Building a network where data drives every insight
An accessible guide to how analytical thinking and data-driven decision making drive competitive advantage.
Known as the "bible" of algorithms, this book covers a wide range of topics—from sorting to advanced graph algorithms, essential for mastering data structures.
End-to-end examples for building, training, and deploying models in Python. Ideal for practitioners.
Modern ML techniques—features, algorithms, back-tests—applied to investment problems.
A comprehensive textbook covering theory and practice of neural networks and deep architectures.
Real-world case studies showing how predictive models influence marketing, healthcare, and more.
The big ideas behind reliable, scalable, and maintainable systems. A must-read for data engineers and architects.
Practical techniques for data wrangling, manipulation, and visualization with pandas.
Dimensional modeling methods to design agile, user-friendly data warehouses and BI systems.
The foundational text on agents learning via reward signals with algorithms and proofs.
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