Agile Machine Learning With Datarobot PDF Download
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| Author | : Bipin Chadha |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 345 |
| Release | : 2021-12-24 |
| Genre | : Computers |
| ISBN | : 1801078645 |
Download Agile Machine Learning with DataRobot Book in PDF, ePub and Kindle
Leverage DataRobot's enterprise AI platform and automated decision intelligence to extract business value from data Key FeaturesGet well-versed with DataRobot features using real-world examplesUse this all-in-one platform to build, monitor, and deploy ML models for handling the entire production life cycleMake use of advanced DataRobot capabilities to programmatically build and deploy a large number of ML modelsBook Description DataRobot enables data science teams to become more efficient and productive. This book helps you to address machine learning (ML) challenges with DataRobot's enterprise platform, enabling you to extract business value from data and rapidly create commercial impact for your organization. You'll begin by learning how to use DataRobot's features to perform data prep and cleansing tasks automatically. The book then covers best practices for building and deploying ML models, along with challenges faced while scaling them to handle complex business problems. Moving on, you'll perform exploratory data analysis (EDA) tasks to prepare your data to build ML models and ways to interpret results. You'll also discover how to analyze the model's predictions and turn them into actionable insights for business users. Next, you'll create model documentation for internal as well as compliance purposes and learn how the model gets deployed as an API. In addition, you'll find out how to operationalize and monitor the model's performance. Finally, you'll work with examples on time series forecasting, NLP, image processing, MLOps, and more using advanced DataRobot capabilities. By the end of this book, you'll have learned to use DataRobot's AutoML and MLOps features to scale ML model building by avoiding repetitive tasks and common errors. What you will learnUnderstand and solve business problems using DataRobotUse DataRobot to prepare your data and perform various data analysis tasks to start building modelsDevelop robust ML models and assess their results correctly before deploymentExplore various DataRobot functions and outputs to help you understand the models and select the one that best solves the business problemAnalyze a model's predictions and turn them into actionable insights for business usersUnderstand how DataRobot helps in governing, deploying, and maintaining ML modelsWho this book is for This book is for data scientists, data analysts, and data enthusiasts looking for a practical guide to building and deploying robust machine learning models using DataRobot. Experienced data scientists will also find this book helpful for rapidly exploring, building, and deploying a broader range of models. The book assumes a basic understanding of machine learning.
| Author | : Eric Carter |
| Publisher | : Apress |
| Total Pages | : 257 |
| Release | : 2019-08-21 |
| Genre | : Computers |
| ISBN | : 1484251075 |
Download Agile Machine Learning Book in PDF, ePub and Kindle
Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto. Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists both contributing expertise in their respective fields, communication alone can be a challenge. Agile Machine Learning teaches you how to deliver superior data products through agile processes and to learn, by example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment. The authors’ approach models the ground-breaking engineering principles described in the Agile Manifesto. The book provides further context, and contrasts the original principles with the requirements of systems that deliver a data product. What You'll Learn Effectively run a data engineering team that is metrics-focused, experiment-focused, and data-focused Make sound implementation and model exploration decisions based on the data and the metrics Know the importance of data wallowing: analyzing data in real time in a group setting Recognize the value of always being able to measure your current state objectively Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations Who This Book Is For Anyone who manages a machine learning team, or is responsible for creating production-ready inference components. Anyone responsible for data project workflow of sampling data; labeling, training, testing, improving, and maintaining models; and system and data metrics will also find this book useful. Readers should be familiar with software engineering and understand the basics of machine learning and working with data.
| Author | : Robert Keane |
| Publisher | : Createspace Independent Publishing Platform |
| Total Pages | : 238 |
| Release | : 2017-12-04 |
| Genre | : |
| ISBN | : 9781981383443 |
Download Data Analytics Book in PDF, ePub and Kindle
This Book Includes 3 Manuscripts Data Analytics Master The Techniques For Data Science, Big Data And Data Analytics If your business is like most, it is already generating a staggering amount of data on a regular basis. Understanding what this data truly means is key to succeeding in the marketplace these days and if you are looking for a way to give yourself an edge then Data Analytics is the book you have been waiting for. Inside this book you will find: Everything you need to know to get started completing the right kind of data analysis to benefit your business regardless of what that business is The best ways to utilize predictive analysis effectively Easy to use machine learning and regression techniques The reasons why you need discrete choice models in your life Agile Project Management Focus On Continuous Improvement, Scope Flexibility, Team Input, And Delivering Essential Quality Products Agile Project Management has grown in popularity over the past several years. Change is occurring so fast that many organizations are unable to keep up with the demands of a changing global world. Your ability to quickly change and adapt to your environment will make or break, not only your career but could be the deciding factor as to whether your company survives in the coming years. Those that have implemented the Agile strategies you will learn in this book are the ones that are succeeding and will be around for years to come. Look around at your peers. How many of them are looking to take that next step? The answer is probably very few but not you. You are an action taker. The fact that you are looking for a book like this says so. Here is some of what you will learn: The Benefits of Agile for you and your organization Agile strategy and making Agile work within an organization What is Scrum and how to implement it Explanation of ITIL and how it relates to Agile Tools of the trade Case Studies to show you Agile in action And an added BONUS - THE SECRET WEAPON Machine Learning Master The Three Types Of Machine Learning Machine learning is vital to the world of information technology. While many people may have no idea what machine learning is, they have probably used it sometime in their daily lives. For example, if you have ever done a search query on a search engine, you have worked with one form of machine learning. The program to do your search query has been trained to find the best results based on what you are looking for and it will also learn from the choices that you make. In this book you will find: Understanding the Basics of Machine Learning Why should I Use Machine Learning? Machine Learning Applications How Artificial Intelligence and Machine Learning are Different Statistics and Probability Theory The Building Blocks of Machine Learning Formal Statistical Learning Framework PAC Learning Strategies Generalization Models in Machine Learning Supervised Machine Learning Unsupervised Machine Learning Support Vector Machines Issues That Can Come Up In Machine Learning Now is the time! Get started on your Project Management journey today. Scroll Up And Click The "BUY" Button!
| Author | : Kai R. Larsen |
| Publisher | : Oxford University Press |
| Total Pages | : 400 |
| Release | : 2021-05-27 |
| Genre | : Business & Economics |
| ISBN | : 0190941685 |
Download Automated Machine Learning for Business Book in PDF, ePub and Kindle
Teaches the machine learning process for business students and professionals using automated machine learning, a new development in data science that requires only a few weeks to learn instead of years of training Though the concept of computers learning to solve a problem may still conjure thoughts of futuristic artificial intelligence, the reality is that machine learning algorithms now exist within most major software, including Websites and even word processors. These algorithms are transforming society in the most radical way since the Industrial Revolution, primarily through automating tasks such as deciding which users to advertise to, which machines are likely to break down, and which stock to buy and sell. While this work no longer always requires advanced technical expertise, it is crucial that practitioners and students alike understand the world of machine learning. In this book, Kai R. Larsen and Daniel S. Becker teach the machine learning process using a new development in data science: automated machine learning (AutoML). AutoML, when implemented properly, makes machine learning accessible by removing the need for years of experience in the most arcane aspects of data science, such as math, statistics, and computer science. Larsen and Becker demonstrate how anyone trained in the use of AutoML can use it to test their ideas and support the quality of those ideas during presentations to management and stakeholder groups. Because the requisite investment is a few weeks rather than a few years of training, these tools will likely become a core component of undergraduate and graduate programs alike. With first-hand examples from the industry-leading DataRobot platform, Automated Machine Learning for Business provides a clear overview of the process and engages with essential tools for the future of data science.
| Author | : Doug Rose |
| Publisher | : FT Press |
| Total Pages | : 292 |
| Release | : 2020-12-09 |
| Genre | : Business & Economics |
| ISBN | : 0136556663 |
Download Artificial Intelligence for Business Book in PDF, ePub and Kindle
The Easy Introduction to Machine Learning (Ml) for Nontechnical People--In Business and Beyond Artificial Intelligence for Business is your plain-English guide to Artificial Intelligence (AI) and Machine Learning (ML): how they work, what they can and cannot do, and how to start profiting from them. Writing for nontechnical executives and professionals, Doug Rose demystifies AI/ML technology with intuitive analogies and explanations honed through years of teaching and consulting. Rose explains everything from early “expert systems” to advanced deep learning networks. First, Rose explains how AI and ML emerged, exploring pivotal early ideas that continue to influence the field. Next, he deepens your understanding of key ML concepts, showing how machines can create strategies and learn from mistakes. Then, Rose introduces current powerful neural networks: systems inspired by the structure and function of the human brain. He concludes by introducing leading AI applications, from automated customer interactions to event prediction. Throughout, Rose stays focused on business: applying these technologies to leverage new opportunities and solve real problems. Compare the ways a machine can learn, and explore current leading ML algorithms Start with the right problems, and avoid common AI/ML project mistakes Use neural networks to automate decision-making and identify unexpected patterns Help neural networks learn more quickly and effectively Harness AI chatbots, virtual assistants, virtual agents, and conversational AI applications
| Author | : Geada, Nuno |
| Publisher | : IGI Global |
| Total Pages | : 280 |
| Release | : 2023-03-21 |
| Genre | : Business & Economics |
| ISBN | : 1668467887 |
Download Enhancing Business Communications and Collaboration Through Data Science Applications Book in PDF, ePub and Kindle
Digital evolution has become increasingly present in our lives, whether on cellphones, computers, watches, or other appliances. As a result of the wide access we have to the digital world, the amount of data generated daily is vast. This density of information generated at every moment can be the insight needed for the success of an organization. Much is said about data-based decision-making to generate the best results. The new capabilities of data intelligence unleashed by the emergence of cloud computing and artificial intelligence make it one of the most promising areas of digital transformation change management. Enhancing Business Communications and Collaboration Through Data Science Applications provides relevant theoretical frameworks and the latest empirical research findings in the area. It is written for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. Covering topics such as data science, online business communication, and user-centered design, this premier reference source is an ideal resource for business managers and leaders, entrepreneurs, data scientists, data analysts, sociologists, students and educators of higher education, librarians, researchers, and academicians.
| Author | : Carlo Appugliese |
| Publisher | : |
| Total Pages | : 51 |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
Download Agile AI Book in PDF, ePub and Kindle
As more companies work to adopt AI for business processes, project costs and failure rates are on the rise. Why? No standard practice exists for implementing AI in business applications, and many organizations don't have the skills, processes, and tools to mitigate risk. With this practical report, industry experts Carlo Appugliese, Paco Nathan, and William S. Roberts teach you Agile AI to help you innovate, reduce required investments, and decrease failure risk. Written for technical leaders as well as tech-savvy business cohorts with an understanding of analytics, software engineering, and data science, this report from IBM is useful for anyone interested in an Agile approach to AI and machine learning at the enterprise level. You'll quickly learn how to choose the approach that works best for your company. Fundamentals: Explore data science and AI tools, including the trends in and risks of machine learning AI skills: Examine core skills in data science, as well as effective practices for building a data science team and nurturing a supportive culture Agile approach: Focus on the right team mind-set of flexibility, the right set of tools, and the right set of team skills.
| Author | : Vyas Manju |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023-09-02 |
| Genre | : Computers |
| ISBN | : 9781916706910 |
Download Machine Learning Approach for Cost and Effort Estimation in Agile Development Process Book in PDF, ePub and Kindle
Software project management is a key area in the field of computer science as software now-a-days impacts every area related to human life. Managing software means the process for development and the maintenance of software must be completely controlled using various pre-defined set of rules. As the software development process has to follow various parameters and a well-defined life cycle to ultimately deliver all the requirements gathered from the customers hence it has become quite time consuming and expensive process. It is also an evident fact that failure in software is caused mainly due to faulty practices used in project management. Using the right and optimised practices for software management helps both client as well as developers. Because of all the factors the need for highly reliable software is increasing. The reliability of software is mainly dependent on two factors: the selection of proper model for development and the estimation of various parameters. During the last few decades, the former area has been a research interest for many researchers resulting in development of many reliability models. Hence, currently parameter estimation is considered to be a primary activity in software reliability prediction and broadly the most important aspect of software project management. Software reliability models only become useful if they provide a correct and optimal estimation of various parameters. A successfully completed project means that the project is developed within the planned budget and timeline which is mostly related to accurate effort and cost estimation whereas inaccurate estimation of effort and cost results in failure of a project in context of delivery time, cost and other parameters. Hence the most important parameters requiring accurate estimate in terms of software projects are effort and cost. The accuracy of the estimation of these two vital parameters depends on the correct estimation of size of the project to be developed, and the ability to convert the size estimate into man hours, duration and cost.
| Author | : Luis Sobrecueva |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 194 |
| Release | : 2021-05-21 |
| Genre | : Computers |
| ISBN | : 1800561814 |
Download Automated Machine Learning with AutoKeras Book in PDF, ePub and Kindle
Create better and easy-to-use deep learning models with AutoKeras Key FeaturesDesign and implement your own custom machine learning models using the features of AutoKerasLearn how to use AutoKeras for techniques such as classification, regression, and sentiment analysisGet familiar with advanced concepts as multi-modal, multi-task, and search space customizationBook Description AutoKeras is an AutoML open-source software library that provides easy access to deep learning models. If you are looking to build deep learning model architectures and perform parameter tuning automatically using AutoKeras, then this book is for you. This book teaches you how to develop and use state-of-the-art AI algorithms in your projects. It begins with a high-level introduction to automated machine learning, explaining all the concepts required to get started with this machine learning approach. You will then learn how to use AutoKeras for image and text classification and regression. As you make progress, you'll discover how to use AutoKeras to perform sentiment analysis on documents. This book will also show you how to implement a custom model for topic classification with AutoKeras. Toward the end, you will explore advanced concepts of AutoKeras such as working with multi-modal data and multi-task, customizing the model with AutoModel, and visualizing experiment results using AutoKeras Extensions. By the end of this machine learning book, you will be able to confidently use AutoKeras to design your own custom machine learning models in your company. What you will learnSet up a deep learning workstation with TensorFlow and AutoKerasAutomate a machine learning pipeline with AutoKerasCreate and implement image and text classifiers and regressors using AutoKerasUse AutoKeras to perform sentiment analysis of a text, classifying it as negative or positiveLeverage AutoKeras to classify documents by topicsMake the most of AutoKeras by using its most powerful extensionsWho this book is for This book is for machine learning and deep learning enthusiasts who want to apply automated ML techniques to their projects. Prior basic knowledge of Python programming and machine learning is expected to get the most out of this book.
| Author | : Andrew Kelleher |
| Publisher | : |
| Total Pages | : |
| Release | : 2019 |
| Genre | : Cloud computing |
| ISBN | : 9780134116556 |
Download Machine Learning in Production Book in PDF, ePub and Kindle
