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1 Foundations Data Algorithms Books Categories
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1 Foundations Data Algorithms Books Categories
1 Foundations Data Algorithms Categories Books List
1 Foundations Data Algorithms Books Categories
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Algorithms in a Nutshell (Paperback)
By:
George T. Heineman
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Data Science and Complex Networks: Real Case Studies with Python (Hardcover)
By:
Guido Caldarelli
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Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow (Paperback)
By:
Hannes Hapke
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Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles (ebook)
By:
Draguna Vrabie
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Artificial Intelligence: A Guide to Intelligent Systems (3rd Edition)
By:
Michael Negnevitsky
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Statistical Inference (Hardcover)
By:
George Casella
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A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning (Foundations and Trends(r) in Machine Learning)
By:
Alborz Geramifard
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Spark: The Definitive Guide: Big Data Processing Made Simple (Kindle Edition)
By:
Bill Chambers
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Kubernetes in Action: Deploying and managing containers and cloud-native applications (Paperback)
By:
Marko Luksa
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Data Management at Scale: Best Practices for Enterprise Architecture (Paperback)
By:
Piethein Strengholt
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The Go Programming Language (Paperback)
By:
Alan A.A. Donovan
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Algorithms (Hardcover)
By:
Robert Sedgewick
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Who's #1? The Science of Rating and Ranking (Hardcover)
By:
Amy N. Langville
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Mathematics for Computer Science (ebook)
By:
Eric Lehman
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Learning Spark: Lightning-Fast Big Data Analysis (Kindle Edition)
By:
Holden Karau
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Jumpstart Snowflake: A Step-by-Step Guide to Modern Cloud Analytics (Kindle Edition)
By:
Dmitry Anoshin
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PyTorch 1.x Reinforcement Learning Cookbook: Over 60 recipes to design, develop, and deploy self-learning AI models using Python (Kindle Edition)
By:
Yuxi (Hayden) Liu
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Flask Web Development: Developing Web Applications with Python (Paperback)
By:
Miguel Grinberg
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Cassandra: The Definitive Guide (Paperback)
By:
Eben Hewitt
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Cloud Native: Using Containers, Functions, and Data to Build Next-Generation Applications (Paperback)
By:
Boris Scholl
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Reinforcement Learning and Dynamic Programming Using Function Approximators (Automation and Control Engineering)
By:
Lucian Buşoniu
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Understanding Computation: From Simple Machines to Impossible Programs (Paperback)
By:
Tom Stuart
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Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale (Paperback)
By:
Valliappa Lakshmanan
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Effective Python: 59 Specific Ways to Write Better Python (Effective Software Development Series)
By:
Brett Slatkin
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Kubeflow for Machine Learning: From Lab to Production (Paperback)
By:
Trevor Grant
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Classic Computer Science Problems in Python (Paperback)
By:
David Kopec
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Test-Driven Development with Python: Obey the Testing Goat: Using Django, Selenium, and JavaScript (Paperback)
By:
Harry Percival
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Deep Reinforcement Learning with Guaranteed Performance: A Lyapunov-Based Approach (Hardcover)
By:
Yinyan Zhang
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From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning (Foundations and Trends(r) in Machine Learning)
By:
Remi Munos
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A Survey on Policy Search for Robotics (Paperback)
By:
Marc Peter Deisenroth
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Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (Paperback)
By:
Foster Provost
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
By:
Richard S. Sutton
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Practical Time Series Analysis: Prediction with Statistics and Machine Learning (Paperback)
By:
Aileen Nielsen
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Head First Go (Paperback)
By:
Jay McGavren
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Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning (Paperback)
By:
Valliappa Lakshmanan
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Markov Decision Processes in Artificial Intelligence: MDPs, Beyond MDPs and Applications (Kindle Edition)
By:
Olivier Sigaud
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Data Pipelines with Apache Airflow (Paperback)
By:
Bas P. Harenslak
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Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale (Paperback)
By:
Neha Narkhede
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Algorithms Illuminated (Part 1): The Basics
By:
Tim Roughgarden
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Effective Python: 90 Specific Ways to Write Better Python (Kindle Edition)
By:
Slatkin Brett
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Graph Algorithms: Practical Examples in Apache Spark & Neo4j (Paperback)
By:
Mark Needham
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Mathematics for Machine Learning: 1st Edition (Kindle Edition)
By:
Marc Peter Deisenroth
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Introduction to Algorithms (Hardcover)
By:
Thomas H. Cormen
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Deep Learning (ebook)
By:
Ian Goodfellow
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Learning Go: An Idiomatic Approach to Real-World Go Programming (Paperback)
By:
Jon Bodner
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Software Engineering at Google: Lessons Learned from Programming Over Time (Paperback)
By:
Titus Winters
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Algorithms for Reinforcement Learning (ebook)
By:
Csaba Szepesvari
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Concrete Mathematics: A Foundation for Computer Science (Hardcover)
By:
Ronald Graham