All Projects → gboeing → Ppd599

gboeing / Ppd599

Licence: mit
USC urban data science course series with Python and Jupyter

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Ppd599

Osmnx Examples
Usage examples, demos, and tutorials for OSMnx.
Stars: ✭ 863 (-18.74%)
Mutual labels:  jupyter-notebook, transportation, network-analysis, transport
Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
Stars: ✭ 8,329 (+684.27%)
Mutual labels:  jupyter-notebook, data-science, statistics, jupyter
Crime Analysis
Association Rule Mining from Spatial Data for Crime Analysis
Stars: ✭ 20 (-98.12%)
Mutual labels:  jupyter-notebook, data-science, jupyter, spatial-analysis
Book
This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.
Stars: ✭ 141 (-86.72%)
Mutual labels:  jupyter-notebook, data-science, statistics, spatial-analysis
Cookbook 2nd Code
Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]
Stars: ✭ 541 (-49.06%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Intro To Python
An intro to Python & programming for wanna-be data scientists
Stars: ✭ 536 (-49.53%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Fastai2
Temporary home for fastai v2 while it's being developed
Stars: ✭ 630 (-40.68%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Practical dl
DL course co-developed by YSDA, HSE and Skoltech
Stars: ✭ 1,006 (-5.27%)
Mutual labels:  jupyter-notebook, course, course-materials
Stats Maths With Python
General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
Stars: ✭ 381 (-64.12%)
Mutual labels:  jupyter-notebook, data-science, statistics
Nteract
📘 The interactive computing suite for you! ✨
Stars: ✭ 5,713 (+437.95%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Cookbook 2nd
IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018
Stars: ✭ 704 (-33.71%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Data Science Your Way
Ways of doing Data Science Engineering and Machine Learning in R and Python
Stars: ✭ 530 (-50.09%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Stars: ✭ 4,674 (+340.11%)
Mutual labels:  jupyter-notebook, data-science, statistics
Probabilistic Programming And Bayesian Methods For Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Stars: ✭ 23,912 (+2151.6%)
Mutual labels:  jupyter-notebook, data-science, statistics
Edward2
A simple probabilistic programming language.
Stars: ✭ 419 (-60.55%)
Mutual labels:  jupyter-notebook, data-science, statistics
Cracking The Data Science Interview
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
Stars: ✭ 672 (-36.72%)
Mutual labels:  jupyter-notebook, data-science, statistics
Machinelearningcourse
A collection of notebooks of my Machine Learning class written in python 3
Stars: ✭ 35 (-96.7%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Probability
Probabilistic reasoning and statistical analysis in TensorFlow
Stars: ✭ 3,550 (+234.27%)
Mutual labels:  jupyter-notebook, data-science, statistics
Quantitative Notebooks
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
Stars: ✭ 356 (-66.48%)
Mutual labels:  jupyter-notebook, data-science, jupyter
Statistical Rethinking With Python And Pymc3
Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
Stars: ✭ 713 (-32.86%)
Mutual labels:  jupyter-notebook, data-science, statistics

Binder Build Status

PPD599: Advanced Urban Analytics

This is the second part of a two-course series on urban data science that I teach at the University of Southern California's Department of Urban Planning and Spatial Analysis.

This course series takes a computational social science approach to working with urban data. It uses Python and Jupyter notebooks to introduce coding and statistical methods that students can reproduce and experiment with in the cloud. The series as a whole presumes no prior knowledge as it introduces coding, stats, spatial analysis, and applied machine learning from the ground up, but PPD599 assumes you have completed PPD534 or its equivalent.

Urban Data Science course series

PPD534: Data, Evidence, and Communication for the Public Good

The first course in the series, PPD534, starts with the basics of coding with Python, then on to data loading and analysis, then on to descriptive statistics, then inference and the scientific method, and finally a critical assessment of smart cities and urban informatics.

PPD534's lecture materials are available on GitHub and interactively on Binder.

PPD599: Advanced Urban Analytics

The second course, PPD599, assumes you have completed PPD534 (or its equivalent) and builds on its topics. It introduces spatial analysis, network analysis, spatial models, and applied machine learning. It also digs deeper into the tools and workflows of urban data science in both research and practice.

PPD599's lecture materials are available in this repo and interactively on Binder.

Not a USC student?

Did you discover this course on GitHub? Come study with us: consider applying to the urban planning master's or PhD programs at USC.

Are you interested in data science and spatial analysis to improve urban transportation around the world, critically interrogate how big data reshapes housing affordability, or leverage technology for better city planning? We seek students from all backgrounds. If you're an activist or urbanist with no tech experience, we will teach you data/tech skills to effectively apply your knowledge to serve the community. If you're a coder or scientist interested in urbanism and planning, we will teach you how to unlock your skills for more equitable cities.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].