AWS DeepRacer – Tips and Tricks – Battery and SSH

If you would like to know more about what the AWS DeepRacer is, please refer to my previous post:  AWS DeepRacer – Overview

I was going to do an unboxing video, but Andrew Knaebel has done a well enough job of that and posted it on YouTube, so I’ll skip that part and move onto more detail on getting up and running with the AWS DeepRacer. 

A lot of this is covered in the AWS DeepRacer Getting Started Guide so I’ll try and focus on the places where it was not so clear.… [Keep reading] “AWS DeepRacer – Tips and Tricks – Battery and SSH”

AWS DeepRacer – Training your reinforcement learning model in AWS Robomaker

If you would like to know more about what the AWS DeepRacer is, please refer to my previous post:  AWS DeepRacer – Overview

There seems to be many ways to get your AWS DeepRacer model trained. These are a few I have discovered:

  • The AWS DeepRacer Console (Live Preview yet to commence, GA early 2019)
  • SageMaker RL notebook
  • Locally from the DeepRacer GitHub repository
  • AWS RoboMaker sample simulation
  • AWS RoboMaker Cloud9 IDE with sample application downloaded

In this post, we will be exploring how to train a reinforcement learning model using AWS Robomaker, both with the sample application downloaded and in the Cloud9 development environment.… [Keep reading] “AWS DeepRacer – Training your reinforcement learning model in AWS Robomaker”

AWS DeepRacer – How to load a model

If you would like to know more about what the AWS DeepRacer is, please refer to my previous post:  AWS DeepRacer – Overview

This post assumes you have followed the AWS DeepRacer Getting Started Guide which gets you to the point of being able to manually drive the car.

So now you have the AWS DeepRacer charged up and ready to go. You have a trained model you got from Re:Invent or you followed my other post here and trained your model with RoboMaker/SageMaker.… [Keep reading] “AWS DeepRacer – How to load a model”

AWS DeepRacer – How to login to the Ubuntu Computer Onboard

If you would like to know more about what the AWS DeepRacer is, please refer to my previous post:  AWS DeepRacer – Overview

This post assumes you have followed the AWS DeepRacer Getting Started Guide which gets you to the point of being able to manually drive the car.

So to go deep into your understanding of the AWS DeepRacer and to troubleshoot deep technical issues, it may become necessary to log into the Ubuntu Server on-board the AWS DeepRacer.… [Keep reading] “AWS DeepRacer – How to login to the Ubuntu Computer Onboard”

AWS DeepRacer – Overview

Recently I had the privilege of attending the AWS Re:Invent 2018 conference in Las Vegas. Among the hundreds of announcements, there was one that particularly spoke to my passions of reinforcement learning and robotics.

The AWS DeepRacer!

I was one of the lucky few that got into the AWS DeepRacer workshops where we were introduced to the technology in the service as well as interacting with the yet to be released DeepRacer console.… [Keep reading] “AWS DeepRacer – Overview”

Using AWS EC2 Instances to train a Convolutional Neural Network to identify Cows and Horses

First published at https://nivleshc.wordpress.com

Background

Machine Learning (ML) and Artificial Intelligence (AI) has been a hobby of mine for years now. After playing with it approximately 8 years back, I let it lapse till early this year, and boy oh boy, how things have matured! There are products in the market these days that use some form of ML – some examples are Apple’s Siri, Google Assistant, Amazon Alexa.
Computational power has increased to the point where calcuations that took months can now be done within days.… [Keep reading] “Using AWS EC2 Instances to train a Convolutional Neural Network to identify Cows and Horses”

How LUIS can help BOTs in understanding natural language

Since bots are evolving, you need a mechanism to better understand what user wants from his/her language and take actions or respond to user queries appropriately. In the days of increasing automation, bots can certainly help provided they are backed by tools to understand user language both naturally and contextually.
Azure Cognitive Services has an API that can help to identify what user wants, extracts concepts and entities from a sentence (user input) using an intelligent service name Language Understanding Intelligent Service (LUIS).… [Keep reading] “How LUIS can help BOTs in understanding natural language”

Using Azure Machine Learning to predict Titanic survivors

So in the last blog I looked at one of the Business Intelligence tools available in the Microsoft stack by using the Power Query M language to query data from an Internet source and present in Excel. Microsoft are making a big push into the BI space at the moment, and for good reason. BI is a great cloud workload. So now let’s take a look at one of the heavy hitters at the other end of the BI scale spectrum, Azure Machine Learning.… [Keep reading] “Using Azure Machine Learning to predict Titanic survivors”

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