Create a quiz app to assess online learning

As learning and collaboration moves online in response to the COVID-19 crisis, developers will need to build microservices to enable distance learning. As part of that learning, instructors need to be able to assess their students’ understanding of course material.
This tutorial shows you how to build a simple quiz app to assess learner understanding. A major benefit of the app is its flexibility: this starter kit can easily be adapted into a short essay app, a grading app, or other educational tool.
Loopback is an open source tool for quickly building a data api for your applications. Whatever your specific application’s purpose, Loopback gets you quickly writing application logic instead of data-handling code.

You can find code and related files for this tutorial in the accompanying GitHub repo.
You can also try a quiz and explore the api before you get started on your own app.
Learning objectives
By completing this tutorial, you will


Original URL: https://developer.ibm.com/tutorials/cfc-starter-kit-quiz-app-example/

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Google Cloud launches new tools for deploying ML pipelines

Google Cloud today announced the beta launch of Cloud AI Platform Pipelines, a new enterprise-grade service that is meant to give developers a single tool to deploy their machine learning pipelines, together with tools for monitoring and auditing them.
“When you’re just prototyping a machine learning (ML) model in a notebook, it can seem fairly straightforward,” Google notes in today’s announcement. “But when you need to start paying attention to the other pieces required to make an ML workflow sustainable and scalable, things become more complex.” And as complexity grows, building a repeatable and auditable process becomes harder.

That, of course, is where Pipelines comes in. It gives developers the ability to build these repeatable processes. As Google notes, there are two parts to the service: the infrastructure for deploying and running those workflows, and the tools for building and debugging the pipelines. The service automates processes like setting up Kubernetes Engine


Original URL: http://feedproxy.google.com/~r/Techcrunch/~3/5fQhZmgeyGM/

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Actor and HitRecord founder Joseph Gordon-Levitt says we should all get off YouTube

The multi-hyphenate actor-director-entrepreneur, Joseph Gordon-Levitt (best known for roles in “3rd Rock from the Sun,” “Inception,” “Snowden” and “10 Things I Hate About You,”) came to TechCrunch Disrupt SF 2019 this morning to talk about his startup, the collaborative media platform HitRecord.
Specifically, he addressed how HitRecord differs from other platforms for creators. In doing so, he also called out the YouTube business model as problematic and something we should all get away from. 
The comments around YouTube followed a discussion of some of the criticism HitRecord’s platform has faced — namely, that it doesn’t offer high enough payouts or a way for creatives to make a living.
Since 2010, it has only paid out some $3 million dollars to its creators.
Gordon-Levitt said that HitRecord doesn’t emphasize that you’ll gain entry into the creative industry by using its platform, nor does it market itself as something you can turn into a full-time


Original URL: http://feedproxy.google.com/~r/Techcrunch/~3/GHJjQOYkKFY/

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Why is Dropbox reinventing itself?

According to Dropbox CEO Drew Houston, 80% of the product’s users rely on it, at least partially, for work.
It makes sense, then, that the company is refocusing to try and cement its spot in the workplace; to shed its image as “just” a file storage company (in a time when just about every big company has its own cloud storage offering) and evolve into something more immutably core to daily operations.
Earlier this week, Dropbox announced that the “new Dropbox” would be rolling out to all users. It takes the simple, shared folders that Dropbox is known for and turns them into what the company calls “Spaces” — little mini collaboration hubs for your team, complete with comment streams, AI for highlighting files you might need mid-meeting, and integrations into things like Slack, Trello and G Suite. With an overhauled interface that brings much of Dropbox’s functionality out of the OS


Original URL: http://feedproxy.google.com/~r/Techcrunch/~3/hHYmUEjO30g/

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Build models using Jupyter Notebooks in IBM Watson Studio

This tutorial is part of the Getting started with Watson Studio learning path.
Level
Topic
Type
100
Introduction to IBM Watson Studio
Article
101
Data visualization, preparation, and transformation using IBM Watson Studio
Tutorial
201
Automate model building in IBM Watson Studio
Tutorial
301
Creating SPSS Modeler flows in IBM Watson Studio
Tutorial
401
Build models using Jupyter Notebooks in IBM Watson Studio
Tutorial

Introduction
This tutorial explains how to set up and run Jupyter Notebooks from within IBM® Watson Studio. We start with a data set for customer churn that is available on Kaggle. The data set has a corresponding Customer Churn Analysis Jupyter Notebook (originally developed by Sandip Datta), which shows the archetypical steps in developing a machine learning model by going through the following essential steps:
Import the data set.

Analyze the data by creating visualizations and inspecting basic statistic parameters (for example, mean or standard variation).

Prepare the data for machine model building (for example, by transforming categorical features into numeric features and by normalizing the data).

Split the data


Original URL: https://developer.ibm.com/tutorials/watson-studio-using-jupyter-notebook/

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How YACHT fed their old music to the machine and got a killer new album

The band YACHT, named for a mysterious sign seen in Portland around the turn of the century. [credit:
YACHT / Google I/O 2019 ]

The dance punk band YACHT has always felt like a somewhat techy act since debuting in the early 2000s. They famously recorded instrumental versions of two earlier albums and made them available for artists under a Creative Commons license at the Free Music Archive. Post-Snowden, they wrote a song called “Party at the NSA” and donated proceeds to the EFF. One album cover of theirs could only be accessed via fax initially (sent through a Web app YACHT developed to ID the nearest fax to groups of fans; OfficeMax must’ve loved it). Singer Claire L. Evans literally wrote the book (Broad Band) on female pioneers of the Internet.
So when Evans showed up at Google I/O this summer, we


Original URL: https://arstechnica.com/?p=1560697

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Create your first Assistant-powered chatbot

This article is part of the Watson Assistant learning path.
Level
Topic
Type
100
Introduction to Watson Assistant
Article
101
Create your first Assistant-powered chatbot
Tutorial
200
Create a web-based chatbot with voice input and output
Code pattern
201
Create a banking chatbot
Code pattern
300
Create a Google Action with Watson Assistant
Code pattern
301
Create an Alexa skill with serverless and a conversation
Code pattern
400
Create a next-generation call center with Voice Gateway
Code pattern

Watson Assistant can help you solve a problem by providing an intelligent interface using natural language. You can use the tools provided by the Assistant service with skills that will directly help your customers. The flexibility of the GUI tools and APIs combine to allow you to power applications and tools using AI in simple and powerful ways. The videos in this tutorial explain how to create the Watson Assistant service and how to add intents and entities.
What you’re going to learn
The following video gives a brief explanation of what you’ll create with this tutorial.

Create the Assistant


Original URL: https://developer.ibm.com/tutorials/create-your-first-assistant-powered-chatbot/

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Facebook open sources PyText NLP framework

Facebook AI Research is open sourcing some of the conversational AI tech it is using to power its Portal video chat display and M suggestions on Facebook Messenger.
The company announced today that its PyTorch-based PyText NLP framework is now available to developers.
Natural language processing deals with how systems parse human language and are able to make decisions and derive insights. The PyText framework, which the company sees as a conduit for AI researchers to move more quickly between experimentation and deployment will be particularly useful for tasks like document classification, sequence tagging, semantic parsing and multitask modeling, among others, Facebook says.
The company has built the framework to fit pretty seamlessly into research and production workflows with an emphasis on robustness and low-latency to meet the company’s real-time NLP needs. The product is responsible for models powering more than a billion daily predictions at Facebook.

Another big highlight is the framework’s modularity, allowing it


Original URL: http://feedproxy.google.com/~r/Techcrunch/~3/_l0qJPEBrJI/

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Amazon Comprehend adds customized language lists to machine learning tool

Last year Amazon announced Comprehend, a natural language processing tool to help companies extract common words and phrases from a corpus of information. Today, a week ahead of its Re:invent customer conference, Amazon announced an enhancement to Comprehend that allows developers to build lists of specialized words and phrases without machine learning domain knowledge.
“Today we are excited to bring new customization features to Comprehend, which allow developers to extend Comprehend to identify natural language terms and classify text which is specialized to their team, business or industry,” Matt Wood, GM for deep learning and AI wrote in a blog post announcing the enhancement.
The key aspect of this is that Amazon is handling all of the complexity, allowing developers to add customized lists without having deep machine learning or natural language processing background. “Under the hood, Comprehend will do the heavy lifting to build, train, and host the customized machine learning


Original URL: http://feedproxy.google.com/~r/Techcrunch/~3/e_UhGsptuug/

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