Book picks similar to
Problem Solving in Data Structures & Algorithms Using Python: Programming Interview Guide by Hemant Jain
algorithms
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software_engineer<br/>ing_books
interview-programming
Stronger: Courage, Hope, and Humor in My Life with John McCain
Cindy Mccain - 2021
Ace the Technical Pilot Interview
Gary V. Bristow - 2002
This practical study tool asks the right questions so you'll know the right answers. It's a must-have, one-stop resource for all pilots, regardless of aircraft type, performance, or global region.Ace the Technical Pilot Interview, Second Edition helps you: Review the material most likely to be asked on your interview Practice with 1000+ exam-style questions--complete with answers Learn about the latest technologies, including CPDLC (Controller Pilot Data Link Communications) and ADS (Automatic Dependent Surveillance) Focus your study on what you need to know COVERAGE INCLUDES: Aerodynamics * Engines * Jet and propeller aircraft differences * Navigation * Atmosphere and speed * Aircraft instruments and systems * Performance and flight planning * Meteorology and weather recognition * Flight operations and technique * Human performance * Type-specific questions
Ejb 3 in Action
Debu Panda - 2007
This book builds on the contributions and strengths of seminal technologies like Spring, Hibernate, and TopLink.EJB 3 is the most important innovation introduced in Java EE 5.0. EJB 3 simplifies enterprise development, abandoning the complex EJB 2.x model in favor of a lightweight POJO framework. The new API represents a fresh perspective on EJB without sacrificing the mission of enabling business application developers to create robust, scalable, standards-based solutions.EJB 3 in Action is a fast-paced tutorial, geared toward helping you learn EJB 3 and the Java Persistence API quickly and easily. For newcomers to EJB, this book provides a solid foundation in EJB. For the developer moving to EJB 3 from EJB 2, this book addresses the changes both in the EJB API and in the way the developer should approach EJB and persistence.
Designing with the Mind in Mind: Simple Guide to Understanding User Interface Design Rules
Jeff Johnson - 2010
But as the field evolves, designers enter the field from many disciplines. Practitioners today have enough experience in UI design that they have been exposed to design rules, but it is essential that they understand the psychology behind the rules in order to effectively apply them. In "Designing with the Mind in Mind," Jeff Johnson, author of the best selling "GUI Bloopers," provides designers with just enough background in perceptual and cognitive psychology that UI design guidelines make intuitive sense rather than being just a list of rules to follow. * The first practical, all-in-one source for practitioners on user interface design rules and why, when and how to apply them.* Provides just enough background into the reasoning behind interface design rules that practitioners can make informed decisions in every project.* Gives practitioners the insight they need to make educated design decisions when confronted with tradeoffs, including competing design rules, time constrictions, or limited resources.
Machine Learning for Absolute Beginners
Oliver Theobald - 2017
The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors
