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, perform sentiment analysis 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 perform sentiment analysis and deploy data in a Jupyter Notebook

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

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, much like herself, and provides support by building and fostering communities for underrepresented people in tech.

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.

IBM Project Debater: Sentiment Analysis w Jupyter Notebooks