data-becki Goto Github PK

ab-testing-at-nosh-mish-mosh

Using numpy to help a food delivery service figure out the amount of data they’ll need to make meaningful decisions.

airline-analysis

Using seaborn to perform exploratory data analysis airline pricing data.

biodiversity-in-national-parks

Using matplotlib and seaborn to interpret data from the National Parks Service about endangered species in different parks.

bookclub-r4ds

R for Data Science Book Club

breast-cancer-classifier

Using several Python libraries to make a K-Nearest Neighbor classifier that is trained to predict whether a patient has breast cancer.

chocolate-scraping-with-beautiful-soup

Codecademy project using Beautiful Soup to scrape a website and gain insights into the best chocolate bars.

cleaning-us-census-data-project

Working with US Census Data for the Data Wrangling and Tidying portion of the codecademy Data Science path.

codecademy-students-and-grades

The final exercise in the Python classes module on codecademy that I didn't quite understand.

date-a-scientist

dr.-diracs-statistics-midterm

Using probabilities to determine if a student answered a question correctly, what is the probability that she really knows the material?

eda-diagnosing-diabetes-project

Working with medical data for the Data Wrangling and Tidying portion of the codecademy Data Science path.

email-similarity

Using Naive Bayes on several different datasets. By reporting the accuracy of the classifier, we can find which datasets are harder to distinguish.

final-codecademy-project---libraries-in-oregon

This is the final project in the codecademy Data Science Career Path, using Python, EDA, Data Visualization, Data Cleaning and Prepping, Linear Regression Machine Learning.

find-the-flag

Using decision trees to try to predict the continent of flags based on several features.

heart-disease-research-ii

Using binom_test, ttest_1samp, ttest_ind, f_oneway, pairwise_tukeyhsd, chi2_contingency to investigate some data from a sample of patients who were evaluated for heart disease.

heart-disease-research-part-i

Using scipy.stats to investigate some data from a sample of patients who were evaluated for heart disease.

honey-production

Using linear regression to investigate the decline and how the trends of the past predict the future for the honeybees.

hypothesis-testing-projects

Three projects in the codecademy data science career path.

life-expectancy-and-gdp

Using matplotlib and seaborn to try and identify the relationship between the GDP and life expectancy of six countries.

matplotlib-challenge-projects

Four codecademy projects using Matplotlib to investigate twitch data, food delivery service data, and roller coaster data.

ml_linear_regression

moderndive_book

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

mystery-friend

Using scikit-learn’s bag-of-words and Naive Bayes classifier to determine who the mystery writer of a postcard is.

nba-trends-project

Using pearsonr and chi2_contingency from scipy stats to analyze data from the NBA (National Basketball Association) and explore possible associations.

netflix-data-codecademy-capstone-project

Using seaborn to create some of the visualizations for a stock profile of Netflix.

okcupid-date-a-scientist

Codecademy Machine Learning portfolio project using ML to predict whether someone has pets using OkCupid dataset.

pandas-aggregates-a-b-testing-for-shoefly-project

Using Pandas to analyze results of posting two different versions of an advertisement.

pandas-multiple-tables-page-visits-funnel-project

Using Pandas to describe how many people continue to the next step purchasing through a website.

pandas-petal-power-project

Using Pandas to analyze the inventory of a gardening store.

predict-baseball-strike-zones-with-machine-learning

Using an SVM (Support Vector Machine) trained using a baseball dataset to find the decision boundary of the strike zone.