Data Science from Scratch
by Joel Grus
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you’ll learn how many of the most fundamental data science tools and algorithms work by imple…
38 AI-mapped connections to other books on Hikara
Books that ECHO Data Science from Scratch
Reads that harmonize with similar ideas, themes, or philosophies.
Machine Learning for Tabular Data
Mark Ryan, Luca Massaron
Fundamentals for Self-Taught Programmers
Jasmine Greenaway
Practical Statistics for Data Scientists
Peter Bruce, Andrew Bruce, Peter Gedeck
Modern Data Analytics in Excel
George Mount
Essential Math for Data Science
Thomas Nield
Think Like a Data Scientist
Brian Godsey
The Linux Command Line, 3rd Edition
William Shotts
Python for Data Analysis
Wes McKinney
The Self-Taught Cloud Computing Engineer
Dr. Logan Song
Build a Career in Data Science
Emily Robinson, Jacqueline Nolis
Books that BRIDGE from Data Science from Scratch
Cross-domain reads that transfer ideas into new fields.
Machine Learning Algorithms in Depth
Vadim Smolyakov
Practical MLOps
Noah Gift, Alfredo Deza
Grokking Algorithms, Second Edition
Aditya Y Bhargava
Kubernetes in Action, Second Edition
Marko Lukša, Kevin Conner
Docker Deep Dive
Nigel Poulton
Fundamentals of Data Engineering
Joe Reis, Matt Housley
Learning Spark
Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee
The Data Warehouse Toolkit
Ralph Kimball, Margy Ross
The Personal MBA
Josh Kaufman
Engineering MLOps
Emmanuel Raj
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