Sign-In
Cart
15 Math Concepts Every Data Scientist Should Know: Understand and learn how to apply the math behind data science algorithms
Paperback
General ComputersGeneral MathematicsProgramming
ISBN13: 9781837634187
Publisher: Packt Publishing
Published: Aug 16 2024
Pages: 510
Weight: 1.91
Height: 1.03 Width: 7.50 Depth: 9.25
Language: English
Create more effective and powerful data science solutions by learning when, where, and how to apply key math principles that drive most data science algorithms
Key Features:
- Understand key data science algorithms with Python-based examples
- Increase the impact of your data science solutions by learning how to apply existing algorithms
- Take your data science solutions to the next level by learning how to create new algorithms
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description:
Data science combines the power of data with the rigor of scientific methodology, with mathematics providing the tools and frameworks for analysis, algorithm development, and deriving insights. As machine learning algorithms become increasingly complex, a solid grounding in math is crucial for data scientists. David Hoyle, with over 30 years of experience in statistical and mathematical modeling, brings unparalleled industrial expertise to this book, drawing from his work in building predictive models for the world's largest retailers.
Encompassing 15 crucial concepts, this book covers a spectrum of mathematical techniques to help you understand a vast range of data science algorithms and applications. Starting with essential foundational concepts, such as random variables and probability distributions, you'll learn why data varies, and explore matrices and linear algebra to transform that data. Building upon this foundation, the book spans general intermediate concepts, such as model complexity and network analysis, as well as advanced concepts such as kernel-based learning and information theory. Each concept is illustrated with Python code snippets demonstrating their practical application to solve problems.
By the end of the book, you'll have the confidence to apply key mathematical concepts to your data science challenges.
What You Will Learn:
- Master foundational concepts that underpin all data science applications
- Use advanced techniques to elevate your data science proficiency
- Apply data science concepts to solve real-world data science challenges
- Implement the NumPy, SciPy, and scikit-learn concepts in Python
- Build predictive machine learning models with mathematical concepts
- Gain expertise in Bayesian non-parametric methods for advanced probabilistic modeling
- Acquire mathematical skills tailored for time-series and network data types
Who this book is for:
This book is for data scientists, machine learning engineers, and data analysts who already use data science tools and libraries but want to learn more about the underlying math. Whether you're looking to build upon the math you already know, or need insights into when and how to adopt tools and libraries to your data science problem, this book is for you. Organized into essential, general, and selected concepts, this book is for both practitioners just starting out on their data science journey and experienced data scientists.
Table of Contents
- Recap of Mathematical Notation and Terminology
- Random Variables and Probability Distributions
- Matrices and Linear Algebra
- Loss Functions and Optimization
- Probabilistic Modeling
- Time Series and Forecasting
- Hypothesis Testing
- Model Complexity
- Function Decomposition
- Network Analysis
- Dynamical Systems
- Kernel Methods
- Information Theory
- Non-Parametric Bayesian Methods
- Random Matrices
Also from
Hoyle, David
Also in
Programming
Interactive Theorem Proving and Program Development: Coq'art: The Calculus of Inductive Constructions
Castéran, Pierre
Bertot, Yves
Hardcover
The Legend of Zelda(tm) Tears of the Kingdom - The Complete Official Guide: Collector's Edition
Piggyback
Hardcover
Python Crash Course, 3rd Edition: A Hands-On, Project-Based Introduction to Programming
Matthes, Eric
Paperback
The Legend of Zelda(tm) Tears of the Kingdom - The Complete Official Guide: Standard Edition
Piggyback
Paperback
Crisis Engineering: Time-Tested Tools for Turning Chaos Into Clarity
Dickerson, Mikey
Nitze, Marina
Weaver, Matthew
Paperback
Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations
Kim, Gene
Forsgren Phd, Nicole
Humble, Jez
Paperback
Embedded Systems with ARM Cortex-M Microcontrollers in Assembly Language and C: Fourth Edition
Zhu, Yifeng
Paperback
Fundamentals of Software Architecture: A Modern Engineering Approach
Ford, Neal
Richards, Mark
Paperback
Make: Electronics: Learning by Discovery: A Hands-On Primer for the New Electronics Enthusiast
Platt, Charles
Paperback
The Manager's Path: A Guide for Tech Leaders Navigating Growth and Change
Fournier, Camille
Paperback
Vibe Coding: Building Production-Grade Software with Genai, Chat, Agents, and Beyond
Yegge, Steve
Kim, Gene
Paperback
AI Projects with Raspberry Pi: High-Performance Artificial Intelligence for Robotics, Security, Home Automation, and Vision
Hattersley, Lucy
Jepson, Brian
Paperback
Site Reliability Engineering: How Google Runs Production Systems
Leng, Christof
Beyer, Betsy
Jones, Chris
Paperback
I Have an App Idea: The Essential Guide to Building an App Without Tech Skills
Spann, Amanda
Paperback
The Devops Handbook, 2nd Edition: How to Create World-Class Agility, Reliability, & Security in Technology Organizations
Humble, Jez
Debois, Patrick
Kim, Gene
Paperback
The Return on AI: From Promise to Profit in the Age of Intelligent Business
Sawhney, Mohanbir
Mittal, Ashwin
Paperback
The Staff Engineer's Path: A Guide for Individual Contributors Navigating Growth and Change
Reilly, Tanya
Paperback
The Developer's Guide to AI: A Field Guide for the Working Developer
Reghunadh, Jerry M.
Thompson, Danny
Orshalick, Jacob
Paperback
Evals for AI Engineers: Systematically Measuring and Improving AI Applications
Shankar, Shreya
Husain, Hamel
Paperback
Building Applications with AI Agents: Designing and Implementing Multiagent Systems
Albada, Michael
Paperback
Software Architecture: The Hard Parts: Modern Trade-Off Analyses for Distributed Architectures
Sadalage, Pramod
Ford, Neal
Richards, Mark
Paperback
Observability Engineering: Achieving Production Excellence
Miranda, George
Majors, Charity
Fong-Jones, Liz
Paperback
Cracking the Coding Interview: 189 Programming Questions and Solutions
McDowell, Gayle Laakmann
Paperback
Forecasting: Principles and Practice, the Pythonic Way
Hyndman, Rob J.
Athanasopoulos, George
Paperback
Building Safer Technology: A Field Guide to Failing Well
Zunger, Yonatan
Coles, Neil
Kissner, Lea
Paperback
Learning Web Design: A Beginner's Guide to Html, Css, Javascript, and Web Images
Robbins, Jennifer
Paperback
The New AI Cold War: Liberty vs. Tyranny in the Age of Machine Empires
Maginnis, Ltc Robert L.
Paperback
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
Occupytheweb
Paperback
The Pragmatic Programmer: Your Journey to Mastery, 20th Anniversary Edition
Thomas, David
Hunt, Andrew
Hardcover
SQL QuickStart Guide: The Simplified Beginner's Guide to Managing, Analyzing, and Manipulating Data With SQL
Shields, Walter
Hardcover
A Human's Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control
Hosanagar, Kartik
Paperback
Grokking Algorithms, Second Edition: An Illustrated Guide for Programmers and Other Curious People
Bhargava, Aditya Y.
Paperback
Building Resilient Distributed Systems: Patterns and Practices for Stable Software
Newman, Sam
Paperback
Learning Domain-Driven Design: Aligning Software Architecture and Business Strategy
Khononov, Vlad
Paperback
Generative AI Design Patterns: Solutions to Common Challenges When Building Genai Agents and Applications
Lakshmanan, Valliappa
Hapke, Hannes
Paperback
Concrete Mathematics: A Foundation for Computer Science
Patashnik, Oren
Knuth, Donald
Graham, Ronald
Hardcover
The Official Raspberry Pi Handbook 2026: Astounding Projects with Raspberry Pi Computers
Makers of Raspberry Pi Official Magazine, The
Paperback
Head First Design Patterns: Building Extensible and Maintainable Object-Oriented Software
Freeman, Eric
Robson, Elisabeth
Paperback
The Software Architect Elevator: Redefining the Architect's Role in the Digital Enterprise
Hohpe, Gregor
Paperback
Signals & Levers: Systems Thinking Tools to Unblock Software Delivery
Tosi, Joel
Hendrickson, Elisabeth
Paperback
Java in a Nutshell: A Desktop Quick Reference
Clark, Jason R.
Flanagan, David
Evans, Benjamin J.
Paperback
Learning Generative AI Tools for Excel: Speed Up Your Everyday Tasks with Microsoft Excel, Copilot, Chatgpt, and Beyond
Duca, Angelica Lo
Paperback
Building AI-Powered Products: The Essential Guide to AI and Genai Product Management
Nika, Marily
Paperback
AI Agents with MCP: Model Context Protocol for Building Clients, Servers, and End-To-End Agents
Stratis, Kyle
Paperback
Arduino Programming for Beginners: A Comprehensive Beginner's Guide to Learn the Realms of Arduino Programming from A-Z
Protosmith, Ada
Paperback
Build an AI Agent (from Scratch): Agents That Reason, Plan, and ACT Autonomously
Hur, Jungjun
Song, Younghee
Paperback
Inteligencia Artificial Con Python: Sistemas de aprendizaje, Machine Learning y Deep Learning explicados de forma clara y práctica.
Selles Rodenas, Juan Ignacio
Paperback
Frictionless: 7 Steps to Remove Barriers, Unlock Value, and Outpace Your Competition in the AI Era
Forsgren, Nicole
Noda, Abi
Paperback
Debugging: The 9 Indispensable Rules for Finding Even the Most Elusive Software and Hardware Problems
Agans, David J.
Paperback
Software Engineering at Google: Lessons Learned from Programming Over Time
Manshreck, Tom
Wright, Hyrum
Winters, Titus
Paperback
Living a Jewish Life, Revised and Updated: Jewish Traditions, Customs, and Values for Today's Families
Diamant, Anita
Cooper, Howard
Paperback
Learning Php, MySQL & JavaScript: A Step-By-Step Guide to Creating Dynamic Websites
Nixon, Robin
Paperback
The Multiplier Mindset: How to Move from Senior Engineer to Tech Leader in the Age of AI
Ojstersek, Gregor
Paperback
Programming Massively Parallel Processors: A Hands-On Approach
El Hajj, Izzat
Hwu, Wen-Mei W.
Kirk, David B.
Paperback
Python Programming for Young Coders: A Hands-On, Project-Based Introduction to Coding for Beginners, Kids, and Teens
Pandey, Anand
Paperback
Certified Associate in Project Management (Capm)(R) Exam Official Cert Guide
Kanabar, Vijay
Thomas, Arthur
Lechler, Thomas
Paperback
Creación de Aplicaciones Con Agentes de Ia (Spanish Edition): Diseño E Implementación de Sistemas Multiagente
Albada, Michael
Paperback
Adobe Photoshop, 2nd Edition: A Complete Course and Compendium of Features
Laskevitch, Stephen
Paperback
Computer Science from Scratch: Building Interpreters, Art, Emulators and ML in Python
Kopec, David
Paperback
Electronic Music and Sound Design - Theory and Practice with Max 9 - Volume 1 (Fifth Edition)
Cipriani, Alessandro
Maurizio, Giri
Paperback
Kubernetes in Action, Second Edition: Deploying and Managing Containers and Cloud-Native Applications
Luksa, Marko
Conner, Kevin
Paperback
The Book of Debugging: A Systematic Workflow for Finding and Fixing Bugs
Kuhlmann, Johannes
Paperback