alwilliams2433 Goto Github PK

2016-springboard-course

3.1.4-model-comparison

Using the housing data that we prepared in a previous assignment, I will now build two models (KNN and Linear Regression) to compare them.

applied-machine-learning

Applied Machine Learning @ http://amitkaps.com/ml

applied_machine_learning

Assignments from Applied Machine Learning Course in Columbia University

appliedml

Appl ML

appliedml-spring2017

Assignments for Applied Machine Learning at Columbia University, Spring 2017

automated-elk-stack-deployment

automated-elk-stack-deployment-old

bayesian-linear-regression

A python tutorial for a Bayesian treatment of Linear Regression: https://zjost.github.io/bayesian-linear-regression/

columbia_capstone_2017

Code and files for Data Science Capstone project at Columbia University, Fall 2017

csbc-homework

data-tutorials

A collection of data science and systems administration tutorials.

data_analysis_with_python_and_pandas

The Code belonging to my course "Data Analysis in Python and pandas"

deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

deep-learning-book-chapter-summaries

Attempting to make the Deep Learning Book easier to understand.

excelsorter

Reads a file of records, sorts them, and then writes them back to another file.

foundations

Foundations of Computing (Columbia University, 2018)

ga_classes

house_prices_bayesian_regression

Assignment 3 for Machine Learning Course @ Columbia University. Used data from Kaggle House Prices DataSet. Link provided in the notebook.

introstatlearn

Exercises from 'Introduction to Statistical Learning with Applications in R' written in Python.

introtostatisticallearningr-

Work on Introduction to Statistical Learning

machine-learning

Coursework at Columbia University

markdown-here

Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.

ml_pot_11-08

Class material for November 8, 2018 Hands-on Introduction to Machine Learning with Watson Studio

pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

proben1

A copy of the datasets for PROBEN1 from the paper "Proben1: A Set of Neural Network Benchmark Problems and Benchmarking Rules", Lutz Prechelt

pyrotutorial

PyroTutorial

python-machine-learning-book

The "Python Machine Learning (1st edition)" book code repository and info resource

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

python_learning