Mastering Machine Learning
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Mastering Machine Learning Algorithms
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Author : Giuseppe Bonaccorso
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-25
Mastering Machine Learning Algorithms written by Giuseppe Bonaccorso and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-25 with Computers categories.
Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is for This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.
Mastering Machine Learning On Aws
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Author : Dr. Saket S.R. Mengle
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-20
Mastering Machine Learning On Aws written by Dr. Saket S.R. Mengle and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-20 with Computers categories.
Gain expertise in ML techniques with AWS to create interactive apps using SageMaker, Apache Spark, and TensorFlow. Key FeaturesBuild machine learning apps on Amazon Web Services (AWS) using SageMaker, Apache Spark and TensorFlowLearn model optimization, and understand how to scale your models using simple and secure APIsDevelop, train, tune and deploy neural network models to accelerate model performance in the cloudBook Description AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud. As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics, and predictive modeling, through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS. What you will learnManage AI workflows by using AWS cloud to deploy services that feed smart data productsUse SageMaker services to create recommendation modelsScale model training and deployment using Apache Spark on EMRUnderstand how to cluster big data through EMR and seamlessly integrate it with SageMakerBuild deep learning models on AWS using TensorFlow and deploy them as servicesEnhance your apps by combining Apache Spark and Amazon SageMakerWho this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and AWS users who want to build advanced models and smart applications on the cloud using AWS and its integration services. Some understanding of machine learning concepts, Python programming and AWS will be beneficial.
Mastering Machine Learning With R
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Author : Cory Lesmeister
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-01-31
Mastering Machine Learning With R written by Cory Lesmeister and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-31 with Computers categories.
Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key FeaturesBuild independent machine learning (ML) systems leveraging the best features of R 3.5Understand and apply different machine learning techniques using real-world examplesUse methods such as multi-class classification, regression, and clusteringBook Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learnPrepare data for machine learning methods with easeUnderstand how to write production-ready code and package it for useProduce simple and effective data visualizations for improved insightsMaster advanced methods, such as Boosted Trees and deep neural networksUse natural language processing to extract insights in relation to textImplement tree-based classifiers, including Random Forest and Boosted TreeWho this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.
Mastering Machine Learning With Scikit Learn Second Edition
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Author : Gavin Hackeling
language : en
Publisher:
Release Date : 2017-07-27
Mastering Machine Learning With Scikit Learn Second Edition written by Gavin Hackeling and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-27 with Computers categories.
Mastering Machine Learning With R
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Author : Cory Leismester
language : en
Publisher: Packt Publishing
Release Date : 2015-10-28
Mastering Machine Learning With R written by Cory Leismester and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-28 with Computers categories.
Master machine learning techniques with R to deliver insights for complex projectsAbout This Book• Get to grips with the application of Machine Learning methods using an extensive set of R packages• Understand the benefits and potential pitfalls of using machine learning methods• Implement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML systemWho This Book Is ForIf you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will Learn• Gain deep insights to learn the applications of machine learning tools to the industry• Manipulate data in R efficiently to prepare it for analysis• Master the skill of recognizing techniques for effective visualization of data• Understand why and how to create test and training data sets for analysis• Familiarize yourself with fundamental learning methods such as linear and logistic regression• Comprehend advanced learning methods such as support vector machines• Realize why and how to apply unsupervised learning methodsIn DetailMachine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data.The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series.The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approachThis is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.
Mastering Machine Learning With Core Ml And Python
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Author : Vardhan Agrawal
language : en
Publisher: AppCoda
Release Date : 2020-08-13
Mastering Machine Learning With Core Ml And Python written by Vardhan Agrawal and has been published by AppCoda this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-13 with Computers categories.
Machine learning, now more than ever, plays a pivotal role in almost everything we do in our digital lives. Whether it’s interacting with a virtual assistant like Siri or typing out a message to a friend, machine learning is the technology facilitating those actions. It’s clear that machine learning is here to stay, and as such, it’s a vital skill to have in the upcoming decades. This book covers Core ML in-depth. You will learn how to create and deploy your own machine learning model. On top of that, you will learn about Turi Create, Create ML, Keras, Firebase, and Jupyter Notebooks, just to name a few. These are a few examples of professional tools which are staples for many machine learning experts. By going through this book, you’ll also become proficient with Python, the language that’s most frequently used for machine learning. Plus, you would have created a handful of ready-to-use apps such as barcode scanners, image classifiers, and language translators. Most importantly, you will master the ins-and-outs of Core ML.
Machine Learning
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Author : Andrew Park
language : en
Publisher:
Release Date : 2020-11-14
Machine Learning written by Andrew Park and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-14 with categories.
Master The World Of Machine Learning And Data Science With This Comprehensive 2-in-1 bundleIf you want to learn more about Machine Learning and Data Science or how to master them with Python quickly and easily, then keep reading. Data Science and Machine Learning are one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?" Data Science includes all the different steps that you take with the data: collecting and cleaning them, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations. Machines and automation represent a huge part of our daily life. They are becoming part of our experience, and existence. Artificial Intelligence is currently one of the most thriving fields any programmer would wish to delve into, and for a good reason: this is the future! Simply put, Machine Learning is about teaching machines to think and make decisions as we would. The difference between the way machines learn and the way we do is that while for the most part we learn from experiences, machines learn from data. In book one, PYTHON MACHINE LEARNING, you will learn: What is Machine Learning and how it is applied in real-world situations Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence Machine learning training models, Regression techniques and Linear Regression in Python How to use Lists and Modules in Python The 12 essential libraries for Machine Learning in Python Artificial Neural Networks And Much More! In book two, PYTHON DATA SCIENCE, you will learn: What Data Science is all about and why so many companies are using it to give them a competitive edge. Why Python and how to use it to implement Data Science The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with practical codes and exercises The 7 most important algorithms and models in Data Science Data Aggregation, Group Operations, Databases and Data in the Cloud 9 important Data Mining techniques in Data Science And So Much More! Where most books only focus on how collecting and cleaning the data, this book goes further, providing guidance on how to perform a proper analysis in order to extract precious information that may be vital for a business. Don't miss the opportunity to master the key points of Machine Learning technology and understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines. Even if some Machine Learning concepts and algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Understanding Machine Learning and Data Science is easier than it looks. You just need the right guidance. And this bundle provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications. Would You Like To Know More?Scroll Up and Click the BUY NOW Button to Get Your Copy!
Mastering Reinforcement Learning With Python
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Author : Enes Bilgin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-12-18
Mastering Reinforcement Learning With Python written by Enes Bilgin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-18 with Computers categories.
Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices Key FeaturesUnderstand how large-scale state-of-the-art RL algorithms and approaches workApply RL to solve complex problems in marketing, robotics, supply chain, finance, cybersecurity, and moreExplore tips and best practices from experts that will enable you to overcome real-world RL challengesBook Description Reinforcement learning (RL) is a field of artificial intelligence (AI) used for creating self-learning autonomous agents. Building on a strong theoretical foundation, this book takes a practical approach and uses examples inspired by real-world industry problems to teach you about state-of-the-art RL. Starting with bandit problems, Markov decision processes, and dynamic programming, the book provides an in-depth review of the classical RL techniques, such as Monte Carlo methods and temporal-difference learning. After that, you will learn about deep Q-learning, policy gradient algorithms, actor-critic methods, model-based methods, and multi-agent reinforcement learning. Then, you'll be introduced to some of the key approaches behind the most successful RL implementations, such as domain randomization and curiosity-driven learning. As you advance, you’ll explore many novel algorithms with advanced implementations using modern Python libraries such as TensorFlow and Ray’s RLlib package. You’ll also find out how to implement RL in areas such as robotics, supply chain management, marketing, finance, smart cities, and cybersecurity while assessing the trade-offs between different approaches and avoiding common pitfalls. By the end of this book, you’ll have mastered how to train and deploy your own RL agents for solving RL problems. What you will learnModel and solve complex sequential decision-making problems using RLDevelop a solid understanding of how state-of-the-art RL methods workUse Python and TensorFlow to code RL algorithms from scratchParallelize and scale up your RL implementations using Ray's RLlib packageGet in-depth knowledge of a wide variety of RL topicsUnderstand the trade-offs between different RL approachesDiscover and address the challenges of implementing RL in the real worldWho this book is for This book is for expert machine learning practitioners and researchers looking to focus on hands-on reinforcement learning with Python by implementing advanced deep reinforcement learning concepts in real-world projects. Reinforcement learning experts who want to advance their knowledge to tackle large-scale and complex sequential decision-making problems will also find this book useful. Working knowledge of Python programming and deep learning along with prior experience in reinforcement learning is required.
Mastering Machine Learning
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Author : SREEKUMAR V T
language : en
Publisher: SREEKUMAR V T
Release Date : 2025-03-13
Mastering Machine Learning written by SREEKUMAR V T and has been published by SREEKUMAR V T this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Antiques & Collectibles categories.
"Mastering Machine Learning: From Fundamentals to Advanced Techniques" is a comprehensive guide that takes readers on a journey through the exciting world of machine learning. This book is designed to cater to both beginners and experienced practitioners, providing a structured approach to mastering the principles, algorithms, and methodologies of machine learning. Machine learning has become an integral part of numerous industries and fields, ranging from healthcare and finance to e-commerce and autonomous systems. The ability of machine learning models to analyze data, uncover patterns, and make accurate predictions has transformed the way we interact with technology and harness the power of data. In this book, readers will gain a solid understanding of the fundamental concepts and techniques of machine learning. Starting from the basics, the book covers data preprocessing, feature engineering, and exploratory data analysis, laying a strong foundation for more advanced topics. As readers progress, they will delve into supervised and unsupervised learning algorithms, model evaluation techniques, hyper-parameter tuning, and ensemble methods. The book also explores cutting-edge advancements in machine learning, including deep learning, natural language processing, reinforcement learning, time series analysis, and transfer learning. Readers will gain practical insights into the applications of these advanced techniques and learn how to apply them to real-world scenarios. Additionally, the book addresses important ethical considerations in machine learning, such as fairness, bias mitigation, and transparency. Understanding these ethical implications is crucial for responsible and ethical use of machine learning models. Key Features: Provides a comprehensive and structured approach to mastering machine learning. Covers fundamental concepts, algorithms, and methodologies. Explores advanced techniques such as deep learning, natural language processing, and reinforcement learning. Addresses ethical considerations in machine learning. Includes practical examples, exercises, and hands-on projects to reinforce learning. Whether you are a student, researcher, data scientist, or industry professional, "Mastering Machine Learning: From Fundamentals to Advanced Techniques" equips you with the knowledge, skills, and confidence to tackle real-world machine learning challenges. With a balanced blend of theory and practice, this book enables readers to unlock the full potential of machine learning and stay at the forefront of this rapidly evolving field.
Mastering Machine Learning Algorithms Second Edition
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Author : Giuseppe Bonaccorso
language : en
Publisher:
Release Date : 2020-01-31
Mastering Machine Learning Algorithms Second Edition written by Giuseppe Bonaccorso and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.