For years, TensorFlow dominated deep learning, but more AI developers are switching to PyTorch—and for good reason. With its intuitive Pythonic design and flexible execution, PyTorch makes it easier than ever to build and train neural networks. In this guide, we break down why PyTorch is gaining traction, walk you through a simple model predicting salaries, and help you take your first steps in deep learning.
The Dataquest Download
Level up your data and AI skills, one newsletter at a time.
Each week, the Dataquest Download brings the latest behind-the-scenes developments at Dataquest directly to your inbox. Discover our top tutorial of the week to boost your data skills, get the scoop on any course changes, and pick up a useful tip to apply in your projects. We also spotlight standout projects from our students and share their personal learning journeys.
Hello, Dataquesters!
Here’s what we have in store for you in this edition:
Top Read: TensorFlow vs. PyTorch—why AI developers are making the switch and how to build your first deep-learning model. Learn more
From the Community: Explore deep learning for IPO predictions, exchange rate trends, and mobile app engagement insights. Join the conversation
New Resource: Introduction to Cloud Computing—get started with AWS, Azure, and Google Cloud fundamentals. Learn more
From the Community
Predicting IPO Listing Gains with Deep Learning: Sam’s TensorFlow project stands out for its structured approach, strong feature engineering, and insightful visualizations.
Visualizing Daily Exchange Rates (1999–2024): Ofofonono explores financial data for the first time, using powerful visualizations to uncover key trends over time.
Mobile App Trends & User Engagement: Nguyen’s first guided project is an impressive deep dive into mobile app data, complete with comparisons and thoughtful recommendations.
Adding the ToC and a data dictionary to your projects: Linky shared helpful resources on how to insert the table of contents and a data dictionary into your project notebooks for easy and quick navigation and reference.
Checking for Sample Representativity: Raisa explains how to assess if a sample truly reflects the population—an essential skill for any data analyst.
DQ Resources
Introduction to Cloud Computing [New]: Learn the basics of cloud computing, including key service models (IaaS, PaaS, SaaS), deployment types, and major providers like AWS, Azure, and Google Cloud. Learn more
Building and Presenting Your Data Portfolio (Data Coach Insights): Learn how to create a strong data portfolio that showcases your skills, highlights impactful projects, and stands out to employers. Learn more
Profitable App Profiles—A Data Analysis Project: Learn to analyze mobile app market data and recommend profitable development strategies in this guided project. Gain hands-on experience with Python, data cleaning, and exploratory analysis. Learn more
What We're Reading
The Pudding—Data-Driven Visual Essays: Explore interactive visual essays that use data storytelling to explain complex cultural topics in an engaging way.
2025 Tech Job Market Trends: Discover key trends shaping the 2025 tech job market, from rising AI demand to shifts in hiring and upskilling strategies.
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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.
2025-06-11
Learn how to automate ETL with Airflow, compare cloud providers hands-on, and discover regex, SQL, and engagement tips from the community. Read More
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Learn how to solve business problems with SQL, explore ML-driven pricing strategies, and compare cloud platforms with real-world examples. Read More
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Explore financial data with Nasdaq's API, simplify GitHub workflows, master Python concepts, segment customers with K-means, and more. Read More