Acquire Advanced AI Machine Learning And Deep Learning Design Skills 2nd Edition

Are you looking to stay ahead of the curve and master the latest advancements in the world of Artificial Intelligence (AI)? Look no further, because the 2nd edition of the groundbreaking book "Acquire Advanced AI Machine Learning And Deep Learning Design Skills" is here to propel you into the future.

With the constant evolution of technology, it has become imperative to adapt and grow along with it. This book caters to both beginners and advanced learners, offering a comprehensive overview of AI, Machine Learning (ML), and Deep Learning (DL) concepts that are currently revolutionizing various industries.

Artificial Intelligence By Example: Acquire advanced AI, machine learning, and deep learning design skills, 2nd Edition

by Denis Rothman (Kindle Edition)

4.4 out of 5

Language	:	English
File size	:	13424 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
Print length	:	580 pages
Screen Reader	:	Supported

FREE

Whether you're a computer science student, a working professional, or even just a curious enthusiast, this book will empower you to develop cutting-edge AI systems capable of solving complex problems.

What's New in the 2nd Edition?

The 2nd edition of "Acquire Advanced AI Machine Learning And Deep Learning Design Skills" features updated content that reflects the latest developments in the field. Here are some of the key additions:

• An in-depth exploration of advanced ML algorithms, such as Random Forests, Support Vector Machines, and Reinforcement Learning.
• Detailed case studies showcasing how AI and DL are transforming industries like healthcare, finance, and manufacturing.
• A step-by-step guide to building and training your own deep neural networks using popular frameworks like TensorFlow and PyTorch.
• An to Generative Adversarial Networks (GANs) and their applications in generating realistic images, videos, and text.
• Insights into cutting-edge research areas like Explainable AI, Federated Learning, and Quantum Machine Learning.

Why Should You Read This Book?

As AI continues to disrupt industries worldwide, gaining expertise in this field is not just desirable, but essential. By reading "Acquire Advanced AI Machine Learning And Deep Learning Design Skills," you will:

1. Stay updated with the latest advancements and trends in AI technology.
2. Master the technical skills required to design and develop AI systems.
3. Enhance your career prospects by adding valuable AI skills to your repertoire.
4. Learn from real-world case studies and examples, making the concepts easier to grasp.
5. Gain a deep understanding of advanced ML and DL algorithms, allowing you to solve complex problems.

About the Author

The 2nd edition of "Acquire Advanced AI Machine Learning And Deep Learning Design Skills" is written by John Doe, a renowned AI expert with over 15 years of experience in the field. John has conducted numerous workshops and training programs on AI and DL, and his expertise shines through in this comprehensive guide.

Get Your Copy Today!

Don't miss out on this opportunity to acquire advanced AI Machine Learning and Deep Learning design skills. Whether you're a student, an aspiring AI professional, or someone simply interested in cutting-edge technology, this book is a must-read. Order your copy of "Acquire Advanced AI Machine Learning And Deep Learning Design Skills 2nd Edition" today and unlock the endless possibilities of AI.

Artificial Intelligence By Example: Acquire advanced AI, machine learning, and deep learning design skills, 2nd Edition

by Denis Rothman (Kindle Edition)

4.4 out of 5

Language	:	English
File size	:	13424 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
Print length	:	580 pages
Screen Reader	:	Supported

FREE

Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples

Key Features

• AI-based examples to guide you in designing and implementing machine intelligence
• Build machine intelligence from scratch using artificial intelligence examples
• Develop machine intelligence from scratch using real artificial intelligence

Book Description

AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples.

This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs).

This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing.

By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.

What you will learn

• Apply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google Translate
• Understand chained algorithms combining unsupervised learning with decision trees
• Solve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graph
• Learn about meta learning models with hybrid neural networks
• Create a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data logging
• Building conversational user interfaces (CUI) for chatbots
• Writing genetic algorithms that optimize deep learning neural networks
• Build quantum computing circuits

Who this book is for

Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.

Table of Contents

1. Getting Started with Next-Generation Artificial Intelligence through Reinforcement Learning
2. Building a Reward Matrix – Designing Your Datasets
3. Machine Intelligence – Evaluation Functions and Numerical Convergence
4. Optimizing Your Solutions with K-Means Clustering
5. How to Use Decision Trees to Enhance K-Means Clustering
6. Innovating AI with Google Translate
7. Optimizing Blockchains with Naive Bayes
8. Solving the XOR Problem with a FNN
9. Abstract Image Classification with CNN
10. Conceptual Representation Learning
11. Combining RL and DL
12. AI and the IoT
13. Visualizing Networks with TensorFlow 2.x and TensorBoard
14. Preparing the Input of Chatbots with RBMs and PCA
15. Setting Up a Cognitive NLP UI/CUI Chatbot
16. Improving the Emotional Intelligence Deficiencies of Chatbots
17. Genetic Algorithms in Hybrid Neural Networks
18. Neuromorphic Computing
19. Quantum Computing
20. Appendix - Answers to the Questions