karmacelina Goto Github PK

2015lab1

Forked repo; using it to review DS tools learned in Metis. [Harvard CS109 class]

atlaspr

Interactive, detailed maps of Puerto Rico

biterm

Biterm topic model

boricua_registry

Connecting Loved Ones in PR

citi_bike

Analysis of 2015 CitiBike data

d3-book

Sample code files to accompany the book “Interactive Data Visualization for the Web”

dsp

Metis Data Science Bootcamp - Official Prework Repository

gensim

Topic Modelling for Humans

imbalanced-learn

Python module to perform under sampling and over sampling with various techniques.

instagramcrawler

A non API python program to crawl public photos, posts or followers

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

islr-python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

karmacelina.github.io

Blog

kyotoux-009x

lifelines

Survival analysis in Python

lifetimes

Lifetime value in Python

machine_learning_examples

A collection of machine learning examples and tutorials.

mining-the-social-web-2nd-edition

The official online compendium for Mining the Social Web, 2nd Edition (O'Reilly, 2013)

ml-from-scratch

Machine Learning algorithms implemented in Python from scratch

mta_traffic_eda

mtb_snail_uploads

naive_bayes_classifier

numerical-mooc

A course in numerical methods with Python for engineers and scientists: currently 5 learning modules, with student assignments.

pandas-cookbook

Recipes for using Python's pandas library

pandas-videos

Jupyter notebook and datasets from the pandas Q&A video series

pandas_exercises

Practice your pandas skills!

parametric_tsne

Python / Tensorflow / Keras implementation of Parametric tSNE algorithm

plotly.py

An interactive, browser-based graphing library for Python :sparkles:

pr_mort_official

Data and pipeline for Mortality in Puerto Rico after Hurricane Maria

predicting_movie_widest_release

This project relied on extracting and munging scraped, unstructured data from the Box Office Mojo website to apply regression modeling techniques for actionable insight extraction.