Leonard Apeltsin

Leonard Apeltsin is the head of data science at Anomaly. His team applies advanced analytics to uncover healthcare fraud, waste, and abuse. Prior to Anomaly, Leonard led the machine learning development efforts at Primer AI, a startup that specializes in natural language processing. As a founding member, Leonard helped grow the Primer AI team from 4 to nearly 100 employees. Before venturing into startups, Leonard worked in academia, uncovering hidden patterns in genetically linked diseases. His discoveries have been published in the subsidiaries of the journals Science and Nature. Leonard holds BS degrees in biology and computer science from Carnegie Mellon University and a PhD in bioinformatics from The University of California, San Francisco.

products by Leonard Apeltsin

Data Science Bookcamp Projects

11 weeks · 4-8 hours per week average · INTERMEDIATE

Are you ready to work out with the Data Science Bookcamp? This series of liveProjects takes you hands-on with fun and engaging data science challenges from the bestselling book by Leonard Apeltsin. It features Discovering Disease Outbreaks from News Headlines, which he co-created with Will Koehrsen, Nate George’s Decoding Data Science Job Postings to Improve Your Resume, and three original projects by Emre Rencberoglu. Each challenge stretches your data science muscles and teaches you useful new skills through practice, such as using NumPy and SciPy for mathematical operations, clustering with scikit-learn, and analyzing and visualizing network datasets with NetworkX. Tackle them individually or all of them for an intensive workout of your data capabilities!

Uncovering Friend Groups in Social Networks

  • Course duration: 56m

A primer for social network analysis using Python’s NetworkX graph analysis library.

NLP Analysis of Large Text Datasets

  • Course duration: 1

A demonstration of xClustering of large text datasets in Python.

Discovering Disease Outbreaks from News Headlines

4 weeks · 5-10 hours per week · INTERMEDIATE

In this liveProject, you’ll take on the role of a data scientist at the World Health Organization (WHO). The WHO is responsible for responding to international epidemics, a critical component of which involves monitoring global news headlines for signs of disease outbreaks. However, this daily deluge of news data is too huge to manually analyze. Your challenge is to pull geographic information from headlines, and determine where in the world outbreaks are occurring. Problems you will have to solve include extracting information from text using regular expressions, using the Basemap Matplotlib extension to visualize map locations for patterns indicating an epidemic, and reporting your findings to your superiors so resources can be dispatched.

Data Science Bookcamp

  • October 2021
  • ISBN 9781617296253
  • 704 pages
  • printed in black & white
  • Available translations: Complex Chinese, Korean, Russian, Simplified Chinese

Data Science Bookcamp doesn’t stop with surface-level theory and toy examples. As you work through each project, you’ll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don’t quite fit the model you’re building. You’ll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you’ll be confident in your skills because you can see the results.