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amazon-sagemaker-examples

Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

atap

Code for Applied Text Analysis with Python

auto-sklearn

Automated Machine Learning with scikit-learn

awesome-gcp-certifications

A curated list of resources for learning about Google Cloud Platform certifications and how to prepare for it.

aws-apigateway-lambda-authorizer-blueprints

Blueprints and examples for Lambda-based custom Authorizers for use in API Gateway.

baycomp

Baycomp is a library for Bayesian comparison of classifiers

bigquery-bokeh-dashboard

bigquery-oreilly-book

Source code accompanying: BigQuery: The Definitive Guide by Lakshmanan & Tigani to be published by O'Reilly Media

cortex

Machine learning infrastructure platform for developers

d6tflow

Python library for building highly effective data science workflows

data-engineering-on-gcp-cheatsheet

data-science--cheat-sheet

Cheat Sheets

data-science-on-gcp

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017

deploymentmanager-samples

Deployment Manager samples and templates.

fes

Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson

gds-word-cloud

Easy word clouds in Google Data Studio

gmplot

Plotting data on google maps, the easy (stupid) way.

h2o-3

Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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.

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

introduction_to_ml_with_python

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

jupyter-helpers

A collection of helpers for Jupyter/IPython

lime

Lime: Explaining the predictions of any machine learning classifier

linearmodels

Linear models including instrumental variable estimators and panel data models

machinelearningnotebooks

Use the example notebooks in this repo to explore the Azure Machine Learning service.

map-classifier-python

Maximum A Posteriori Classifier

modin

Modin: Speed up your Pandas workflows by changing a single line of code

nbdime

Tools for diffing and merging of Jupyter notebooks.

nova-jupyterlab-extensions

optimization-methods-for-tuning-predictive-models

Code and slides from a 2016 talk at the Cambridge UK RUG