placing your order...Don't refresh or navigate away from the page.
I like how well thought-out and well-defined the instructions were! This liveProject was very informative.
In this liveProject, you’re a data scientist at a healthcare provider that deals with large volumes of incoming text. Your task is to analyze a large dataset containing medical transcriptions. Leveraging technologies including pandas, the IBM Project Debater API, and Seaborn, you’ll explore a Kaggle dataset, segment text data into known categories, and extract key points.
You’ll finish by building an interactive data visualization dashboard for analysis in the open-source framework Streamlit. When you’re done, you’ll have leveled up your NLP toolbox with skills that are highly sought not only in healthcare but in law, customer support, market intelligence, media, and many other fields.
The IBM Data Science Community is a place dedicated to people supporting the practice of data science in their businesses, for practitioners by practitioners. Whether you’re a data scientist, machine learning engineer, AI developer, or someone working on the AI lifecycle, the community lets you connect with others, engage on timely topics, and share your expertise.
This liveProject is for intermediate data scientists. To begin this liveProject, you’ll need to be familiar with the following:TOOLS
In this liveProject, you’ll learn NLP skills widely used by data scientists in fields including healthcare, law, customer support, market intelligence, media, and others.
This liveProject gives you a wide variety of tools to work through. It teaches you how to use a cloud NLP API to analyze text data and takes you into how you can use that to build a dashboard.
I like how this course incorporated a brand new technology (IBM Project Debater) and also included some more established technologies like Streamlit and Seaborn. All were new to me, and I felt like it gave a good introduction to the type of work you can do with these technologies and left me excited to explore them more on my own.