fork of gphocs-dev/G-PhoCS

G-PhoCS is a software package for inferring ancestral population sizes, population divergence times, and migration rates from individual genome sequences.

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tamborello/Rutils

These are some scripts I wrote in R to obtain, transform, and make sense of data. They include obtaining data from remote servers via API and from local text and Excel files. They also include some custom parsing logic, inferential statistical analyses, and graphical plots.

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