haoybl

records

SQL for Humans™

flask-sqlalchemy

Adds SQLAlchemy support to Flask

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

pyomo

The main repository for the Pyomo optimization modeling software.

tensorflow

Computation using data flow graphs for scalable machine learning

movie_review_classifier

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

pymc

PyMC: Bayesian Stochastic Modelling in Python (for PyMC3: https://github.com/pymc-devs/pymc3)

lantern

🔴Lantern Latest Download https://github.com/getlantern/lantern/releases/tag/latest 🔴蓝灯最新版本下载 https://github.com/getlantern/forum/issues/833 🔴

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 ;)

ISLR-python

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

geoalchemy

Using SQLAlchemy with spatial databases

matplotlib

matplotlib: plotting with Python

pytrain

Machine Learning library for python

lifelines

Survival analysis in Python

PyomoGallery

A collection of Pyomo examples

statsintro_python

Python modules and IPython Notebooks, for the book "Introduction to Statistics With Python"

deeplearning_projects

blaze

NumPy and Pandas interface to Big Data

scikit-image

Image Processing SciKit (Toolbox for SciPy)

models

Models built with TensorFlow

seaborn

Statistical data visualization using matplotlib

patsy

Describing statistical models in Python using symbolic formulas

py-earth

A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines

scientific-python-lectures

Lectures on scientific computing with python, as IPython notebooks.

hmmlearn

Hidden Markov Models in Python, with scikit-learn like API

House-Prices-Prediction-Regression

Models that predict house prices by predicting a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. I have explored regularized linear regression models for the task of prediction and feature selection. I was able to handle very large sets of features and select between models of various complexities. Analyzed the impact of aspects of the data -- such as outliers -- on the selected models and predictions. To fit these models, I have implemented optimization algorithms that scale to large datasets.

pymc3

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

scipy-lecture-notes

Tutorial material on the scientific Python ecosystem

sci-pype

A Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository.