The Practical Data Scientist
Gowthami PeriA newsletter focused on applying data science to real-world problems, with practical insights on building impactful solutions and growing a successful career in the field.
| Platform |  | Pricing | Only free issues | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 30 | Founded | 6 months ago | Last Issue | 8 days ago |
| Active | |||||
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thepracticaldatascientist.substack....Latest Issues
No full article this week!
I don’t have a regular article for you this week.
Rather than rush one out, I’m working on something a little different for next week.
Special Edition: How to Crack Behavioral Interviews
We’ll cover how to build a story bank, choose the...
Matrix Factorization for Recommendation Systems
Introduction
Last time, we talked about collaborative filtering — the idea that if two people liked a lot of the same movies, you can use one person’s taste to recommend something to the other.
It’s a good idea. It just doesn’t scale w...
Collaborative Filtering: Learning From What Others Like
Introduction
In the previous article, we looked at content-based filtering. The idea was simple: understand what a user already likes, look at the characteristics of those items, and recommend other items with similar features.
It work...
Where’s the Money in Data?
Dataford shared a report from over 85,000 job listings and more than 600,000 interviews with me. Here’s what it shows about which data jobs pay the most, and how hard they are to get.
Thanks for reading The Practical Data Scientist! Subscr...
Building an End-to-End Content-Based Recommendation System
Introduction
In my previous article, I explored how content-based recommendation systems work—how they use the characteristics of items to identify and recommend similar products.
But understanding the idea is only the first step.
Wha...
Key Facts
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| Subscribers | Engagement | 70 | Monthly Web Visits | ||
|---|---|---|---|---|---|
| Accepts Sponsors | Estimated Cost per Ad | ||||
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Authors
The writers behind this newsletter.
Gowthami Peri is a Data Scientist passionate about making data science practical and accessible. She writes The Practical Data Scientist, sharing insights on analytics, machine learning, experimentation, AI, and career growth in data.
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