tlohani31 Goto Github PK

amazon-sagemaker-examples

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

aws-data-wrangler

Pandas on AWS

dd-panel-blog

Code for Intro to Difference-in-Differences Blog Post

dimensionality_reduction_viz

document-clustering

dsnd_term1

Contains files related to content and project of DSND

dsnd_term2

Contains files related to content and project of DSND Term 2

gnu-rl

A precocial reinforcement learning solution for HVAC control

inter_workshop

Workshop materials for ODSC 2019 Interpretability Talk

introtoml

ML utils

mapping-geographic-data-in-r

Files relating to the "Mapping Geographic Data in R" workshop at ODSC Boston, 2019

ml-workshop-2-of-4

Intermediate Machine Learning with Scikit-learn, 4h interactive workshop

ml-workshop-3-of-4

Advanced Machine Learning with Scikit-learn part I

ml-workshop-4-of-4

Advanced Machine Learning with Scikit-learn part II

model_validation_tutorial

Tutorial of machine learning model validation

mpc.pytorch

A fast and differentiable model predictive control (MPC) solver for PyTorch.

network-analysis-made-simple

For PyCon, PyData, ODSC, and beyond!

odsc-missing-data-may-18

Open Data Science Conference East, 2018: Data Science with Missing Data

odsc-west-2018-missing-data

ODSC West 2018 - Good, Fast, Cheap: How to do Data Science with Missing Data

odsc-west-2018-visualization

ODSC West 2018 - Data Visualization: From Square One to Interactivity

odsc_neural_nets_11-04-17

Talk "Deep Learning From Scratch Using Python" delivered at ODSC West on November 4, 2017

openshift-ml-workflows-workshop

This is material for a tutorial that @sophwats and @willb developed about machine learning workflows and about running them on OpenShift

or-gym

Environments for OR and RL Research

pomegranate

Fast, flexible and easy to use probabilistic modelling in Python.

pyathena

PyAthena is a Python DB API 2.0 (PEP 249) client for Amazon Athena.

reinforcement-learning-explained

This repository contains the lab files for Microsoft course DAT257x: Reinforcement Learning Explained

reinforcement_learning_for_traffic_light_control

Apply deep reinforcement learning methods including DQN, DDPG for traffic light control in simulation (discrete environment), to prove the 'Green Wave' phenomenon in intelligent traffic system.

workshop

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker