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Beschreibung

We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics.

The updated second edition of this book describes the intuition behind these innovations without jargon or complexity. Python-proficient programmers, software engineering professionals, and computer science majors will be able to reimplement these breakthroughs on their own and reason about them with a level of sophistication that rivals some of the best developers in the field.

  • • Learn the mathematics behind machine learning jargon • Examine the foundations of machine learning and neural networks • Manage problems that arise as you begin to make networks deeper • Build neural networks that analyze complex images • Perform effective dimensionality reduction using autoencoders • Dive deep into sequence analysis to examine language • Explore methods in interpreting complex machine learning models • Gain theoretical and practical knowledge on generative modeling • Understand the fundamentals of reinforcement learning

We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics.

The updated second edition of this book describes the intuition behind these innovations without jargon or complexity. Python-proficient programmers, software engineering professionals, and computer science majors will be able to reimplement these breakthroughs on their own and reason about them with a level of sophistication that rivals some of the best developers in the field.

  • • Learn the mathematics behind machine learning jargon • Examine the foundations of machine learning and neural networks • Manage problems that arise as you begin to make networks deeper • Build neural networks that analyze complex images • Perform effective dimensionality reduction using autoencoders • Dive deep into sequence analysis to examine language • Explore methods in interpreting complex machine learning models • Gain theoretical and practical knowledge on generative modeling • Understand the fundamentals of reinforcement learning
Über den Autor

Nithin Buduma is one of the first machine learning engineers at [...], a start-up based out of Harvard and Stanford working to help healthcare companies leverage their massive datasets.

Nikhil Buduma is the cofounder and chief scientist of Remedy, a San Francisco-based company that is building a new system for data-driven primary healthcare. At the age of 16, he managed a drug discovery laboratory at San Jose State University and developed novel low-cost screening methodologies for resource-constrained communities. By the age of 19, he was a two-time gold medalist at the International Biology Olympiad. He later attended MIT, where he focused on developing large-scale data systems to impact healthcare delivery, mental health, and medical research. At MIT, he cofounded Lean On Me, a national nonprofit organization that provides an anonymous text hotline to enable effective peer support on college campus and leverages data to effect positive mental health and wellness outcomes. Today, Nikhil spends his free time investing in hard technology and data companies through his venture fund, Q Venture Partners, and managing a data analytics team for the Milwaukee Brewers baseball team.

Joe Papa has over 25 years experience in research & development and is the founder of [...]. He holds an MSEE and has led AI Research teams with PyTorch at Booz Allen and Perspecta Labs. Joe has mentored hundreds of Data Scientists and has taught 6,000+ students across the world on Udemy.

Details
Erscheinungsjahr: 2022
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9781492082187
ISBN-10: 149208218X
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Buduma, Nithin
Buduma, Nikhil
Papa, Joe
Auflage: 2nd edition
Hersteller: O'Reilly Media
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 233 x 180 x 25 mm
Von/Mit: Nithin Buduma (u. a.)
Erscheinungsdatum: 30.06.2022
Gewicht: 0,682 kg
Artikel-ID: 119699145