Machine Learning Theory

Whether you're new to the world of programming and are looking for clarity on what direction to take, or you're simply curious about what machine learning, AI, and big data has in store for the future and want to prepare for it, this guide makes it easy to actually understand implement machine learning and data analytics effectively.

Today, 91 percent of Python programmers are not quite prepared. This is what the IT companies say, according to a recent survey. Do you know why? The reason is that they have no notions of artificial intelligence. So, future programmers will no longer find work without having knowledge of this particular field that is constantly evolving.

Even though you have no prior knowledge about AI, this guide will let you explore the world of AI and how you can leverage the technology to improve decision-making, enhance efficiency, and boost sales—all while reaching out to more customers.

Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks, procedural reuse design pattern for CNN architectures, models for mobile and IoT devices, assembling large-scale model deployments, optimizing hyperparameter tuning, and migrating a model to a production environment.

Yes, you can succeed in an AI-driven world by unleashing your potential in machine learning! A working knowledge of AI and ML is no longer a “nice-to-have” but an “essential” in today's job market. But what if you feel lost amid the tech jargon? What if terms like “algorithms”, “neural networks”, or “data preprocessing” sound like a foreign language to you?

Machine learning is a use of artificial intelligence (AI) that gives software the capacity to naturally learn and improve without being unequivocally modified. Machine learning centers around the improvement of computer programs that can get to data and use it to learn for themselves. The way toward learning starts with perceptions or data - for example, models, direct understanding, or guidance, so as to search for designs in data and settle on better choices later, depending on the models that we give.

This boxed set includes two titles: Book 1: Machine Learning - This book is an introduction to basic machine learning and artificial intelligence. It gives you a list of applications, and also a few examples of the different types of machine learning. Book 2: Neural Networks - Neural networks are used to model complex patterns for prediction and simulation. It uses the processing pattern used by brain neurons to achieve this. Neural Networks are good at processing complex, non-linear relationships and are used in forecasting, image processing, and character recognition.

AI: A phrase that intrigues some, confuses many, and brings fear to others. Whether you're a teacher looking to stay ahead or a parent curious about AI's impact on your child's education, you have questions. Can AI enhance teaching without overwhelming you? Can it tailor learning experiences? Can it be ethical and protect student data? If these concerns resonate, you've found the right book.

This book demonstrates how nonscientific ideas have been encoded deep into our technological infrastructure. Offering a rigorous, fresh perspective on how technology has brought us to this place, Rage Inside the Machine challenges the long-held assumption that technology is an apolitical and amoral force.

If you are an active user of statistics to examine trends in your business, then using machine learning is your next best step. It uses advanced predictive algorithms of different aspects of your business to help you make the best possible decision. If you are new to business or thinking about starting a new business, this will also help you lay the groundwork and get ahead of others who are at your same level. It is a fascinating listen recommended for everyone, as it also looks at how machine learning and AI can impact society as a whole.

Artificial intelligence is a growing field with many possibilities extending in many directions. Artificial intelligence encompasses many terms you may have heard and terms that we will be covering in this book like deep learning, neural networks, and machine learning. Sometimes we hear doubts out there that artificial intelligence will never be as good as humans are at navigating the choices and actions of other humans, but that is not always the case.

If you are a technical recruiter who wants to keep your skills up to date in the growing area of artificial intelligence (AI) and machine learning (ML), this is the essential resource for you. In this book, you will learn the fundamentals of AI/ML, from the basics to more advanced. You will also find simple screening questions and conversations that can be used for matching your candidate's resumes to AI/ML job descriptions.

Ever wondered how your favorite apps predict your preferences or how self-driving cars navigate the roads? Welcome to the world of Machine Learning, where these wonders come to life! "Introduction to Machine Learning" is your ticket to unraveling the mysteries of this groundbreaking technology without the need for a PhD!

Dive into the fascinating world of how both your brain and AI learn through supervised learning! In this engaging and accessible book, neuroscientist Dr. Tursun Alkam takes you on a journey to explore the incredible learning capabilities of the human brain and the revolutionary world of Artificial Intelligence.

Discover how to leverage AI and transform your productivity and creativity—even if you're starting from scratch! Feeling overwhelmed by terms like “Machine Learning” and “ChatGPT”? You’re not alone. Many adults feel left behind by tech’s rapid rise—but you don’t need to be a coder to harness AI’s power.

In our highly competitive world of today, we need all the edge we can to get ahead of our competitors. For a long time, companies have focused on spending more on marketing and advertisement, ignoring the powerful asset they had at their disposal: data. Although this isn't the case anymore for large companies, smaller businesses are still in the dark about this, and you can use this asset to your advantage. This bundle will show you how.

Generative AI for Beginners Simplified is your ultimate gateway into the exciting world of artificial intelligence and machine learning. This comprehensive guide is specially designed for beginners, breaking down complex concepts into easy-to-understand lessons, practical exercises, and real-world projects. Whether you’re completely new to AI or looking to refresh your skills, this book provides you with a step-by-step roadmap to mastering generative AI and unlocking your creative potential.

What is artificial intelligence (AI)? What can it do and how is it created? In this highly accessible guide to the subject, Richard Urwin explains how AI came about and how it has developed over the years through the construction of ever more sophisticated computer programs. Along the way, you will discover numerous intriguing examples of how scientists have progressed the development of AI, as well as finding out how research into brain function is continually influencing this dynamic field.

You’re not imagining it—education feels harder than ever. The paperwork is endless. Student engagement rollercoasters. And the tech? It keeps evolving before you’ve even had a chance to breathe. But what if, instead of scrambling to keep up, you could leap ahead—without burning out? Across classrooms, school offices, and kitchen tables, one thing is becoming clear: AI isn’t here to replace you. It’s here to help you do what you do best. It’s a tool to reduce your workload, personalize learning, and reignite the spark that brought you to education in the first place.

Dieses Hörbuch ist so aufgebaut, dass Ihnen die Inhalte im Rahmen der geschichtlichen Entwicklung der KI vermittelt werden. Aus diesem Grund beginnt unsere Reise mit dem Punkt "Einführung und geschichtlicher Hintergrund der KI". Im zweiten Abschnitt greifen wir zunächst die anfänglichen Techniken der KI auf. Sie lernen dabei die Konzepte und berühmte Beispielsysteme kennen, die diese frühe Phase der Euphorie auslösten.