A Technology Broker and Management Company Specializing in KM Systems
Favorite Anyone who has tried building a bot to support interactions knows that managing the conversation flow can be tricky. Real users (people who obviously haven’t rehearsed your script) can digress in the middle of a conversation. They could ask a question related to the current topic or take the
Read More
Shared by AWS Machine Learning August 9, 2019
Favorite The Amazon ML Solutions Lab worked with Kinect Energy recently to build a pipeline to predict future energy prices based on machine learning (ML). We created an automated data ingestion and inference pipeline using Amazon SageMaker and AWS Step Functions to automate and schedule energy price prediction. The process
Read More Shared by AWS Machine Learning August 9, 2019
Favorite Launched at AWS re:Invent 2018, Amazon SageMaker Ground Truth enables you to efficiently and accurately label the datasets required to train machine learning (ML) systems. Ground Truth provides built-in labeling workflows that take human labelers step-by-step through tasks and provide tools to help them produce good results. Built-in workflows
Read More Shared by AWS Machine Learning August 8, 2019
Favorite Businesses use the Twilio platform to build new ways to communicate with their customers: whether it’s fully automating a restaurant’s food orders with a conversational Interactive Voice Response (IVR) or building a next generation advanced contact center. With the launch of Media Streams, Twilio is opening up their Voice
Read More Shared by AWS Machine Learning August 7, 2019
Favorite By the year 2050, our planet will need to feed ten billion people. We can’t expand the earth to create more agricultural land, so the solution to growing more food is to make agriculture more productive and less resource-dependent. In other words, there is no room for crop losses
Read More Shared by AWS Machine Learning August 6, 2019
Favorite With a few clicks in the Amazon SageMaker console or a few one-line API calls, you can now quickly search, filter, and sort your machine learning (ML) experiments using key model attributes, such as hyperparameter values and accuracy metrics, to help you more quickly identify the best models for
Read More Shared by AWS Machine Learning August 3, 2019
Favorite Git integration is now available in the Amazon SageMaker Python SDK. You no longer have to download scripts from a Git repository for training jobs and hosting models. With this new feature, you can use training scripts stored in Git repos directly when training a model in the Python
Read More Shared by AWS Machine Learning August 3, 2019
Favorite This is a guest blog post by Paul DeHart, co-owner and CEO, BlueToad. BlueToad, one of the leading global providers of digital content solutions, prioritizes innovation. Since 2017, we have enabled publishers (our customers) to provide audio versions of articles found in their digital magazines using Amazon Polly. We see
Read More Shared by AWS Machine Learning August 2, 2019
Favorite This is a guest blog post by Dante Monaldo, co-founder and CTO of Pluto Money Pluto Money, a San Francisco-based startup, is a free money management app that combines banking, behavioral economics, and machine learning (ML) to guide Generation Z towards their financial goals in college and beyond. We’re
Read More Shared by AWS Machine Learning August 2, 2019
Favorite The race is on! Start your engines! The AWS DeepRacer Scholarship Challenge from Udacity is now open for enrollment. As mentioned in our previous post, the AWS DeepRacer Scholarship Challenge program introduces you—no matter what your developer skill levels are—to essential machine learning (ML) concepts in a fun and
Read More Shared by AWS Machine Learning August 2, 2019