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Artificial Intelligence: Made Easy w/ Ruby Programming; Learn to Create your * Problem Solving * Algorithms! TODAY! w/ Machine Learning & Data .....
75% of respondents would recommend this to a friend
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Design the MIND of a Robotic Thinker!
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What Stands Out
Product Details
- Teaches how to design the MIND of a Robotic Thinker with clear and consistent information
- Includes a bonus quick-start guide to Learning Ruby in less than a Day
- Covers creating AI bots and the simplicity of the process without the need for advanced math
- Provides great coding skills to learn with topics on solving complicated scheduling problems and analyzing AI algorithms for efficiency
- Explains interpreting a system into logical code for AI, diagnosing a system, and getting an AI agent to solve problems
- Breaks down training into easy-to-understand modules, starting from essentials for beginners
| Publisher | CreateSpace Independent Publishing Platform |
| Publication date | April 10, 2016 |
| Language | English |
| Print length | 150 pages |
| ISBN-10 | 1530826861 |
| ISBN-13 | 978-1530826865 |
| Item Weight | 7.5 ounces (212.63 grams) |
| Dimensions | 6 x 0.34 x 9 inches (15.2 x 0.9 x 22.9 cm) |
Who Should Buy?
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Aspiring Programmers
Individuals looking to learn Ruby and its application in artificial intelligence and problem-solving algorithms.
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Data Enthusiasts
People interested in machine learning and data engineering concepts will benefit from this introductory approach.
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Education Seekers
Students or self-learners seeking structured guidance on integrating Ruby with AI concepts will find value.
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Advanced Developers
Experienced programmers may find the content too basic and lacking in depth for their advanced needs.
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Machine Theory Editorial Review
**** The book *Artificial Intelligence: Made Easy w/ Ruby Programming* has garnered a mixed reception among readers, particularly among those who are new to either programming or artificial intelligence. Many users appreciate the author's ability to introduce complex concepts in an accessible manner, making it a suitable entry point for beginners. Several reviewers noted that the book provides clear explanations of fundamental principles of artificial intelligence using the Ruby programming language. Readers have found the inclusion of practical examples helpful, which allows them to follow along and apply the concepts in real scenarios. Some users emphasized that while the book is easy to understand, having prior knowledge of Ruby is advantageous, as it can streamline the learning process. On the flip side, some criticisms arise regarding the depth of content and the quality of the code examples. A few readers have pointed out that the book may not sufficiently cover more advanced AI concepts, instead offering only basic techniques and a few introductory algorithms. Concerns were also raised about the overall rigor of the material and the coding standards demonstrated within the examples. Despite these criticisms, a segment of the audience believes the book effectively meets its goals for beginners looking to grasp basic AI concepts using Ruby, although Prospective readers are encouraged to preview the book first to ensure it aligns with their expectations. Overall, this book serves as a useful starter guide for novices interested in artificial intelligence and Ruby programming, but advanced users or those seeking in-depth content may want to explore additional resources. **
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Pros
- Accessible introduction to artificial intelligence for beginners.
- Clear explanations and practical examples.
- Well-structured content that is easy to follow.
- Positive reviews from those new to Ruby programming.
Cons
- Lacks depth and rigor in advanced AI concepts.
Product Price History
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HKD 123
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Features & Benefits
- Learn to create problem-solving algorithms with AI using Ruby programming
- Includes a quick-start guide to learning Ruby in less than a day
- No need for advanced math skills or to pay thousands of dollars
- Easy-to-understand modules for beginners to write great code
- Topics such as complicated scheduling, AI algorithm analysis, logical code, AI diagnosis, and problem-solving techniques covered.
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