data_science/

All material is licensed under the Apache License Version 2.0, January 2004 http://www.apache.org/licenses/LICENSE-2.0 go build ./example1 Sample program to show how to cache data from an API.

Sample program to save data from an API in an embedded k/v store.

Sample program to show how to cache data from an API, and then use that data in analyzing a dataset.

Sample program to show how to cache data from an API, and then use that data in analyzing a dataset.

Sample program to profile our data set.

Sample program to train and validate a kNN model with cross validation.

Program for finding an optimal k value for a k nearest neighbors model.

Template programe for finding an optimal k value for a k nearest neighbors model.

Sample program to train and validate a decision tree model with cross validation.

Sample program to determine an optimal value of the decision tree pruning parameter.

Sample program to visualize the accuracy of models with various decision tree pruning parameters.

Sample program to visualize the accuracy of models with various decision tree pruning parameters.

Sample program to read in records from an example CSV file to a dataframe.

Sample program to create a dataframe and subsequently filter and subset the dataframe.

Sample program to register of CSV file as an in-memory SQL database and execute SQL queries on the CSV.

Sample program to register of CSV file as an in-memory SQL database and execute SQL queries on the CSV.

Sample program to read in a CSV, create three filtered datasets, and save those datasets to three separate files.

Sample program to register of CSV file as an in-memory SQL database, sum float columns, and output a process CSV.

Sample program to read in a CSV, create three filtered datasets, and save those datasets to three separate files.

Sample program to register of CSV file as an in-memory SQL database, sum float columns, and output a process CSV.

Sample program to read in records from an example CSV file.

Sample program to read in records from an example CSV file, and catch an unexpected extra field in the data.

Sample program to read in records from an example CSV file, and catch an unexpected types in a single column.

Sample program to save records to a CSV file.

Sample program to read in records from an example CSV file, and catch an unexpected types in any of the columns.

Sample program to read in records from an example CSV file, catch an unexpected types in any of the columns, and output processed data to a different CSV file.

Sample program to read in records from an example CSV file, and catch an unexpected types in any of the columns.

Sample program to read in records from an example CSV file, catch an unexpected types in any of the columns, and output processed data to a different CSV file.

Sample program to illustrate the calculation of principal components.

Sample program to visualize the impact of dimensionality reduction.

Sample program to project iris data on to principal components.

Sample program to project iris data on to 3 principal components.

Sample program to project iris data on to 3 principal components.

Sample program to calculate an R^2 value.

Sample program to calculate a mean absolute error.

Sample program to calculate a accuracy.

Sample program to calculate precision.

Sample program to calculate recall.

Sample program to calculate specificity.

Sample program to calculate a mean squared error.

Sample program to calculate specificity.

Sample program to calculate a mean squared error.

Sample program to calculate expected values.

Sample program to calculate a chi-squared value.

Sample program to output the result of the test, based on a critical value.

Sample program to compare parsing a clean CSV with Go to parsing a clean CSV with python.

Sample program to illustrate maintaining integrity with Go in the presence of messy data.

Sample program to illustrate maintaining integrity with Go in the presence of messy data.

Sample program to illustrate maintaining integrity with Go in the presence of messy data.

All material is licensed under the Apache License Version 2.0, January 2004 http://www.apache.org/licenses/LICENSE-2.0 go build ./example1 Sample program to show how to unmarshal JSON data from an API.

All material is licensed under the Apache License Version 2.0, January 2004 http://www.apache.org/licenses/LICENSE-2.0 go build ./example1 Sample program to show how to save JSON data to a file.

All material is licensed under the Apache License Version 2.0, January 2004 http://www.apache.org/licenses/LICENSE-2.0 go build ./exercise1 Sample program to show how to unmarshal JSON data from an API.

All material is licensed under the Apache License Version 2.0, January 2004 http://www.apache.org/licenses/LICENSE-2.0 go build ./template1 Sample program to show how to unmarshal JSON data from an API.

Sample program to read in records from an example CSV file and form a matrix with gonum.

Sample program to show modifications to matrices.

Sample program to access values within a matrix.

Sample program to illustrate various ways to format matrix output.

Sample program to read in records from a CSV file and form a matrix with gonum.

Sample program to read in records from a CSV file and form a matrix with gonum.

Sample program to show basic matrix operations.

Sample program to compute the transpose, determinant, and inverse of a matrix.

Sample program to solve an eigenvalue/vector problem.

Sample program to compute vector and matrix norms.

Sample program to divide a matrix by its norm.

Sample program to divide a matrix by its norm.

Sample program to profile our data set.

Sample program to investigate correlations between our target and our features.

Sample program to create training, test, and holdout data sets.

Sample program to train and test a regression model.

Sample program to validate a trained regression model on a holdout data set.

Sample program to train and test a multiple regression model.

Sample program to validate a trained multiple regression model on a holdout data set.

Sample program to train and test a multiple regression model.

Sample program to validate a trained multiple regression model on a holdout data set.

Sample program to connect to and ping a database connection.

Sample program to load the iris dataset into a database.

Sample program to retrieve results from a database.

Sample program to modify data in a database.

Sample program to retrieve results from a database.

Sample program to delete rows in a database table.

Sample program to retrieve results from a database.

Sample program to delete rows in a database table.

Sample program to calculate means, modes, and medians.

Sample program to calculate means, modes, and medians.

Sample program to calculate standard deviation and variance.

Sample program to calculate quantiles

Sample program to calculate both central tendency and statistical dispersion measures for the iris dataset.

Sample program to calculate both central tendency and statistical dispersion measures for the iris dataset.

Sample program to generate a histogram of a normal distribution.

Sample program to generate a histogram of the iris data variables.

Sample program to generate a box plot of example distributions.

Sample program to generate box plots of the iris data variables.

Sample program to generate a box plot of diabetes bmi values.

Sample program to generate a histogram of diabetes bmi values.

Sample program to generate a box plot of diabetes bmi values.

Sample program to generate a histogram of diabetes bmi values.