jet2016 Goto Github PK

ds_projects_2020

dsc-data-science-env-installation-v2-1-onl01-dtsc-pt-030220

dsc-html-introduction-lab-onl01-dtsc-pt-030220

dsc-introduction-to-numpy-online-ds-ft-061019

dsc-lists-online-ds-sp-000

dsc-pep8-online-ds-pt-120919

dsc-python-operators-functions-and-methods-online-ds-pt-061019

dsc-strings-online-ds-ft-061019

expressing-functions-ds-apply-000

flatiron-school-data-science-curriculum-resources

galvanize_classified_2

The Angular front end to Galvanize Classified.

gcloud-tweaks

Google Cloud Console commands tweaks

gmaps

Google maps for Jupyter notebooks

healthcare-case-study-data-science-leadership

Final project - DSCI6006 - Leadership for Data Scientists

house_prices

Projects

house_prices_data_analysis

human-resource-analytics-and-employee-churn-prediction

A Data science and Analytics project with the main aim of doing some Descriptive and Exploratory Data Analysis and then applying predictive modelling for predicting why and which are the best and most experienced employees leaving prematurely?

jet2016.github.io

killrweather

KillrWeather is a reference application (work in progress) showing how to easily integrate streaming and batch data processing with Apache Spark Streaming, Apache Cassandra, Apache Kafka and Akka for fast, streaming computations on time series data in asynchronous event-driven environments.

learn-ab-and-multivariate-testing

Tutorial on A/B and multivariate testing :heavy_check_mark:

learn-co-sandbox

learndatascience

Open Content for self-directed learning in data science

mapsplotlib

Custom Python plots on a Google Maps background. A flexible matplotlib like interface to generate many types of plots on top of Google Maps.

marketing-analytics-case-study-data-science-leadership

Marketing Analytics project - One of the two final projects in the class DSCI6006 - Data Science for Leaders - part of UNH-Galvanize data science graduate program.

neural-nlp

Framework for performing NLP deep learning experiments

nlp---amazon_foods_review_analysis

This was the final project for NLP Class(DSCI 6004) at Galvanize. This project uses Bag of Words and Macro Level Text Summary models to process data. Machine Learning models (KNN, Naive Bayes, Quadrant Discriminant Analysis, Random Forest) were used to evaluate the data. Additional performance metric used was time taken by these Machine learning models to run.

nn-from-scratch

Implementing a Neural Network from Scratch

nonlinear-derivatives-readme-ds-apply-000

numpy

Numpy main repository

photorestoration

A hit and go photo restoration pipeline