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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.

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.

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.

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

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

Algorithms

Algorithms PDF Author: Robert Sedgewick
Publisher: Addison-Wesley Professional
ISBN: 0133799107
Category : Computers
Languages : en
Pages : 828

Book Description
This book is Part I of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part I contains Chapters 1 through 3 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

Deep Learning with Python

Deep Learning with Python PDF Author: Francois Chollet
Publisher: Simon and Schuster
ISBN: 1638352046
Category : Computers
Languages : en
Pages : 597

Book Description
Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

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

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.

Artificial Intelligence For Dummies

Artificial Intelligence For Dummies PDF Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 1119467586
Category : Computers
Languages : en
Pages : 60

Book Description
Step into the future with AI The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. Learn about what AI has contributed to society Explore uses for AI in computer applications Discover the limits of what AI can do Find out about the history of AI The world of AI is fascinating—and this hands-on guide makes it more accessible than ever!

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.