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.
– 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.
– 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.
– TensorFlow 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?
If you haven’t enrolled in the machine learning Quests mentioned in this blog, you’re missing out! One last chance for free labs, follow any of the Quest links in this post and get a 30 day pass to finish these Quests. Hurry, offer expires Thursday, June 28 (free of charge, no CC required).
Tackle any of the Quests from the roadmap below to become a ML master. If you’re a beginner… begin at the beginning 🙂
Earn a machine learning Quest badge or two, get practice with real-world scenarios, and make the most out of your time at Next ‘18 with some ML rockstars. Who might you meet at Next ’18?
Fei Fei Li is a Chief Scientist of Cloud AI and ML at Google Cloud. She works in the areas of computer vision and cognitive neuroscience. Her publications include Scaling Human-Object Interaction Recognition through Zero-Shot Learning and Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks. Get hands-on practice with Cloud AI at scale with the Machine Learning APIs Quest.
Or you might run into Valliappa Lakshmanan. Lak is on a mission to democratize machine learning so anyone can do it using Google’s infrastructure. Check out his latest book, Data Science on the Google Cloud Platform, explaining how to apply statistical and machine learning methods to real-world problems. And try it for yourself with a lab from the Scientific Data Processing Quest!
Take some labs ahead of time, gain a little experience, and ask better questions at the ML sessions offered at the Next ’18! Check out these sessions:
Can’t get enough of machine learning? When you register for Next ‘18, you will have the option to add some of these ML boot camps:
- End-to-End Machine Learning with TensorFlow on GCP: You’ll go through the process of building a complete machine learning pipeline, covering ingest, exploration, training, evaluation, deployment and prediction.
- Building and updating a Machine Learning Model on Edge Network using Cloud ML: You’ll learn how to process and store IoT or other data using Cloud Pub/Sub, Cloud Dataflow, Cloud Storage, and Google BigQuery.
- Building Chatbots with Machine Learning: You’ll use Dialogflow and Cloud Natural Language API to rapidly convert an HR manual document into a fully functional and conversational chatbot. You’ll also add text and voice interactions to the chatbot and secure and scale it for production.
If you can’t make it to Next in San Francisco, take classes worldwide. Find one here.
To make the most of your time at Next ’18, enroll in these ML Quests by Thursday, June 28 (free of charge, no CC required).