Download or read book Machine Learning with MOJO Programming Language written by Edward R DeForest and published by Independently Published. This book was released on 2024-04-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conquer Machine Learning with Mojo: Your Guide to High-Performance Models & Rapid AI Development About the Technology: Mojo is a revolutionary programming language designed to bridge the gap between research and production in machine learning. It offers the ease of use of Python with the lightning-fast performance of C++, making it ideal for building powerful and efficient AI applications. Worried about complex machine learning? Fret no more! This book guides you step-by-step through the Mojo development process, even if you're new to machine learning. Learn how to leverage Mojo's intuitive syntax and powerful features to create sophisticated models without getting bogged down in complex details. Challenges of slow development cycles? Say goodbye to waiting! Mojo's focus on speed allows you to rapidly prototype, train, and deploy your machine learning models. This book equips you with the knowledge and techniques to streamline your development workflow and bring your AI ideas to life faster than ever before. What to Expect: Master the fundamentals: Gain a solid understanding of machine learning concepts and techniques. Harness the power of Mojo: Learn how to leverage Mojo's unique features to build high-performance models. Navigate the development process: Discover practical guidance on data preparation, model training, deployment, and optimization. Real-world applications: Explore how to apply machine learning to solve problems in various domains. Code examples and exercises: Put your learning into practice with hands-on projects that solidify your understanding. Ready to unlock the potential of machine learning with Mojo? This book is your ultimate roadmap to success. Get started today and embark on your journey to becoming a confident and productive machine learning develop

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Practical Automated Machine Learning Using H2O ai written by Salil Ajgaonkar and published by Packt Publishing Ltd. This book was released on 2022-09-26 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accelerate the adoption of machine learning by automating away the complex parts of the ML pipeline using H2O.ai Key FeaturesLearn how to train the best models with a single click using H2O AutoMLGet a simple explanation of model performance using H2O ExplainabilityEasily deploy your trained models to production using H2O MOJO and POJOBook Description With the huge amount of data being generated over the internet and the benefits that Machine Learning (ML) predictions bring to businesses, ML implementation has become a low-hanging fruit that everyone is striving for. The complex mathematics behind it, however, can be discouraging for a lot of users. This is where H2O comes in – it automates various repetitive steps, and this encapsulation helps developers focus on results rather than handling complexities. You'll begin by understanding how H2O's AutoML simplifies the implementation of ML by providing a simple, easy-to-use interface to train and use ML models. Next, you'll see how AutoML automates the entire process of training multiple models, optimizing their hyperparameters, as well as explaining their performance. As you advance, you'll find out how to leverage a Plain Old Java Object (POJO) and Model Object, Optimized (MOJO) to deploy your models to production. Throughout this book, you'll take a hands-on approach to implementation using H2O that'll enable you to set up your ML systems in no time. By the end of this H2O book, you'll be able to train and use your ML models using H2O AutoML, right from experimentation all the way to production without a single need to understand complex statistics or data science. What you will learnGet to grips with H2O AutoML and learn how to use itExplore the H2O Flow Web UIUnderstand how H2O AutoML trains the best models and automates hyperparameter optimizationFind out how H2O Explainability helps understand model performanceExplore H2O integration with scikit-learn, the Spring Framework, and Apache StormDiscover how to use H2O with Spark using H2O Sparkling WaterWho this book is for This book is for engineers and data scientists who want to quickly adopt machine learning into their products without worrying about the internal intricacies of training ML models. If you're someone who wants to incorporate machine learning into your software system but don't know where to start or don't have much expertise in the domain of ML, then you'll find this book useful. Basic knowledge of statistics and programming is beneficial. Some understanding of ML and Python will be helpful.

Download or read book Generative AI written by Martin Musiol and published by John Wiley & Sons. This book was released on 2023-01-08 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: An engaging and essential discussion of generative artificial intelligence In Generative AI: Navigating the Course to the Artificial General Intelligence Future, celebrated author Martin Musiol—founder and CEO of generativeAI.net and GenAI Lead for Europe at Infosys—delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space. Musiol analyzes complex and foundational topics in generative AI, breaking them down into straightforward and easy-to-understand pieces. You'll also find: Bold predictions about the future emergence of Artificial General Intelligence via the merging of current AI models Fascinating explorations of the ethical implications of AI, its potential downsides, and the possible rewards Insightful commentary on Autonomous AI Agents and how AI assistants will become integral to daily life in professional and private contexts Perfect for anyone interested in the intersection of ethics, technology, business, and society—and for entrepreneurs looking to take advantage of this tech revolution—Generative AI offers an intuitive, comprehensive discussion of this fascinating new technology.

Download or read book Programming Language Explorations written by Ray Toal and published by CRC Press. This book was released on 2024-08-06 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Programming Language Explorations helps its readers gain proficiency in programming language practice and theory by presenting both example-focused, chapter-length explorations of fourteen important programming languages and detailed discussions of the major concepts transcending multiple languages. A language-by-language approach is sandwiched between an introductory chapter that motivates and lays out the major concepts of the field and a final chapter that brings together all that was learned in the middle chapters into a coherent and organized view of the field. Each of the featured languages in the middle chapters is introduced with a common trio of example programs and followed by a tour of its basic language features and coverage of interesting aspects from its type system, functional forms, scoping rules, concurrency patterns, and metaprogramming facilities. These chapters are followed by a brief tour of over 40 additional languages designed to enhance the reader’s appreciation of the breadth of the programming language landscape and to motivate further study. Targeted to both professionals and advanced college undergraduates looking to expand the range of languages and programming patterns they can apply in their work and studies, the book pays attention to modern programming practices, keeps a focus on cutting-edge programming patterns, and provides many runnable examples, all of which are available in the book’s companion GitHub repository. The combination of conceptual overviews with exploratory example-focused coverage of individual programming languages provides its readers with the foundation for more effectively authoring programs, prompting AI programming assistants, and, perhaps most importantly, learning—and creating—new languages.

Download or read book Learning FPGAs written by Justin Rajewski and published by "O'Reilly Media, Inc.". This book was released on 2017-08-16 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to design digital circuits with FPGAs (field-programmable gate arrays), the devices that reconfigure themselves to become the very hardware circuits you set out to program. With this practical guide, author Justin Rajewski shows you hands-on how to create FPGA projects, whether you’re a programmer, engineer, product designer, or maker. You’ll quickly go from the basics to designing your own processor. Designing digital circuits used to be a long and costly endeavor that only big companies could pursue. FPGAs make the process much easier, and now they’re affordable enough even for hobbyists. If you’re familiar with electricity and basic electrical components, this book starts simply and progresses through increasingly complex projects. Set up your environment by installing Xilinx ISE and the author’s Mojo IDE Learn how hardware designs are broken into modules, comparable to functions in a software program Create digital hardware designs and learn the basics on how they’ll be implemented by the FPGA Build your projects with Lucid, a beginner-friendly hardware description language, based on Verilog, with syntax similar to C/C++ and Java

Download or read book Mojo Programming for Beginners written by David A Fitzgerald and published by Independently Published. This book was released on 2024-05-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Become an AI Developer: Your Beginner's Guide to Mojo Programming Unleash the Power of AI with Mojo Mojo is a revolutionary programming language designed specifically for Artificial Intelligence. It combines the readability of Python with the lightning-fast performance of C, making it the perfect tool to build cutting-edge AI applications. Even if you're new to coding, Mojo's intuitive syntax and wealth of practical examples will have you creating intelligent programs in no time. Turn Your Ideas into Reality Imagine building AI-powered tools that can: Analyze massive datasets and uncover hidden insights Develop chatbots that can hold natural conversations Create intelligent systems that learn and adapt on their own With Mojo Programming for Beginners, these possibilities become a reality. What You'll Learn Inside: Master Mojo's fundamental concepts, including variables, data types, and control flow. Craft powerful functions and leverage object-oriented programming techniques. Navigate the exciting world of Machine Learning with clear, step-by-step guidance. Debug your code effectively and ensure your AI applications run smoothly. Explore Mojo's unique features like Single Instruction, Multiple Data (SIMD) for unparalleled performance. Benefits You'll Reap: Gain a coveted skillset in high demand within the booming AI industry. Bring your innovative ideas to life with the power of Mojo. Simplify complex AI concepts with a beginner-friendly approach. Stay ahead of the curve in the ever-evolving world of technology. Not Sure if Mojo is Right for You? Whether you're a complete beginner or have some programming experience, Mojo Programming for Beginners is designed to be accessible and engaging. The book provides a solid foundation in Mojo, preparing you to tackle more advanced AI projects. Take Your First Step Towards AI Mastery Don't wait any longer to unlock the potential of AI. Purchase your copy of Mojo Programming for Beginners today and embark on your journey to becoming a successful AI developer!

Download or read book Haskell Programming from First Principles written by Christopher Allen and published by . This book was released on 2016-07-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Haskell Programming makes Haskell as clear, painless, and practical as it can be, whether you're a beginner or an experienced hacker. Learning Haskell from the ground up is easier and works better. With our exercise-driven approach, you'll build on previous chapters such that by the time you reach the notorious Monad, it'll seem trivial.

Download or read book History of Programming Languages written by Richard L. Wexelblat and published by Academic Press. This book was released on 2014-05-27 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: History of Programming Languages presents information pertinent to the technical aspects of the language design and creation. This book provides an understanding of the processes of language design as related to the environment in which languages are developed and the knowledge base available to the originators. Organized into 14 sections encompassing 77 chapters, this book begins with an overview of the programming techniques to use to help the system produce efficient programs. This text then discusses how to use parentheses to help the system identify identical subexpressions within an expression and thereby eliminate their duplicate calculation. Other chapters consider FORTRAN programming techniques needed to produce optimum object programs. This book discusses as well the developments leading to ALGOL 60. The final chapter presents the biography of Adin D. Falkoff. This book is a valuable resource for graduate students, practitioners, historians, statisticians, mathematicians, programmers, as well as computer scientists and specialists.

Download or read book Neural Networks and Statistical Learning written by Ke-Lin Du and published by Springer Science & Business Media. This book was released on 2013-12-09 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.

Download or read book The D Programming Language written by Andrei Alexandrescu and published by Addison-Wesley Professional. This book was released on 2010-06-02 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: D is a programming language built to help programmers address the challenges of modern software development. It does so by fostering modules interconnected through precise interfaces, a federation of tightly integrated programming paradigms, language-enforced thread isolation, modular type safety, an efficient memory model, and more. The D Programming Language is an authoritative and comprehensive introduction to D. Reflecting the author’s signature style, the writing is casual and conversational, but never at the expense of focus and pre¿cision. It covers all aspects of the language (such as expressions, statements, types, functions, contracts, and modules), but it is much more than an enumeration of features. Inside the book you will find In-depth explanations, with idiomatic examples, for all language features How feature groups support major programming paradigms Rationale and best-use advice for each major feature Discussion of cross-cutting issues, such as error handling, contract programming, and concurrency Tables, figures, and “cheat sheets” that serve as a handy quick reference for day-to-day problem solving with D Written for the working programmer, The D Programming Language not only introduces the D language—it presents a compendium of good practices and idioms to help both your coding with D and your coding in general.

Download or read book Advances in Intelligent Systems and Computing II written by Natalia Shakhovska and published by Springer. This book was released on 2017-11-20 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on new theories and applications in the field of intelligent systems and computing. It covers computational and artificial intelligence methods, as well as advances in computer vision, current issues in big data and cloud computing, computation linguistics, and cyber-physical systems. It also reports on data mining and knowledge extraction technologies, as well as central issues in intelligent information management. Written by active researchers, the respective chapters are based on papers presented at the International Conference on Computer Science and Information Technologies (CSIT 2017), held on September 5–8, 2017, in Lviv, Ukraine; and at two workshops accompanying the conference: one on inductive modeling, jointly organized by the Lviv Polytechnic National University and the National Academy of Science of Ukraine; and another on project management, which was jointly organized by the Lviv Polytechnic National University, the International Project Management Association, the Ukrainian Project Management Association, the Kazakhstan Project Management Association, and Nazarbayev University. Given its breadth of coverage, the book provides academics and professionals with extensive information and a timely snapshot of the field of intelligent systems, and is sure to foster new discussions and collaborations among different groups.

Download or read book Dynamic Programming for Coding Interviews written by Meenakshi and published by Notion Press. This book was released on 2017-01-18 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: I wanted to compute 80th term of the Fibonacci series. I wrote the rampant recursive function, int fib(int n){ return (1==n || 2==n) ? 1 : fib(n-1) + fib(n-2); } and waited for the result. I wait… and wait… and wait… With an 8GB RAM and an Intel i5 CPU, why is it taking so long? I terminated the process and tried computing the 40th term. It took about a second. I put a check and was shocked to find that the above recursive function was called 204,668,309 times while computing the 40th term. More than 200 million times? Is it reporting function calls or scam of some government? The Dynamic Programming solution computes 100th Fibonacci term in less than fraction of a second, with a single function call, taking linear time and constant extra memory. A recursive solution, usually, neither pass all test cases in a coding competition, nor does it impress the interviewer in an interview of company like Google, Microsoft, etc. The most difficult questions asked in competitions and interviews, are from dynamic programming. This book takes Dynamic Programming head-on. It first explain the concepts with simple examples and then deep dives into complex DP problems.

Download or read book The Master Algorithm written by Pedro Domingos and published by Basic Books. This book was released on 2015-09-22 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

Download or read book Machine Learning Solutions written by Jalaj Thanaki and published by Packt Publishing Ltd. This book was released on 2018-04-27 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical, hands-on solutions in Python to overcome any problem in Machine Learning Key Features Master the advanced concepts, methodologies, and use cases of machine learning Build ML applications for analytics, NLP and computer vision domains Solve the most common problems in building machine learning models Book Description Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions. In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity. What you will learn Select the right algorithm to derive the best solution in ML domains Perform predictive analysis effciently using ML algorithms Predict stock prices using the stock index value Perform customer analytics for an e-commerce platform Build recommendation engines for various domains Build NLP applications for the health domain Build language generation applications using different NLP techniques Build computer vision applications such as facial emotion recognition Who this book is for This book is for the intermediate users such as machine learning engineers, data engineers, data scientists, and more, who want to solve simple to complex machine learning problems in their day-to-day work and build powerful and efficient machine learning models. A basic understanding of the machine learning concepts and some experience with Python programming is all you need to get started with this book.

Download or read book Technology Applied written by Kevin Wooldridge and published by CRC Press. This book was released on 2024-08-01 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology – love it or hate it – is a critical component for nearly every modern business. To the business leader or aspiring business leader, the world of technology may sometimes appear to be confusing and obscure. The language and nuance of software, systems, and IT projects is often a barrier to effective communication between different parts of an enterprise at just the time when it’s most needed – during a technology-enabled project that is seeking to deliver business benefit. This book sets out, in clear non-technical language and with practical real-world examples, the essential background to different aspects of information technology (hardware, software, data, and interfaces); their latest manifestations, such as artificial intelligence and blockchain; and how they all combine into a technology project. Most importantly, this book helps you, the business leader, understand the people behind the technology, appreciate their perspective and their motivations, and to enable you to ask the crucial questions that could transform your engagement to apply technology effectively.

Download or read book The Data Science Design Manual written by Steven S. Skiena and published by Springer. This book was released on 2017-07-01 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)