Automated Machine Learning A Complete Guide 2020 Edition

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Automated Machine Learning A Complete Guide - 2020 Edition

Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9781867318996
Total Pages : 306 pages
Book Rating : 4.3/5 (189 download)

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Book Synopsis Automated Machine Learning A Complete Guide - 2020 Edition by : Gerardus Blokdyk

Download or read book Automated Machine Learning A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-01-28 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: How are consistent Automated machine learning definitions important? Are there recognized Automated machine learning problems? Who is gathering information? What other organizational variables, such as reward systems or communication systems, affect the performance of this Automated machine learning process? Instead of going to current contacts for new ideas, what if you reconnected with dormant contacts--the people you used to know? If you were going reactivate a dormant tie, who would it be? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Automated Machine Learning investments work better. This Automated Machine Learning All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Automated Machine Learning Self-Assessment. Featuring 942 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Automated Machine Learning improvements can be made. In using the questions you will be better able to: - diagnose Automated Machine Learning projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Automated Machine Learning and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Automated Machine Learning Scorecard, you will develop a clear picture of which Automated Machine Learning areas need attention. Your purchase includes access details to the Automated Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Automated Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Automated Machine Learning

Author : Frank Hutter
Publisher : Springer
ISBN 13 : 3030053180
Total Pages : 223 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Automated Machine Learning by : Frank Hutter

Download or read book Automated Machine Learning written by Frank Hutter and published by Springer. This book was released on 2019-05-17 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

Life of AI

Author : William Krystal
Publisher : Independently Published
ISBN 13 :
Total Pages : 812 pages
Book Rating : 4.6/5 (432 download)

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Book Synopsis Life of AI by : William Krystal

Download or read book Life of AI written by William Krystal and published by Independently Published. This book was released on 2020-06-10 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: About Life of Artificial Intelligence Life of Ai Book Offers a Comprehensive Artificial Intelligence Program that will help you work on today's cutting-edge technology - Artificial Intelligence (AI). As part of this best AI teaching, you will master various aspects of Data Science (DS), Machine Learning (ML), Natural Language Processing (NLP), Deep Learning (DL), Reinforcement Learning (RL), IOT (Internet of Things), Python for Artificial Intelligence, Robotics and much more.What will you learn in this Life of Ai Book?The main goal of this book is to familiarize you with all aspects of AI so that you can start your career as an artificial intelligence engineer. A few of the many topics/modules that you will learn in the program are: -Basics of Artificial Intelligence techniques-Data Science-Machine Learning -Natural Language Processing-Deep Learning-Reinforcement Learning-Internet of Things-Python for Artificial Intelligence-Robotics

Machine Learning

Author : Steven Alex
Publisher :
ISBN 13 : 9781706195856
Total Pages : 135 pages
Book Rating : 4.1/5 (958 download)

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Book Synopsis Machine Learning by : Steven Alex

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!

Hands-On Automated Machine Learning

Author : Sibanjan Das
Publisher : Packt Publishing Ltd
ISBN 13 : 1788622286
Total Pages : 273 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Hands-On Automated Machine Learning by : Sibanjan Das

Download or read book Hands-On Automated Machine Learning written by Sibanjan Das and published by Packt Publishing Ltd. This book was released on 2018-04-26 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automate data and model pipelines for faster machine learning applications Key Features Build automated modules for different machine learning components Understand each component of a machine learning pipeline in depth Learn to use different open source AutoML and feature engineering platforms Book Description AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions. What you will learn Understand the fundamentals of Automated Machine Learning systems Explore auto-sklearn and MLBox for AutoML tasks Automate your preprocessing methods along with feature transformation Enhance feature selection and generation using the Python stack Assemble individual components of ML into a complete AutoML framework Demystify hyperparameter tuning to optimize your ML models Dive into Machine Learning concepts such as neural networks and autoencoders Understand the information costs and trade-offs associated with AutoML Who this book is for If you’re a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You’ll also find this book useful if you’re an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book.

Amazon Machine Learning A Complete Guide - 2020 Edition

Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9781867408031
Total Pages : 308 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Amazon Machine Learning A Complete Guide - 2020 Edition by : Gerardus Blokdyk

Download or read book Amazon Machine Learning A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-05-19 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: What sources do you use to gather information for a Amazon Machine Learning study? In the past few months, what is the smallest change you have made that has had the biggest positive result? What was it about that small change that produced the large return? What are the challenges? What internal processes need improvement? Are resources adequate for the scope? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Amazon Machine Learning investments work better. This Amazon Machine Learning All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Amazon Machine Learning Self-Assessment. Featuring 948 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Amazon Machine Learning improvements can be made. In using the questions you will be better able to: - diagnose Amazon Machine Learning projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Amazon Machine Learning and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Amazon Machine Learning Scorecard, you will develop a clear picture of which Amazon Machine Learning areas need attention. Your purchase includes access details to the Amazon Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Amazon Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Python Machine Learning

Author : Andrew Park
Publisher : Independently Published
ISBN 13 : 9781676467687
Total Pages : 168 pages
Book Rating : 4.4/5 (676 download)

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Book Synopsis Python Machine Learning by : Andrew Park

Download or read book Python Machine Learning written by Andrew Park and published by Independently Published. This book was released on 2019-12-17 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to learn how to design and master different Machine Learning algorithms quickly and easily, then keep reading. Today, we live in the era of Artificial Intelligence. Self-driving cars, customized product recommendations, real-time pricing, speech and facial recognition are just a few examples proving this truth. Also, think about medical diagnostics or automation of mundane and repetitive labor tasks; all these highlight the fact that we live in interesting times. From research topics to projects and applications in different stages of production, there is a lot going on in the world of Machine Learning. Machines and automation represent a huge part of our daily life. They are becoming part of our experience, and existence. This is Machine Learning. 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. Starting from scratch, Python Machine Learning explains how this happens, how machines build their experience and compounding knowledge. Data forms the core of Machine Learning because within data lie truths whose depths exceed our imagination. The computations machines can perform on data are incredible, beyond anything a human brain could do. Once we introduce data to a machine learning model, we must create an environment where we update the data stream frequently. This builds the machine's learning ability. The more data Machine Learning models are exposed to, the easier it is for these models to expand their potential. Some of the topics that we will discuss inside include: What is Machine Learning and how it is applied in real-world situations Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence Supervised learning, unsupervised learning, and semi-supervised learning The place of Regression techniques in Machine Learning, including Linear Regression in Python Machine learning training models How to use Lists and Modules in Python The 12 essential libraries for Machine Learning in Python What is the Tensorflow library Artificial Neural Networks While most books only focus on widespread details without going deeper into the different models and techniques, Python Machine Learning explains how to master the concepts of Machine Learning technology and helps you to understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines using various Machine Learning algorithms. Even if some concepts of Machine Learning algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Would You Like To Know More? Scroll to the top of the page and click the "Buy now" button to get your copy now!

Machine Learning Made Easy: A Beginner's Guide for All

Author : M.B. Chatfield
Publisher : M.B. Chatfield
ISBN 13 :
Total Pages : 258 pages
Book Rating : 4./5 ( download)

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Book Synopsis Machine Learning Made Easy: A Beginner's Guide for All by : M.B. Chatfield

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.

Machine Learning

Author : Andrew Park
Publisher :
ISBN 13 :
Total Pages : 350 pages
Book Rating : 4.6/5 (21 download)

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Book Synopsis Machine Learning by : Andrew Park

Download or read book Machine Learning written by Andrew Park and published by . This book was released on 2020-01-21 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the world of Machine Learning and Data Science with this comprehensive 2-in-1 bundle. If 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 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 procedures that must be implemented when working with 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 concepts of Machine Learning 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 book 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 on the BUY NOW Button to Get Your Copy!

Machine Learning

Author : Andrew Park
Publisher :
ISBN 13 : 9781914167553
Total Pages : 250 pages
Book Rating : 4.1/5 (675 download)

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Book Synopsis Machine Learning by : Andrew Park

Download or read book Machine Learning written by Andrew Park and published by . This book was released on 2020-11-14 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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!

Azure Machine Learning A Complete Guide - 2020 Edition

Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9781867408079
Total Pages : 310 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Azure Machine Learning A Complete Guide - 2020 Edition by : Gerardus Blokdyk

Download or read book Azure Machine Learning A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-05-19 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Which machines fail the same way? What are other organizations looking to do next? Does it need to be trained on a set of data before it can provide conclusions? What is the best way to achieve the goal? Does machine learning support high availability? This breakthrough Azure Machine Learning self-assessment will make you the dependable Azure Machine Learning domain veteran by revealing just what you need to know to be fluent and ready for any Azure Machine Learning challenge. How do I reduce the effort in the Azure Machine Learning work to be done to get problems solved? How can I ensure that plans of action include every Azure Machine Learning task and that every Azure Machine Learning outcome is in place? How will I save time investigating strategic and tactical options and ensuring Azure Machine Learning costs are low? How can I deliver tailored Azure Machine Learning advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Azure Machine Learning essentials are covered, from every angle: the Azure Machine Learning self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Azure Machine Learning outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Azure Machine Learning practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Azure Machine Learning are maximized with professional results. Your purchase includes access details to the Azure Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Azure Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Adaptive Machine Learning A Complete Guide - 2020 Edition

Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9781867348078
Total Pages : 310 pages
Book Rating : 4.3/5 (48 download)

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Book Synopsis Adaptive Machine Learning A Complete Guide - 2020 Edition by : Gerardus Blokdyk

Download or read book Adaptive Machine Learning A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-05-08 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: How will you measure the results? Is there any additional Adaptive machine learning definition of success? What is out-of-scope initially? What are the estimated costs of proposed changes? What are you trying to prove to yourself, and how might it be hijacking your life and business success? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Adaptive Machine Learning investments work better. This Adaptive Machine Learning All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Adaptive Machine Learning Self-Assessment. Featuring 951 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Adaptive Machine Learning improvements can be made. In using the questions you will be better able to: - diagnose Adaptive Machine Learning projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Adaptive Machine Learning and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Adaptive Machine Learning Scorecard, you will develop a clear picture of which Adaptive Machine Learning areas need attention. Your purchase includes access details to the Adaptive Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Adaptive Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Supervised Machine Learning A Complete Guide - 2020 Edition

Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9781867330219
Total Pages : 310 pages
Book Rating : 4.3/5 (32 download)

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Book Synopsis Supervised Machine Learning A Complete Guide - 2020 Edition by : Gerardus Blokdyk

Download or read book Supervised Machine Learning A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-02-16 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: How is Supervised machine learning data gathered? What relationships among Supervised machine learning trends do you perceive? What Supervised machine learning data do you gather or use now? What are your most important goals for the strategic Supervised machine learning objectives? Is Supervised machine learning documentation maintained? This instant Supervised Machine Learning self-assessment will make you the accepted Supervised Machine Learning domain auditor by revealing just what you need to know to be fluent and ready for any Supervised Machine Learning challenge. How do I reduce the effort in the Supervised Machine Learning work to be done to get problems solved? How can I ensure that plans of action include every Supervised Machine Learning task and that every Supervised Machine Learning outcome is in place? How will I save time investigating strategic and tactical options and ensuring Supervised Machine Learning costs are low? How can I deliver tailored Supervised Machine Learning advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Supervised Machine Learning essentials are covered, from every angle: the Supervised Machine Learning self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Supervised Machine Learning outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Supervised Machine Learning practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Supervised Machine Learning are maximized with professional results. Your purchase includes access details to the Supervised Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Supervised Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Automated Machine Learning

Author : Joaquin Vanschoren
Publisher :
ISBN 13 : 9781013271663
Total Pages : 222 pages
Book Rating : 4.2/5 (716 download)

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Book Synopsis Automated Machine Learning by : Joaquin Vanschoren

Download or read book Automated Machine Learning written by Joaquin Vanschoren and published by . This book was released on 2020-10-08 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Machine Learning Automation with TPOT

Author : Dario Radecic
Publisher : Packt Publishing Ltd
ISBN 13 : 1800564961
Total Pages : 270 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Machine Learning Automation with TPOT by : Dario Radecic

Download or read book Machine Learning Automation with TPOT written by Dario Radecic and published by Packt Publishing Ltd. This book was released on 2021-05-07 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how TPOT can be used to handle automation in machine learning and explore the different types of tasks that TPOT can automate Key FeaturesUnderstand parallelism and how to achieve it in Python.Learn how to use neurons, layers, and activation functions and structure an artificial neural network.Tune TPOT models to ensure optimum performance on previously unseen data.Book Description The automation of machine learning tasks allows developers more time to focus on the usability and reactivity of the software powered by machine learning models. TPOT is a Python automated machine learning tool used for optimizing machine learning pipelines using genetic programming. Automating machine learning with TPOT enables individuals and companies to develop production-ready machine learning models cheaper and faster than with traditional methods. With this practical guide to AutoML, developers working with Python on machine learning tasks will be able to put their knowledge to work and become productive quickly. You'll adopt a hands-on approach to learning the implementation of AutoML and associated methodologies. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will show you how to build automated classification and regression models and compare their performance to custom-built models. As you advance, you'll also develop state-of-the-art models using only a couple of lines of code and see how those models outperform all of your previous models on the same datasets. By the end of this book, you'll have gained the confidence to implement AutoML techniques in your organization on a production level. What you will learnGet to grips with building automated machine learning modelsBuild classification and regression models with impressive accuracy in a short timeDevelop neural network classifiers with AutoML techniquesCompare AutoML models with traditional, manually developed models on the same datasetsCreate robust, production-ready modelsEvaluate automated classification models based on metrics such as accuracy, recall, precision, and f1-scoreGet hands-on with deployment using Flask-RESTful on localhostWho this book is for Data scientists, data analysts, and software developers who are new to machine learning and want to use it in their applications will find this book useful. This book is also for business users looking to automate business tasks with machine learning. Working knowledge of the Python programming language and beginner-level understanding of machine learning are necessary to get started.

Building Machine Learning Pipelines

Author : Hannes Hapke
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492053147
Total Pages : 398 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Building Machine Learning Pipelines by : Hannes Hapke

Download or read book Building Machine Learning Pipelines written by Hannes Hapke and published by "O'Reilly Media, Inc.". This book was released on 2020-07-13 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques

Machine Learning

Author : Oliver Tensor
Publisher :
ISBN 13 : 9781687763105
Total Pages : 368 pages
Book Rating : 4.7/5 (631 download)

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Book Synopsis Machine Learning by : Oliver Tensor

Download or read book Machine Learning written by Oliver Tensor and published by . This book was released on 2019-08-21 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to learn the progress made in the web marketing space and how you can exploit it for your marketing strategies? Do you want to gain an edge over your business's competitors?If you want to know How Machine Learning and Artificial Intelligence Technology can give your business a major performance boost, then keep reading. The Fourth Industrial Revolution is upon us, led by the Artificial Intelligence technology and setting the humankind for a global social transformation. The powerful applications of AI have already transformed our daily lives. Tools such as virtual personal and home assistants (like Siri in Apple Pods and Alexa in Amazon Echo) have become everyday usage products. Moreover, our digital lives have inundated organizations with astronomical volumes of data with hidden treasures of valuable insights. This information can be uncovered with the use of big data analytics and applied in combination with the Artificial Intelligence technology to increase your business performance efficiency. Learning to incorporate the Artificial Intelligence applications, Machine Learning, and Big Data Analytics in line with your company's domain can only give your business positive results. Machine Learning: The Definive Guide includes 3 books - Machine Learning for Beginners - Artificial Intelligence Business Applications - Artificial Intelligence and Machine Learning for Business Our aim with this book is to provide you a 360 view of the fundamentals and importance of Machine Learning and Artificial Intelligence Technology. You Will Learn: The Fundamentals of Artificial Intelligence and Machine Learning Applications, and Why are They so Important in the World Today. Gain an In-depth Understanding of 12 of the Most Popular Artificial Intelligence Tools in the Market, in an Easy to Understand and Colloquial Language. The Science of Big Data and How Companies are Increasingly Employing Good Analytical Tools to Makes Sense of an Estimated 1.7 MB of Data that will be Generated per Second per Person by 2020. What Different Types of Machine Learning Algorithms are and How They Work to Make Machines Able to Learn and Train themselves with Repeated Use. Even if you are a beginner, you will be armed to make sound personal and professional technological choices. Would You Like to Know More? Download Now to get access to Artificial Intelligence power. Scroll to the top of the page and select BUY NOW button