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Generative AI from Beginner to Paid Professional, Part 2

Generative AI from Beginner to Paid Professional, Part 2 PDF Author: Bolakale Aremu
Publisher: AB Publisher LLC
ISBN:
Category : Computers
Languages : en
Pages : 169

Book Description
Unlock the Future of Generative AI and Skyrocket Your Career. This book is your comprehensive roadmap from grasping the fundamentals of AI to mastering the tools and techniques that will set you apart in today’s AI-driven world. Perfect for anyone serious about a career in AI, this book bridges the gap between knowledge and action, giving you the tools to earn, build, and innovate with generative AI technologies. Whether you’re building your first AI project or refining your professional skills, this is the guide you’ve been waiting for. Packed with hands-on projects and practical exercises, this book empowers you to build and launch your very own generative AI solutions. By the end, you’ll not only be equipped with in-demand AI skills but also be prepared to launch your AI projects in the real world. Welcome to Generative AI from Beginner to Paid Professional, Part 2: Master Prompt Design, Gemini Multimodal in Vertex AI Studio, LangChain, Launching & Deploying Generative AI Projects. In Part 2 of this transformative guide, you'll delve deep into powerful AI frameworks and cutting-edge technologies, including Gemini Multimodal, Vertex AI Studio, and LangChain, gaining the expertise needed to design custom AI solutions and deploy scalable AI projects. Whether you’re an aspiring professional or a seasoned developer, this book is your step-by-step companion to navigating the evolving landscape of generative AI. What You’ll Learn: 1. Master Prompt Design: Craft perfect prompts that make your AI work for you, no matter the use case. 2. Gemini Multimodal & Vertex AI Studio: Learn to integrate multimodal models into your AI pipeline, revolutionizing how you build intelligent systems that understand and generate both text and images. 3. LangChain for Real-World AI Projects: Leverage LangChain to create robust, API-powered workflows that bring your AI projects to life. 4. Launching & Deploying AI Projects: From conceptualization to deployment, turn your AI ideas into real-world applications with proven strategies.

Generative AI from Beginner to Paid Professional, Part 2

Generative AI from Beginner to Paid Professional, Part 2 PDF Author: Bolakale Aremu
Publisher: AB Publisher LLC
ISBN:
Category : Computers
Languages : en
Pages : 169

Book Description
Unlock the Future of Generative AI and Skyrocket Your Career. This book is your comprehensive roadmap from grasping the fundamentals of AI to mastering the tools and techniques that will set you apart in today’s AI-driven world. Perfect for anyone serious about a career in AI, this book bridges the gap between knowledge and action, giving you the tools to earn, build, and innovate with generative AI technologies. Whether you’re building your first AI project or refining your professional skills, this is the guide you’ve been waiting for. Packed with hands-on projects and practical exercises, this book empowers you to build and launch your very own generative AI solutions. By the end, you’ll not only be equipped with in-demand AI skills but also be prepared to launch your AI projects in the real world. Welcome to Generative AI from Beginner to Paid Professional, Part 2: Master Prompt Design, Gemini Multimodal in Vertex AI Studio, LangChain, Launching & Deploying Generative AI Projects. In Part 2 of this transformative guide, you'll delve deep into powerful AI frameworks and cutting-edge technologies, including Gemini Multimodal, Vertex AI Studio, and LangChain, gaining the expertise needed to design custom AI solutions and deploy scalable AI projects. Whether you’re an aspiring professional or a seasoned developer, this book is your step-by-step companion to navigating the evolving landscape of generative AI. What You’ll Learn: 1. Master Prompt Design: Craft perfect prompts that make your AI work for you, no matter the use case. 2. Gemini Multimodal & Vertex AI Studio: Learn to integrate multimodal models into your AI pipeline, revolutionizing how you build intelligent systems that understand and generate both text and images. 3. LangChain for Real-World AI Projects: Leverage LangChain to create robust, API-powered workflows that bring your AI projects to life. 4. Launching & Deploying AI Projects: From conceptualization to deployment, turn your AI ideas into real-world applications with proven strategies.

Generative AI from Beginner to Paid Professional, Part 1

Generative AI from Beginner to Paid Professional, Part 1 PDF Author: Bolakale Aremu
Publisher: AB Publisher LLC
ISBN:
Category : Computers
Languages : en
Pages : 43

Book Description
Unlock the Power of Generative AI and Accelerate Your Journey from Beginner to Paid Professional. Are you eager to break into the world of Generative AI but unsure where to start? This step-by-step series is designed for anyone looking to quickly grasp the fundamentals of AI and harness its potential to enhance their skills, grow their career, and start monetizing their expertise. In Part 1 of this essential series, you’ll dive into the basics of Generative AI, discovering how powerful tools from Google and other major platforms can transform your workflow, ignite your creativity, and open new career opportunities. Written in an easy-to-digest microlearning format, this guide simplifies complex AI concepts, ensuring you gain practical skills from day one. What You’ll Learn: Generative AI Essentials: Master the foundations of AI technology and how it’s revolutionizing industries worldwide. Google Tools for AI: Explore Google’s suite of AI-powered tools and learn how to integrate them into your projects. Real-World Applications: Get hands-on experience with actionable examples and projects designed to elevate your understanding. This series goes beyond theory because it takes you on a progressive journey from foundational knowledge to advanced skills needed to become a professional in the rapidly growing AI field. What’s Next in the Series? After establishing a solid base in Part 1, you’ll advance to topics like: LangChain & Hugging Face API: Unlock more powerful tools for building AI models and applications. Gemini Pro LLM Models & Vector Databases: Learn to work with cutting-edge language models and efficient data handling systems. Llama Index & AI Deployment Projects: Gain the skills to deploy AI projects in real-world environments, ready to impress clients or employers. Whether you’re a student, freelancer, or professional looking to boost your expertise, this book series will guide you every step of the way, turning you into a confident AI professional ready to meet the demands of a rapidly evolving market.

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch PDF Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624

Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

The Principles of Deep Learning Theory

The Principles of Deep Learning Theory PDF Author: Daniel A. Roberts
Publisher: Cambridge University Press
ISBN: 1316519333
Category : Computers
Languages : en
Pages : 473

Book Description
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.

Learning How to Learn

Learning How to Learn PDF Author: Barbara Oakley, PhD
Publisher: Penguin
ISBN: 052550446X
Category : Juvenile Nonfiction
Languages : en
Pages : 258

Book Description
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.

Artificial Intelligence Basics

Artificial Intelligence Basics PDF Author: Tom Taulli
Publisher: Apress
ISBN: 1484250281
Category : Computers
Languages : en
Pages : 195

Book Description
Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, and future impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking. What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing)Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch FixUnderstand how AI capabilities for robots can improve businessDeploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer serviceAvoid costly gotchasRecognize ethical concerns and other risk factors of using artificial intelligenceExamine the secular trends and how they may impact your business Who This Book Is For Readers without a technical background, such as managers, looking to understand AI to evaluate solutions.

Deep Learning Architectures

Deep Learning Architectures PDF Author: Ovidiu Calin
Publisher: Springer Nature
ISBN: 3030367215
Category : Mathematics
Languages : en
Pages : 760

Book Description
This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter. This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.

Introducing MLOps

Introducing MLOps PDF Author: Mark Treveil
Publisher: "O'Reilly Media, Inc."
ISBN: 1098116429
Category : Computers
Languages : en
Pages : 171

Book Description
More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized

Generative Art

Generative Art PDF Author: Matt Pearson
Publisher: Simon and Schuster
ISBN: 1638352437
Category : Computers
Languages : en
Pages : 352

Book Description
Summary Generative Art presents both the technique and the beauty of algorithmic art. The book includes high-quality examples of generative art, along with the specific programmatic steps author and artist Matt Pearson followed to create each unique piece using the Processing programming language. About the Technology Artists have always explored new media, and computer-based artists are no exception. Generative art, a technique where the artist creates print or onscreen images by using computer algorithms, finds the artistic intersection of programming, computer graphics, and individual expression. The book includes a tutorial on Processing, an open source programming language and environment for people who want to create images, animations, and interactions. About the Book Generative Art presents both the techniques and the beauty of algorithmic art. In it, you'll find dozens of high-quality examples of generative art, along with the specific steps the author followed to create each unique piece using the Processing programming language. The book includes concise tutorials for each of the technical components required to create the book's images, and it offers countless suggestions for how you can combine and reuse the various techniques to create your own works. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside The principles of algorithmic art A Processing language tutorial Using organic, pseudo-random, emergent, and fractal processes ========================================​========= Table of Contents Part 1 Creative Coding Generative Art: In Theory and Practice Processing: A Programming Language for ArtistsPart 2 Randomness and Noise The Wrong Way to Draw A Line The Wrong Way to Draw a Circle Adding Dimensions Part 3 Complexity Emergence Autonomy Fractals

Machine Learning For Dummies

Machine Learning For Dummies PDF Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 1119724015
Category : Computers
Languages : en
Pages : 471

Book Description
One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more. Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study. Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.