Download or read book Machine Learning Contests A Guidebook written by Wang He and published by Springer Nature. This book was released on 2023-10-11 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically introduces the competitions in the field of algorithm and machine learning. The first author of the book has won 5 championships and 5 runner-ups in domestic and international algorithm competitions. Firstly, it takes common competition scenarios as a guide by giving the main processes of using machine learning to solve real-world problems, namely problem modelling, data exploration, feature engineering, model training. And then lists the main points of difficulties, general ideas with solutions in the whole process. Moreover, this book comprehensively covers several common problems in the field of machine learning competitions such as recommendation, temporal prediction, advertising, text computing, etc. The authors, also knew as "competition professionals”, will explain the actual cases in detail and teach you various processes, routines, techniques and strategies, which is a rare treasure book for all competition enthusiasts. It is very suitable for readers who are interested in algorithm competitions and deep learning algorithms in practice, or computer-related majors.
Download or read book The Kaggle Book written by Konrad Banachewicz and published by Packt Publishing Ltd. This book was released on 2022-04-22 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get a step ahead of your competitors with insights from over 30 Kaggle Masters and Grandmasters. Discover tips, tricks, and best practices for competing effectively on Kaggle and becoming a better data scientist. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key Features Learn how Kaggle works and how to make the most of competitions from over 30 expert Kagglers Sharpen your modeling skills with ensembling, feature engineering, adversarial validation and AutoML A concise collection of smart data handling techniques for modeling and parameter tuning Book DescriptionMillions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first book of its kind, The Kaggle Book assembles in one place the techniques and skills you’ll need for success in competitions, data science projects, and beyond. Two Kaggle Grandmasters walk you through modeling strategies you won’t easily find elsewhere, and the knowledge they’ve accumulated along the way. As well as Kaggle-specific tips, you’ll learn more general techniques for approaching tasks based on image, tabular, textual data, and reinforcement learning. You’ll design better validation schemes and work more comfortably with different evaluation metrics. Whether you want to climb the ranks of Kaggle, build some more data science skills, or improve the accuracy of your existing models, this book is for you. Plus, join our Discord Community to learn along with more than 1,000 members and meet like-minded people!What you will learn Get acquainted with Kaggle as a competition platform Make the most of Kaggle Notebooks, Datasets, and Discussion forums Create a portfolio of projects and ideas to get further in your career Design k-fold and probabilistic validation schemes Get to grips with common and never-before-seen evaluation metrics Understand binary and multi-class classification and object detection Approach NLP and time series tasks more effectively Handle simulation and optimization competitions on Kaggle Who this book is for This book is suitable for anyone new to Kaggle, veteran users, and anyone in between. Data analysts/scientists who are trying to do better in Kaggle competitions and secure jobs with tech giants will find this book useful. A basic understanding of machine learning concepts will help you make the most of this book.
Download or read book MACHINE LEARNING written by Narayan Changder and published by CHANGDER OUTLINE. This book was released on 2023-10-17 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embark on an illuminating journey into the realm of "MACHINE LEARNING" with our definitive MCQ guide, "LearnML." Tailored for enthusiasts, students, and professionals venturing into the dynamic field of machine learning, this resource is your key to unraveling the intricacies of algorithms, models, and the transformative potential of machine learning technologies. Dive into a knowledge-rich experience, progressing from foundational to advanced concepts through a series of thoughtfully curated multiple-choice questions. Key Features: MCQ Exploration: Navigate through a diverse array of questions covering fundamental principles, machine learning algorithms, and the unique characteristics of model training, ensuring a comprehensive understanding of this transformative field. Detailed Explanations: Elevate your knowledge with comprehensive explanations accompanying each MCQ, unraveling the intricacies of supervised learning, unsupervised learning, and the principles that define the power of machine learning. Real-World Applications: Bridge theory and practice, connecting machine learning concepts to real-world applications in predictive analytics, recommendation systems, and the dynamic landscape of AI-driven solutions. Progressive Difficulty Levels: Challenge yourself with questions ranging from foundational to advanced, providing a structured learning experience suitable for learners at all levels. Visual Learning Tools: Reinforce your understanding with visual aids such as machine learning flowcharts, algorithmic diagrams, and examples of machine learning applications, enhancing your grasp of machine learning concepts. Embark on a quest for machine learning mastery with "LearnML: MACHINE LEARNING." Download your copy now to master the essential skills needed for understanding the transformative potential of machine learning. Whether you're a student, machine learning enthusiast, or a professional in the field, this guide is your key to unlocking the capabilities of machine learning with precision and expertise.
Download or read book Machine Learning For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2016-05-11 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data—or anything in between—this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!
Download or read book Machine Learning written by Steven Alex and published by . This book was released on 2019-11-06 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ ★ Buy the Paperback Version of this Book and Get the Kindle Book version for FREE ★ ★ Machine Learning (Update Edition 2019-2020) this Guide is a branch of artificial intelligence, This Machine Learning Series idea is relatively new. A science that researches machines to acquire new knowledge and new skills and to identify existing knowledge. The best way to understand the potential of machine learning is to explore how people and companies are currently taking advantage of it.If you are one of the almost 400 million people with machine learning worldwide, This book offers a method to Techniques! Not every machine learning model uses the same techniques, so training will depend on your approach. Let's consider a few examples: Psychology of learning Machine learning in practice Reinforcement learning Types of machine learning Learning by reinforcement Types of reinforcement The different types of learning This guidebook is going to take some time to explore machine learning, and what it is all about. There are so many different aspects of machine learning and how to make it work for your needs, and all of it is found in this guidebook. Some of the different topics that you will be able to learn about inside include: Neural networks Historical background Why use neural networks? Tasks of neural networks Deep learning Algorithms Starting with python Basic types of data Get access to free software and data sets so you can try out your very own machine learning software. See how advanced machine learning will impact our world in the future! Scroll Up and Click the Buy Now Button!
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 Machine Learning Made Easy A Beginner s Guide for All written by M.B. Chatfield and published by M.B. Chatfield. This book was released on with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the power of machine learning to automate tasks, make predictions, and solve complex problems. Machine learning is a powerful tool that can be used to automate tasks, make predictions, and solve complex problems. It is used in a wide variety of industries, including healthcare, finance, and manufacturing. Machine Learning Made Easy is the perfect resource for anyone who wants to learn the basics of machine learning. This comprehensive guide covers everything you need to know, from the basics of machine learning algorithms to advanced topics such as deep learning. Whether you're a student, a business professional, or a data enthusiast, Machine Learning Made Easy is the essential resource for learning about machine learning. Here are some of the key topics covered in the book: Introduction to machine learning Types of machine learning algorithms Choosing the right machine learning algorithm Training a machine learning model Evaluating a machine learning model Using machine learning to automate tasks Using machine learning to make predictions If you are a beginner who wants to learn about machine learning, Machine Learning Made Easy is a great place to start.
Download or read book A Guide to Machine Learning Deep Learning and Their Applications written by Siddharth Sharma (Writer on machine learning) and published by . This book was released on 2020 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Essential Guide on Data Science written by Andrew Park and published by Andrew Park. This book was released on 2021-02-12 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ 55% OFF for Bookstores! NOW at $ 23,97 instead of $ 33.97! ★ Are you interested in knowing more about the fascinating world of Data Science? Your Customers Will Love This Amazing Step-By-Step Guide! This book offers you the fundamental knowledge you need to get started, but keep in mind that no book or even teacher can do everything for you. You need to work hard by putting each building block in its place as you advance. Data Science is a massive field of study that requires years of learning and practice before you can master it. This shouldn't discourage you, however! Embrace it as a challenge that you can undertake in order to broaden your horizons and improve your knowledge of all that is Data Science and machine learning. Data Science is a highly complex topic that has continuously been developed for decades. It is constantly evolving, and it can be challenging to keep up with all the past, present, and future concepts. With that being said, this isn't supposed to discourage you from pursuing this field. To start out this guidebook, we are going to take a look at what Data Science is all about, why it is important, and why we would want to work with this process in the first place as well. We will then take some time in order to learn the lifecycle of Data Science, and how we need to go through a series of steps like the finding the right data, preparing the data, coming up with the right model, and more. All of this and more will be discussed in this guidebook so that you can go from start to finish with your own Data Science project. This is just the start of some of the amazing things that we are able to do when it is time to start on Data Science. We are able to spend our time looking at what machine learning is all about, the different types of machine learning, and how we are able to put it all together to makes sure that we can create the right algorithms and models when it is time to sort through our data and find the right patterns and insights in the process. In "The Essential Guide on Data Science" you will discover: What is Data Science? Why is Data Science So Important? The Benefits of Python Data Science The Lifecycle of Data Science The Importance of Visuals with Data Science A Look at Data Mining The Real-Life Applications of Data Science There are a lot of benefits that we are able to see when it comes to working on Data Science, and many companies in a lot of different industries are going to work with this in order to ensure that we will be able to handle how to work with their customers, how to beat out the competition, and so much more. When you are ready to work with the idea of Data Science, and you want to work with all of the different parts that are found with it, then make sure to check out this guidebook to help you get started. You can position yourself to use your deep knowledge and understanding of all the cutting-edge technologies obtained from this book to contribute to the growth of any company and land yourself a new high paying and rewarding job! Buy It NOW and Let Your Customers Get Addicted to This Amazing Book!
Download or read book Data Science and Big Data Analytics written by Andrew Park and published by Andrew Park. This book was released on 2021-02-12 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ 55% OFF for Bookstores! NOW at $ 22,97 instead of $ 32.97! LAST DAYS! ★ Your Customers Never Stop to Use this Awesome book! Do you want to know everything about Data science? This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you! Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful! There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business. Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started. The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started. There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together. This book covers: What Is Data Science? How Can I Use Data Science? The Best Python Libraries for Data Science Setting Up Your Virtual Environments for Data Science The Importance of the NumPy Arrays Gathering and Collecting Your Data Loading and Preparing Your Dataset Data Mining Completing the Data Analysis How Machine Learning Can Help How to Work with Data Visualization Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started. Buy it NOW and get addicted to this amazing book
Download or read book Handbook of Machine Learning for Computational Optimization written by Vishal Jain and published by CRC Press. This book was released on 2021-11-02 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.
Download or read book Machine Learning written by Ryan Turner and published by . This book was released on 2019-10-26 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★ Are you someone who is interested in how the next generation of machines can help you? Is Artificial Intelligence something to be feared, or do you imagine it that it will change our lives for the better? Do you want to know more?This book will provide the answers you need!Life is becoming ever more complex as we struggle to keep up with technology and use it to our best advantage. It is also more hectic and less certain, even in some of the mundane aspects of our lives, so that we are constantly trying to keep pace. New advancements in technology are paving the way to making life easier for billions and now things like Machine Learning and AI are changing the way we live.In this book, Machine Learning: The Ultimate Beginner's Guide to Learn Machine Learning, Artificial Intelligence & Neural Networks Step by Step, you will see how this new technology continuously improves itself, can identify trends and patterns with ease and handles a wide variety of data, with chapters that explore:: - Teaching the basic principles of Machine Learning- Why it is important and the many benefits that it provides- How Machine Learning differs from conventional programming- The fundamentals of algorithms- Challenges with Machine Learning and how you can easily overcome them- How it is going to change the future and make life easier- And much more...Machine Learning and AI are more than just science fiction. They are here now and undoubtedly will remain, improving and enhancing our lives in many ways, from the everyday to the vitally important. This book provides a platform that will give you a comprehensive understanding, that is second to none, of machine learning and its place in the world today.Get a copy nowand see how Machine Learning will change your life!
Download or read book Machine Learning for Beginners written by Ethem Mining and published by . This book was released on 2019-12-03 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you fascinated about machine learning and AI and you don't know where to start? Have you ever heard people talking about Machine Learning but you only have a vague idea of the actual meaning? Do you want to understand how machine learning could simplify your daily life? Imagine a world where computing systems understand people and the world around us them to a point where they can notice patterns, collect data, interpret it and give recommendations to solve real world problems with high level of precision. It sounds like science fiction but it is happening in healthcare, agriculture, cyber security, facial recognition, targeting and retargeting customers in online advertising, recommending specific products, stories, videos, text etc., self-driving cars, real time pricing, predicting human behavior and much more. Now imagine you being one of the people behind the code; the people who get these advanced systems to work the way they do. Would it be a dream come true for you? By virtue that you are reading this, it is clear that you have some special liking for this advanced tech and would want to learn how you can be one of the people behind the code. Even if not, you probably want to be able to understand the inner workings of these systems. The concept may sound extremely out there and advanced but it won't be if you follow this guide, which takes an easy to follow, beginner friendly language to help you to understand the ins and outs of machine learning! Here is a summary of what this book will teach you: The basics of machine learning, including what it is, how machine learning has evolved over the years, the application of machine learning in today's world and the future of machine learning How machine learning is beneficial in today's world The different approaches to machine learning, including unsupervised, supervised, reinforcement learning method, semi-supervised machine learning and many others The concept of big data analysis, including what is big data, why big data is important, the application of big data in today's world as well as the different data analysis tools that you can use The link between big data and machine learning The different machine learning algorithms, including what machine-learning algorithms are and how and when the different learning algorithms are used The concept of artificial neural networks, including how they work, when to use neural networks and more How decision trees are used in machine learning, including what decision trees are (in respect to machine learning), how they work, how the decision tree is read, the different nodes in decision trees and when to use them The ins and outs of linear and logistic regression in machine learning, including what linear regression is, different types of regression, how linear regression works, how linear regression is used and much more And much more! Even if this is your first encounter with the concept of machine learning, this book will uncover everything you need to know to master machine learning and possibly get started in this field of advanced computing knowing very well what you are venturing into. And the good thing is that the book takes a beginner friendly approach to help you to apply what you learn right away! Would You Like To Know More? Click Buy Now With 1-Click or Buy Now to get started!
Download or read book Machine Learning and Its Application A Quick Guide for Beginners written by Indranath Chatterjee and published by Bentham Science Publishers. This book was released on 2021-12-22 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Its Application: A Quick Guide for Beginners aims to cover most of the core topics required for study in machine learning curricula included in university and college courses. The textbook introduces readers to central concepts in machine learning and artificial intelligence, which include the types of machine learning algorithms and the statistical knowledge required for devising relevant computer algorithms. The book also covers advanced topics such as deep learning and feature engineering. Key features: - 8 organized chapters on core concepts of machine learning for learners - Accessible text for beginners unfamiliar with complex mathematical concepts - Introductory topics are included, including supervised learning, unsupervised learning, reinforcement learning and predictive statistics - Advanced topics such as deep learning and feature engineering provide additional information - Introduces readers to python programming with examples of code for understanding and practice - Includes a summary of the text and a dedicated section for references Machine Learning and Its Application: A Quick Guide for Beginners is an essential book for students and learners who want to understand the basics of machine learning and equip themselves with the knowledge to write algorithms for intelligent data processing applications.
Download or read book The Hundred page Machine Learning Book written by Andriy Burkov and published by . This book was released on 2019 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.
Download or read book Model Based Machine Learning written by John Winn and published by CRC Press. This book was released on 2023-11-30 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach. The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solve a problem. Features: Explores the assumptions being made by machine learning systems and the effect these assumptions have when the system is applied to concrete problems. Explains machine learning concepts as they arise in real-world case studies. Shows how to diagnose, understand and address problems with machine learning systems. Full source code available, allowing models and results to be reproduced and explored. Includes optional deep-dive sections with more mathematical details on inference algorithms for the interested reader.
Download or read book Machine Learning written by Ryan Turner and published by Publishing Factory . This book was released on 2020-04-19 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you someone who is interested in how the next generation of machines can help you? Is Artificial Intelligence something to be feared, or do you imagine it that it will change our lives for the better? This book will provide the answers you need. Life is becoming ever more complex as we struggle to keep up with technology and use it to our best advantage. It is also more hectic and less certain, even in some of the mundane aspects of our lives, so that we are constantly trying to keep pace. New advancements in technology are paving the way to making life easier for billions and now things like Machine Learning and AI are changing the way we live. In this book, Machine Learning: The Ultimate Beginner’s Guide to Learn Machine Learning, Artificial Intelligence & Neural Networks Step by Step, you will see how this new technology continuously improves itself, can identify trends and patterns with ease and handles a wide variety of data, with chapters that explore: • Teaching the basic principles of Machine Learning • Why it is important and the many benefits that it provides • How Machine Learning differs from conventional programming • The fundamentals of algorithms • Challenges with Machine Learning and how you can easily overcome them • How it is going to change the future and make life easier • And much more… Machine Learning and AI are more than just science fiction. They are here now and undoubtedly will remain, improving and enhancing our lives in many ways, from the everyday to the vitally important. This book provides a platform that will give you a comprehensive understanding, that is second to none, of machine learning and its place in the world today. Get a copy now and see how Machine Learning will change your life!
