How to maximize your impact in 2019 with the AI for Good challenge

A 3-step guide for maximizing your impact in 2019:

  1. Have an idea for how to use AI to help address society’s challenges.
  2. Spend some time thinking about your idea and formulate a plan of action. Is your idea impactful? Feasible? Scalable?
  3. Apply for Google.org’s AI for Good grant.

Google.org is still looking for for organizations around the world to submit ideas for solving societal problems with AI. If your idea is selected, you will receive Google.org grant funding from a $25M pool, support and consulting with Google’s AI and cloud experts, and more resources to help your idea become a reality. The deadline to apply is January 22.

Need some help getting started? Check out some of these resources:

  1. The 7 Steps of Machine Learning, video, 10 minutes: Join Yufeng as he applies machine learning  to universal questions.
  2. AI Experiments: A showcase for simple experiments to help you start exploring ML through music, images, language and more.
  3. 6 free data-related labs: Start exploring the capabilities of BigQuery and data analysis in the Google Cloud – key components of using AI effectively.
  4. Want more labs? Check out a previous post with lots of gnarly data/ML/AI use cases and scenarios.

Get artificial intelligence training with these resources and online training modules, then submit your ideas by January 22 – good luck!

An open call for crazy ideas

Got an idea so crazy it just might work? Google’s AI for good team wants to hear it. Just announced, Google.org is calling for organizations around the world to submit ideas for solving societal problems with AI. If your idea is selected, you will receive Google.org grant funding from a $25M pool, support and consulting with Google’s AI and cloud experts, and more resources to help your idea become a reality.

Not sure where to start? There’s a lab for that. Learn about AI, machine learning and GCP tools, and how they come together in real-world scenarios. Then apply what you learn to approach societal problems you are passionate about. For a limited time through November 24, use the links in this post to claim 45 free Qwiklabs credits, good towards any lab in the catalog. Just enter promo code 1q-165 – it sounds crazy, but it just might work!

  1. The Cloud ML Engine: Qwik Start lab is an excellent starting point if you’re new to GCP. This lab assumes little to know prior knowledge, and by the end of the lab you have built a TensorFlow model, trained it both locally and in the cloud using Cloud ML Engine (CMLE), and used GCP’s online prediction service. 
  2. Classify Images of Clouds in the Cloud with AutoML Vision: The Zoological Society of London is using AutoML to protect endangered species. Try it for yourself with a lab.
  3. Scikit-learn Model Serving with Online Prediction Using Cloud Machine Learning Engine: This 4+ star lab teaches you how to train a simple scikit-learn model, upload the model to ML Engine, and make online predictions against that model.
  4. Translate Text with the Translation API: Can you think of how smooth, seamless translation might be part of your solution? Learn how to take advantage of Google Cloud’s translation API in just 30 minutes. Talk nerdy to me!
  5. Integrating Machine Learning APIs: Now that you have API experience, learn how to use multiple APIs to construct a pipeline that compares an audio recording with an image and determines their relevance to each other. This is an advanced level lab, so if you find yourself in trouble, check out this intro to APIs lab.
  6. Real Time Machine Learning with Google Cloud ML: While a delayed flight is a minor inconvenience compared to societal problems like protecting endangered species and forecasting catastrophic flooding, it is certainly not fun to be stuck in an airport far from home. (I’m writing this in an airport by the way!) This lab teaches you how to create a real-time flight delay prediction service using Google Cloud Platform services. Can you think of how you might apply what you learn to other scenarios?

Get artificial intelligence training with these Google Cloud labs, then submit your ideas at https://ai.google/social-good – good luck!

Are you ready for an AI-first future?

Join Google Cloud CEO Diane Greene and other experts for a free online conference on the future of artificial intelligence. The conference rolls through time zones too, so no matter where you are in the world, there’s a session for you.

Prepare yourself for deep-dives by taking cloud training ahead of time. Each of the following quests guides you through using GCP tools to answer an AI business question or solve a technical challenge. Use what you learn to ask the best questions and have the most meaningful conversations with your conference moderators. Use these links for a 1-month pass to Qwiklabs (free of charge, no CC required). Offer ends November 13th. 

  1. Get your data insight-ready:

Enroll in the Baseline: Data, ML, AI quest to work with BigQuery, Cloud Speech API and Cloud ML Engine. Follow Mark as he guides your path in these 1-minute videos. You’re on your way to building a strong foundation in data management, cloud data warehouse and real-time analytics to implement AI.

2. Put AI to work, fast:

Enroll in the Data Science on GCP quests to practice data ingestion, preparation, exploration and visualization. Finish the first quest and move on to the next, which zooms in on running machine learning jobs with state-of-the-art tools and real-world data sets. The material for these quests comes from a book by Lak, who amongst others will elaborate on how data scientists, developers and others can incorporate AI into their products during the conference. 

3. See AI in action:

Brush up on your ML skills with the Machine Learning APIs quest – some of my favorite labs guide you through use cases like image classification with Cloud Vision API and building an AI chatbot (: Then you’re well on your way to learn how businesses use AI to solve complex business problems like fighting fraud.

Think you can finish one of these quests in one month? Enroll now and be the stand-out participant at the conference! 

Become a data scientist without a PhD: Part 2

Remember that $1.2 trillion business value of AI? Just released, a new set of data science labs zoom in on Google Cloud’s data science and ML tools.  Enroll in the Data Science on GCP: Machine Learning quest by Monday, November 15th and you’ll get 1 month pass to Qwiklabs (free of charge, no CC required). You’ll run machine learning jobs with state-of-the-art tools and real-world data sets.

There are over 8,500 Data Scientist jobs on LinkedIn. 68% of those jobs require machine learning expertise. As a data scientist, you will transform data to:

  • Improve revenue, business agility, customer experience
  • Reduce costs
  • Development of new products and or product features

Don’t have these skills, or want to improve? You don’t need a PhD. Learn how to do all of these things and more with a lab. Here are some of the labs:

  1. Machine Learning with Spark on Google Cloud Dataproc lab: Analyze data using Spark with the PySpark interactive shell on the master node of the Cloud Dataproc cluster running on Google Cloud Datalab:

Then create and train a Spark Dataframe by importing, developing, saving and restoring a logistic regression model. You will then build data visualizations with Jupyter notebooks. In your model, does the on-time arrival probability rise with overall flight distance? Share your results @Qwiklabs!

2. Processing Time Windowed Data with Apache Beam and Cloud Dataflow (Java): You’ll configure Maven Apache using the starter project archetype for Cloud Dataflow projects:

Patience! This will take a few minutes to compile… When the build is successful, you should see something like this:

Finally! You’re ready to deploy a Java application to Apache Beam to create training and test data files.

If you are successful, you should see these files. Did you get it? Share your results! @Qwiklabs.

3. Bayes Classification with Cloud Datalab, Spark and Pig on Google Cloud Dataproc: Have you ever performed quantization of a data set? Here’s your chance. Use Dataproc, Datalab and Spark to perform quantization of a dataset to improve the accuracy of a data model. Then visualize your data with Jupyter notebooks and Apache Pig:

And don’t forget about part 1, the Data Science on GCP quest. Both quests cover the hands-on exercises described in Data Science on Google Cloud Platform book by Valliappa Lakshmanan (Lak).

You are invited to get started on your cloud journey

Did you know that the GCP Essentials quest shows you how to spin up a VM, configure key infrastructure tools, set up Load Balancers and work with Kubernetes nodes, all in less than four hours? Use this link to enroll in the quest by Friday, November 16th and you’ll get 10 Qwiklabs credits  (free of charge, no credit card required) to help you get started.

Then continue your cloud journey in person! Check out these events:

OnAir: Register for a live 45-minute webinar with Google Cloud experts to prepare for an AI-first future.  Join Diane Greene Google Cloud CEO, and the team for an interactive look at artificial intelligence by unlocking the benefits of machine learning.

DevFest: Another opportunity to meet with your community! DevFest is powered by a belief that when developers come together to exchange ideas, amazing things can happen. Each event is uniquely tailored to the needs of a hosted-region, and while your local event may or may not incorporate labs, we hope you can make it!

Next Extended: Not just in San Francisco – Next Extended events bring GCP to your town. Event starts off with food, networking and keynotes and transition to an open panel discussion. Attend a Next Extended event near you and be sure to join the hands-on labs session!

Summits: You can choose from over 20 sessions on machine learning, app development, infrastructure, security, etc. Work with executives, customers, partners, developers, IT decision makers and Google engineers to build the future of the cloud. Choose your city and see where the cloud takes you.

Google Cloud OnBoard: It’s a free, instructor-led training event, that introduces you to GCP. You’ll learn how to get started with virtual machines, containers, applications, big data, and machine learning through presentations and demonstrations. Attendees get a free 30-day pass to Qwiklabs to help you finish the GCP Essentials quest.

Study jams: We learn better together! Study jams are an opportunity to meet with the community of technology enthusiasts to brainstorm and dig deep into cloud concepts as a group. It’s a hands-on event where attendees get free access to the labs ($55+ value). You’ll learn fundamental GCP tools and technologies like Kubernetes, Stackdriver, and cloud storage with the GCP Essentials quest. Earn a Google-hosted badge to show your “flight time” with Google Cloud and encourage other members of your community to do the same.

Enroll in the GCP Essentials quest and come to an event near you. We look forward to meeting you!

Wherefore art thou, Machine Learning training?

How do you learn something new? Do you read a book, watch a video, take a course? Maybe the right answer is poetry.

When you’re learning to use data science tools you need, well, big data to practice. And that’s where Shakespeare comes in. Billy S. wrote 37 plays, 154 sonnets and invented 1700 words (like eyeball, bedazzled, and arch-villain). His works are publicly available and perfect for data manipulation. With the help of Shakespeare, learn how data science tools like BigQuery and TensorFlow can help you take advantage of powerful Google Cloud machine learning technology. And for a limited time, use the links below and get 37 free Qwiklabs credits (as many credits as plays) to take the bard’s favorite labs.

BigQuery: Qwik Start – Command Line: Storing and querying massive datasets can be expensive. Learn how Google Cloud can help you save, after all, “if money go before, all ways do lie open” (The Merry Wives of Windsor). Learn how to move your data into BigQuery and take advantage of the processing power of Google’s infrastructure.

BigQuery training

Big Data Analysis to Slide Presentation: Did you know that Shakespeare invented the word “manager”? Impress yours by learning how to gather and crunch your data, then generate a slide and spreadsheet presentation to blow away management and stakeholders with your breathtaking analytical capabilities and intelligent conclusions.

Big Data and Google Slides analysis

Run a Big Data Text Processing Pipeline in Cloud Dataflow: Learn how to run a Dataflow pipeline that counts the occurrences of unique words in a text file. Not only will you learn how many times the word “alas” appears in King Lear, you’ll learn to use a powerful tool for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation.
Dataflow Pipeline trainingTensorFlow For Poets: Finally, while we don’t know if a rose by any other name smells as sweet, we can use TensorFlow to identify a rose among a floral lineup. Think about what else you could use this technology for – scanning for free parking spaces? Locating your company’s discarded scooters?

Tensorflow training

How they use Machine Learning to train self-driving cars

Interested in self-driving cars? Learn the technology behind the magic – then sit back, relax, and let the car do it for you.

  1. How do autonomous cars recognize speed limit signs? “See” for yourself with the Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API lab (bonus, follow that link and get the lab free of charge). You’ll build a model that recognizes landmarks and items in photos with a simple REST API. 
  2. Then, how do cars know the speed limit? The Extract, Analyze, and Translate Text from Images with the Cloud ML APIs lab shows you how to translate signs – not just read them – which means machine learning can improve your commute no matter what side of the road you drive on.
  3. Some cars know what’s around you – trucks, cars, motorcycles, even reindeer.  Learn how to use Google’s Machine Learning tools to  Classify Images of Clouds in the Cloud with AutoML Vision.
  4. Even when conditions aren’t perfect, cars can predict what’s next. Start making predictions with the Cloud ML Engine: Qwik Start lab.

With these labs, you’re well on your way to your next badge, Machine Learning APIs. Enroll here, and you’ll get 55 Qwiklabs credits to start your next Quest (limited offer, ends January 31, 2019).

Good luck, buckle up!

Back to school: Cloud training for educators

Jobs in the tech industry (machine learning, AI, Cloud) will grow between 12%–37% through 2022. Your computer science curriculum can unlock possibilities for students’ career advancement. Take advantage of free Google Cloud Platform training resources to help your students grow computer science skills:

    • If you’re associated with a non-profit university, complete this form to request free training on Qwiklabs and Coursera.

Next, use your benefit to have your students enroll in a few machine learning Quests:

  • Baseline: Data, ML, AI Quest: Since machine learning is growing rapidly in the tech industry, help your students get started with data tools like Cloud SQL, BigQuery, APIs, Bigtable, Dataproc, Dataprep, and Cloud ML Engine. If your students are interactive learners, they can follow along Mark as he guides their path.
  • Machine Learning APIs Quest: Give your students the opportunity to work with a handful of machine learning APIs. For example, they’ll work with Translation API and Natural Language API to translate text into other languages. They’ll also work with Cloud Vision API to capture text from images and Google Cloud Dialogflow to build a responsive chat bot.
  • Data Science on GCP Quest. Challenge your students to use Tensorflow, Dataflow and Data Studio to practice all aspects of datasets, such as ingestion, exploration, visualization, etc.

Fun fact: This Quest is derived from the book, Data Science on Google Cloud Platform by Valliappa Lakshmanan. Lak is on a mission to democratize machine learning. If your students were to read the book, they will learn how to apply statistical and machine learning methods to real-world problems.

If your class is interested in learning about the fundamentals of Google Cloud in-person, register for a study jam. Your students will get free access to the GCP Essentials Quest during the session and you’ll get two days of free lesson plans. If they complete the Quest within 1 month of their session, they’ll get a 30-day pass to Qwiklabs (free of charge, no CC required). They can use the pass to tackle any of the machine learning Quests mentioned above.

Why wait? Take advantage of these programs and set your students up for success by helping them add these badges to their resumes:

        

Machine Learning for .NET developers

Democratizing machine learning continues, this time for .NET. Google Cloud is committed to supporting developers getting their .NET workloads up and running on the GCP. Enroll in the Developing Data and Machine Learning Apps with C# and you’ll get 35 Qwiklabs credits, good towards labs in the new Quest (free of charge, no CC required).

Each lab demonstrates how to hook up your data to Google’s ML tools with just a few simple commands. You even get app templates you can re-use when you work on your own projects.

  • Using BigQuery with C# (60 mins): To  or not to , that is the question. Use BigQuery to analyze Shakespeare, a GitHub dataset and data you upload yourself (could be anything).
  • Using the Natural Language API with C# (45 mins): Analyze how awesome Yukihiro Matsumoto is, with documentSentiment. What did you get? The overall sentiment analysis consists of two fields: sentiment and magnitude. Sentiment ranges between -1.0 (negative) and 1.0 (positive). Magnitude indicates the overall strength of emotion (both positive and negative) within the given text, between 0.0 and +inf. Pop quiz: who remembers how to diagram a sentence? Now you can #makegoogledoit, one more talent of the Natural Language API.
  • Using the Speech-to-Text API with C# (45 mins): How many languages do you speak? The Google Cloud Speech-to-Text API has 120 different languages and variants. Even French or a Brooklyn accent. For extra credit, see if the API can transcribe a clip of your speech when you take the lab. Check it out on TechCrunch (:
  • Using the Video Intelligence API with C# (45 mins): You’ll work with a shot-change detection example in this lab. What other types of changes would you want to identify? Maybe a model that detects activity in wildlife monitoring cameras or security footage…
  • Using the Vision API with C# (45 mins): What do otter crossing signs have in common with the Eiffel Tower? The Google Cloud Vision API can recognize them both. Learn how to protect wildlife and organize your vacation photos with a lab. Then apply the skills you learned next time you build a license plate recognition app, or rank the most popular landmarks #teampixel is sharing.

  • Using the Translation API with C# (45 mins): How do you say “hello world” in Turkish? I don’t know – but we can use the Translation API to do it for us. Text is translated using the Neural Machine Translation (NMT) model. If the NMT model is not supported for the requested language translation pair, then the Phrase-Based Machine Translation (PBMT) model is used. And “hello world” in Turkish? Selam Dünya!
  • Cloud Spanner: Create a Gaming Leaderboard with C# (60 mins): Ready player one – wait, who won the last round? Learn to create a leaderboard with C# – this one is the most advanced lab in the Quest so prepare to be challenged!

Hurry, click here to enroll by the weekend and get 35 credits to help you get started. Good luck!

Take AutoML Vision for a test drive

What kind of cloud is this?

I don’t know either. Can you think of other types of images that would be useful to classify? For example, if you have an online tire shop, wouldn’t it be cool if your customers could upload a photo of their current tire to find a matching replacement?

AutoML can help your tire shop decrease the number of returns and increase customer delight. And it’s easier than you think – learn how to take advantage of this powerful new tool with a new lab, AutoML Vision API.

Here’s some of what you’ll do:

  • You’ll be prompted to log into the AutoML UI. Open the link in a new tab to make it easy to hop between AutoML and your lab manual. Then, you’ll log into AutoML with your Qwiklabs-provided credentials.
  • In the AutoML UI, you will see a button for “Billing”. You do not need to worry about billing for this lab, as Qwiklabs covers the cost of this lab for you.
  • When you load data into your storage bucket, you’ll set your project name with one of the first commands you run. Find your project name on the left of your lab manual, just below your GCP credentials:

AutoML is currently in beta, so we expect to see constant changes to the user interface. Send any questions to Support@Qwiklabs.com and we’ll be happy to help. Plus you’ll help us keep the lab up to date as the product continues to improve!

Curious about what type of clouds were spotted during our trip to Muir Woods? Here are our model’s predictions:

The model is 99% certain these are cumulus clouds! Prediction certainty and accuracy would be better if we trained our model with more than 20 images per category. When you’re helping customers order tires, you will probably want to use 100+ photos per category.

Happy lab-taking!