This repository contains a collection of Jupyter Notebooks for conducting Exploratory Data Analysis (EDA) and Statistical Analysis on various datasets.

This repository contains the notebooks that can reproduce the results presented in the paper "Classical and quantum regression analysis for the optoelectronic performance of NTCDA/p-Si UV photodiode"

Time series prediction Notebooks

Análise de Ansiedade: Notebook para Processamento e Visualização

If you liked my analysis, pls upvote my notebook!

Materials for all my UWaterloo Data Science workshops including summaries, notebooks, slides, and video. Topics include deep learning, clustering, recommender systems, and regression analysis.

Jupyter Notebook of sinusoidal regression of Yuba River data from USGS NWIS

Some jupyter notebooks exploring statistical models and tests, sample data all included.

A Jupyter Notebook about analyzing and predicting a small dataset of car prices in India.

There are teaching notes that I created in Jupyter notebook to teach statistics for Data science

Jupyter Notebook of sinusoidal regression of Sacramento International Airport (SMF) daily temperature data from NCEI NOAA

Completed Udemy's TensorFlow Developer Course, earning certification on 6th Jan 2024. Includes Jupyter Notebooks and certification PDF. Utilized resources from mrdbourke's TensorFlow repo. Explore assignments, project work, and connect for TensorFlow discussions.

Jupiter notebook to predict the outcome of passengers who died or not in the tragical Titanic event.

This Python Notebook was developed for a challenge: whose model is the most performant in predicting apartments' sale prices?

This notebook contains the EDA, data cleaning, modeling and prediction parts of the "House Price- Advance Regression Techniques" problem from Kaggle.

This repository contains datasets and notebooks for estimating building heating and cooling loads. Explore analyses using Linear Regression with and without sklearn.

ML-Premier-League-Wins-Predictor is my first machine learning project that predicts the number of wins for each team in the Premier League using linear regression. Explore the key factors that contribute to becoming a champion in one of the world's most competitive football leagues. Jupyter Notebook and code included.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow

This open source project is a notebook series for data collection, data pre-processing, exploratory data analysis, and machine learning processes on the haptic touch dataset collected from GetEmotion application.

This project involves building a machine learning model to predict airfare prices based on various features such as airline, date of journey, source, destination, and duration. The dataset used is sourced from Kaggle, and the notebook demonstrates data preprocessing, feature engineering, model training, and evaluation