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10 Best Books to Teach You About Artificial Intelligence in 2024 10 Best Books to Teach You About Artificial Intelligence in 2024
Are you looking into getting into AI? In addition to conferences, meetups, and other in-person events, there are a plethora of... 10 Best Books to Teach You About Artificial Intelligence in 2024

Are you looking into getting into AI? In addition to conferences, meetups, and other in-person events, there are a plethora of artificial intelligence books out there that can give you insight into a wide range of fields. We’ve curated a list of some of our favorite artificial intelligence books below, be sure to check them out!

In-Person and Virtual Conference

September 5th to 6th, 2024 – London

Featuring 200 hours of content, 90 thought leaders and experts, and 40+ workshops and training sessions, Europe 2024 will keep you up-to-date with the latest topics and tools in everything from machine learning to generative AI and more.

 

Get Started with AI with These Artificial Intelligence Books!

Hands-On Data Analysis with Pandas – Second Edition: A Python Data Science Handbook for Data Collection, Wrangling, Analysis, and Visualization

By Stefanie Molin

Using real-world datasets, you’ll learn how to analyze data, get started with machine learning, and become familiar with Python libraries like pandas, NumPy, matplotlib, seaborn, and scikit-learn. It also covers topics like data wrangling, conducting exploratory data analysis, anomaly detection, and more. 

Effective Pandas: Patterns for Data Manipulation

By Matt Harrison 

Dive into years of experience with and knowledge of Pandas condensed into an accessible format and find all the information you need to write good Pandas code in one place. 

Quick Start Guide to Large Language Models

By Sinan Ozdemir

Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems.

Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, hands-on exercises, and more. Along the way, he shares insights into LLMs’ inner workings to help you optimize model choice, data formats, parameters, and performance. You’ll find even more resources on the companion website, including sample datasets and code for working with open- and closed-source LLMs such as those from OpenAI (GPT-4 and ChatGPT), Google (BERT, T5, and Bard), EleutherAI (GPT-J and GPT-Neo), Cohere (the Command family), and Meta (BART and the LLaMA family).

Weapons of Math Destruction

By Cathy O’Neil, PhD

Increasingly algorithms are at the helm of the decisions that affect everyday life, from health insurance or schooling. In this book, Cathy O’Neil examines how the unregulated nature of these algorithms and the tendency to reinforce discrimination have a tangible detrimental effect on society. 

The Algorithm

By Hilke Schellmann

 The Algorithm takes you on a journey to discover how AI has encroached on the world of work. Relying on the first-hand accounts of job applicants and employees, her own experience with the AI-based tools used for hiring, and the algorithms used to build profiles out of our online activity, Schellmann reveals the reality of the effect of AI on the work and the job market. 

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Probably Overthinking It 

By Allen Downey, PhD

In this introduction to statistical thinking, you’ll find real data and real examples with real consequences from a variety of fields. It examines common pitfalls—like the base rate fallacy, length-biased sampling, and Simpson’s paradox—and elucidates what happens when data is interpreted correctly and what happens when it isn’t. 

Deep Learning Illustrated

By Dr. Jon Krohn with Grant Beyleveld, Aglaé Bassens 

In Deep Learning Illustrated you’ll discover an intuitive and complete introduction to Deep Learning’s techniques. With full-color illustrations and approachable code, you’ll find building deep learning models less complex than you thought and fun!

Modern Generative AI with ChatGPT and OpenAI Models

By Valentina Alto

Get under the hood of Large Language Models and examine their inner workings with this book. You’ll explore the field of generative AI, explore ChatGPT use cases, and OpenAI models’ API. Equip yourself with the knowledge and skills to use generative AI, ChatGPT, and OpenAI models’ API. 

Low-Code AI

By Gwendolyn P Stripling and Michael Abel 

This is a hands-on guide to three ways to learn machine learning and deep learning concepts: custom code using Keras and scikit-learn, low-code utilizing BigQuery ML, and no-code ML utilizing AutoML. Using practical examples featuring real-world datasets, you’ll build a strong foundation in machine learning and deep learning. 

The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R

by Colleen M. Farrelly and Yaé Ulrich Gaba 

Understand the interaction between machine learning and the geometry of data structures through numerous case studies from a wide range of industries, from linguistics to medicine. With accessible explanations of the math underpinning algorithms, this book offers a comprehensive examination of the ways geometry influences the algorithms behind data analysis.

In-Person & Virtual Data Science Conference

October 29th-31st, 2024 – Burlingame, CA

Join us for 300+ hours of expert-led content, featuring hands-on, immersive training sessions, workshops, tutorials, and talks on cutting-edge AI tools and techniques, including our first-ever track devoted to AI Robotics!

 

Tell me more!

Interested in hearing from some of these authors of artificial intelligence books? Many of them will be speaking at ODSC East this month. Find out more on our agenda and get your pass here!

Bonus Episode!

All of the above artificial intelligence books are firmly grounded in reality, but sometimes it’s fun to take a dive into the speculative. Check out a few of our favorite speculative fiction books below. 

The Metamorphosis of Prime Intellect

By Roger Williams 

What are the consequences of making an AI that’s as powerful as a god? In the Metamorphosis of Prime Intellect, Roger Williams integrates this question and examines what happens when humans are made immortal and have their every desire fulfilled. 

Walkaway

By Cory Doctorow

When the necessities of life can be printed by a computer, what’s the point of society? That’s the question that motivates Hubert Vernon Rudolph Clayton Irving Wilson Alva Anton Jeff Harley Timothy Curtis Cleveland Cecil Ollie Edmund Eli Wiley Marvin Ellis Espinoza  (aka Hubert, Etc) to join the walkaways and abandon formal society. But when the walkaways discover a way to defeat death, society might not let the walkaways go after all. 

Ancillary Justice (Imperial Radch, 1)

By Ann Leckie

The Justice of Toren was once an AI-powered starship with thousands of soldiers linked by the AI. Now, she is Breq, a single unit in search of the answers to her questions and a resolution to her vengeance. 

Altered Carbon (Takeshi Kovacs)

By Richard K. Morgan 

In this New York Times bestseller, humanity spread out across the stars and conquered death, but is still divided by class, religion, and race. Takeshi Kovacs, an ex-UN envoy, has been resleeved against his will to get to the bottom of a far-reaching conspiracy in what was once San Francisco. 

The Murderbot Diaries

By Martha Wells

All Murderbot wants is to be left alone, but if it’s going to keep the fact it’s hacked its governor module and continue watching its dramas, Murderbot is going to have to fulfill its contract and keep the scientists safe in a hostile world. 

ODSC Team

ODSC Team

ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.

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