🌹Join us for a special IBM Watson Studio three-part series.  You can attend all three or pick and choose the ones that best fit your needs.

✅ IBM Watson Super-class: Build & Deploy Models w Jupyter Notebooks → Dec 9th @ 12:30pm ET Come learn how to use Juypter Notebooks in a secure cloud environment to analyze data. You will learn how to prepare and normalize the data for machine model building, split data into training sets for model validation, train the model by using machine learning algorithms and finally deploy the model so that it can be accessed outside of the notebook.

* Basics of Jupyter Notebooks on Watson Studio

* Learn how to normalize, split, train with Python and deploy data in a Jupyter Notebook

** Get a head start by signing up for a free IBM Cloud account via → http://ibm.biz/watson_superclass_three_cloud **

Julia Nash
Offering Manager & Developer Advocate at IBM

Saishruthi Swaminathan
Data Scientist & Developer Advocate at IBM

Yiwen Li, (@yil532) is a developer advocate and data scientist at IBM. She has been creating online content such as code patterns, tutorials, and blogs demonstrating the potential of products and services offered by IBM (like Watson Studio, Machine learning, Model Asset eXchange, Data Asset eXchange, etc.). She holds dual degree, including BS in Probability and Statistics and BA in Economics from the University of California, San Diego.

Jenna Ritten (@jritten) is a cloud software developer turned developer advocate for IBM Cloud. She works on expanding the reach of open source technologies to Detroit and Austin's developer communities. Her areas of interest include hackathons, design-thinking workshops, NLU/NLP, gamified learning, and Blockchain. Jenna left Detroit to attend Dev Bootcamp San Francisco to learn full-stack web development before joining IBM Austin as part of the Tech Re-Entry program. She is an advocate for non-traditional people in tech and supports underrepresented people in tech.

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✅ IBM Watson Super-class: Build & Deploy Models w Visual Recognition & Natural Language Classifier → Dec 7th @ 12:30pm ET Come learn how to quickly store, train, test and deploy custom visual recognition and natural language model with Watson Studio! You will learn how to quickly and accurately tag, classify, and train and manage your visual and natural language data, using machine learning in a secure cloud environment!

* Learn how to build, classify and train custom visual content and natural language using machine learning

✅ IBM Watson Super-class: Build & Deploy Custom Models w AutoAI → Dec 8th @ 12:30pm ET Come learn how to build and deploy your very own AI predictive models. IBM Watson Studio AutoAI automatically analyzes your data and generates customized predictive model pipelines. Using AutoAI, you can build and deploy a machine learning model with sophisticated training features and no coding!

IBM Watson Super-class: Build & Deploy Models w/ Jupyter Notebooks