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He is also a Data Scientist at Cobrain Company in Bethesda, MD where he builds data products including recommender systems and classifier models. He is currently pursuing his PhD in Computer Science at The University of Maryland, College Park, doing research in Metacognition and Active Logic. #Nodebox python install how toStoring computational models using picklesĪfter this course you should understand how to build a data product using Python and will have built a recommender system that implements the entire data science pipeline.īenjamin is an experienced Data Scientist and Python developer who has worked in military, industry, and academia for the past eight years. Wrangling data into SQLite Databases using SQLAlchemyīuilding a recommender system with PythonĬomputing a matrix factorization with Numpy The workshop will cover the following topics:īasic project structure of a Python application In particular you will learn how to structure a data product using every stage of the data science pipeline including ingesting data from the web, wrangling data into a structured database, computing a non-negative matrix factorization with Python, then producing a web based report. The purpose of this one-day course is to introduce the development process in Python using a project-based, hands-on approach. Therefore, it is important to have a basic working knowledge of the language in order to access more complex topics in data science and natural language processing. Python is one of the most popular programming languages for data analysis. There's even an early bird discount if you register before the end of this month! Tagged: data science, python, data products, workshopĭata Community DC and District Data Labs are excited to be hosting another Building Data Apps with Python workshop on August 23rd. In this class we’ll produce a data product with Python, leveraging every stage of the data science pipeline to produce a book recommender. Python contributes to every stage of the data science pipeline including real time ingestion and the production of APIs, and it is powerful enough to perform machine learning computations. Python is flexible enough to develop extremely quickly on many different types of servers and has a rich tradition in web applications. These applications have been largely built with Python. #Nodebox python install softwareThe rise of these types of applications has directly contributed to the rise of the data scientist and the idea that data scientists are professionals “who are better at statistics than any software engineer and better at software engineering than any statistician.”
2 Comments
1/27/2023 09:32:14 pm
This blog is very informative content... Thanks a lot for sharing
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