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aim325-monitor-ml-models-efficiently-across-fleets-of-devices

amazon-sagemaker-analyze-model-predictions

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

amazon-sagemaker-fraud-detection

async_inference_sagemaker_sample

deep-learning-traffic_sign_recognizer

First project to understand Deep learning

labs

Repository of SageMaker Machine Learning Labs

multipath-forwarding-using-sdn-controller

This code shows the benefits of multipath forwarding by displaying a JavaScript visualization of what is happening in the network while streaming a video between two nodes. It uses WebSockets and animation.js for displaying the data, VLC and RTP to stream the video between the two nodes.

network-automation---ansible-to-automate-provisioning-of-pfsense-firewall

This playbook makes easier update of aliases lists of pfsense and help in provisioning of interfaces

objectorientedjava-coursera

This is a skeleton to use Unfolding in Eclipse as well as some starter code for the Object Oriented Programming in Java course offered by UC San Diego through Coursera.

openstack-api-

Usage of Python SDK to automate provisioning of Openstack instances

sagemaker-immersion-day

SageMaker Immersion Day Content

sagemaker-python-sdk

A library for training and deploying machine learning models on Amazon SageMaker

santander-customer-satisfaction-

From frontline support teams to C-suites, customer satisfaction is a key measure of success. Unhappy customers don't stick around. What's more, unhappy customers rarely voice their dissatisfaction before leaving. Santander Bank is asking Kagglers to help them identify dissatisfied customers early in their relationship. Doing so would allow Santander to take proactive steps to improve a customer's happiness before it's too late. In this competition, you'll work with hundreds of anonymized features to predict if a customer is satisfied or dissatisfied with their banking experience.

traffic-sign-classifier

tweets-clustering-kmeans

Implemented K-MEANS algorithm in Python using Jaccard distance as distance metric and analyzed various twitter based applications that involve truth discovery, trend analysis, search ranking.