Analytics And Machine Learning A Complete Guide - 2019 Edition

Analytics And Machine Learning A Complete Guide - 2019 Edition
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 310
Release: 2019-07-31
Genre:
ISBN: 9780655835431
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What sources do you use to gather information for a Analytics and Machine Learning study? What is the Analytics and Machine Learning Driver? What will drive Analytics and Machine Learning change? Do you recognize Analytics and Machine Learning achievements? What are the Analytics and Machine Learning investment costs? 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 Analytics And Machine Learning investments work better. This Analytics And Machine Learning All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Analytics And Machine Learning Self-Assessment. Featuring 958 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Analytics And Machine Learning improvements can be made. In using the questions you will be better able to: - diagnose Analytics And 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 Analytics And Machine Learning and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Analytics And Machine Learning Scorecard, you will develop a clear picture of which Analytics And Machine Learning areas need attention. Your purchase includes access details to the Analytics And 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 Analytics And 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.

Grokking Deep Learning

Grokking Deep Learning
Author: Andrew W. Trask
Publisher: Simon and Schuster
Total Pages: 475
Release: 2019-01-23
Genre: Computers
ISBN: 163835720X
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Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide

A Practical Guide to Artificial Intelligence and Data Analytics

A Practical Guide to Artificial Intelligence and Data Analytics
Author: Rayan Wali
Publisher: Rayan Wali
Total Pages: 605
Release: 2021-06-12
Genre: Computers
ISBN:
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Whether you are looking to prepare for AI/ML/Data Science job interviews or you are a beginner in the field of Data Science and AI, this book is designed for engineers and AI enthusiasts like you at all skill levels. Taking a different approach from a traditional textbook style of instruction, A Practical Guide to AI and Data Analytics touches on all of the fundamental topics you will need to understand deeper into machine learning and artificial intelligence research, literature, and practical applications with its four parts: Part I: Concept Instruction Part II: 8 Full-Length Case Studies Part III: 50+ Mixed Exercises Part IV: A Full-Length Assessment With an illustrative approach to instruction, worked examples, and case studies, this easy-to-understand book simplifies many of the AI and Data Analytics key concepts, leading to an improvement of AI/ML system design skills.

Python Machine Learning for Beginners

Python Machine Learning for Beginners
Author: Leonard Deep
Publisher:
Total Pages: 236
Release: 2019-05-13
Genre:
ISBN: 9781097858309
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Are you interested to get into the programming world? Do you want to learn and understand Python and Machine Learning? Python Machine Learning for Beginners is the guide for you. Python Machine Learning for Beginners is the ultimate guide for beginners looking to learn and understand how Python programming works. Python Machine Learning for Beginners is split up into easy to learn chapters that will help guide the readers through the early stages of Python programming. It's this thought out and systematic approach to learning which makes Python Machine Learning for Beginners such a sought-after resource for those that want to learn about Python programming and about Machine Learning using an object-oriented programming approach. Inside Python Machine Learning for Beginners you will discover: An introduction to Machine Learning The main concepts of Machine Learning The basics of Python for beginners Machine Learning with Python Data Processing, Analysis, and Visualizations Case studies and much more! Throughout the book, you will learn the basic concepts behind Python programming which is designed to introduce you to Python programming. You will learn about getting started, the keywords and statements, data types and type conversion. Along with different examples, there are also exercises to help ensure that the information sinks in. You will find this book an invaluable tool for starting and mastering Machine Learning using Python. Once you complete Python Machine Learning for Beginners, you will be more than prepared to take on any Python programming. Scroll back up to the top of this page and hit BUY IT NOW to get your copy of Python Machine Learning for Beginners! You won't regret it!

Machine Learning

Machine Learning
Author: Oliver Tensor
Publisher:
Total Pages: 368
Release: 2019-08-21
Genre:
ISBN: 9781687763105
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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

Machine Learning

Machine Learning
Author: Steven Alex
Publisher:
Total Pages: 135
Release: 2019-11-06
Genre:
ISBN: 9781706195856
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★ ★ 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!

Deep Learning Illustrated

Deep Learning Illustrated
Author: Jon Krohn
Publisher: Addison-Wesley Professional
Total Pages: 725
Release: 2019-08-05
Genre: Computers
ISBN: 0135121728
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"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Machine Learning a Complete Guide - 2019 Edition

Machine Learning a Complete Guide - 2019 Edition
Author: Gerardus Blokdyk
Publisher: 5starcooks
Total Pages: 302
Release: 2018-12-21
Genre:
ISBN: 9780655519300
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What is the current state of the data? What is the relationship between different learning algorithms, and which should be used when? Can you use cloud-based data to train machine learning models? What rights should artificial beings have? How does knowledge lead to action? This powerful Machine Learning self-assessment will make you the credible Machine Learning domain auditor by revealing just what you need to know to be fluent and ready for any Machine Learning challenge. How do I reduce the effort in the Machine Learning work to be done to get problems solved? How can I ensure that plans of action include every Machine Learning task and that every Machine Learning outcome is in place? How will I save time investigating strategic and tactical options and ensuring Machine Learning costs are low? How can I deliver tailored 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 Machine Learning essentials are covered, from every angle: the Machine Learning self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Machine Learning outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced 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 Machine Learning are maximized with professional results. Your purchase includes access details to the 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 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.

Fundamentals of Machine Learning for Predictive Data Analytics, second edition

Fundamentals of Machine Learning for Predictive Data Analytics, second edition
Author: John D. Kelleher
Publisher: MIT Press
Total Pages: 853
Release: 2020-10-20
Genre: Computers
ISBN: 0262361108
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The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

Machine Learning

Machine Learning
Author: Mark Graph
Publisher: Independently Published
Total Pages: 239
Release: 2019-11-13
Genre:
ISBN: 9781708031510
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With the help of in-depth explanations, concepts and ideas regarding machine learning and artificial intelligence, beginners can develop basic AI models that are capable of making accurate predictions and data insights with the best performance. Thus, this book is most suitable for beginners who have an interest in methodologies of artificial intelligence and deep learning. Big data analytics and data sciences have brought a major breakthrough in the current world by introducing models that bring long-term benefits to businesses and industries. By understanding the algorithms and approaches explained in this book, beginners can develop state of the art machine learning models for solving real work problems. By reviewing possible challenges, performances and implementations of artificial intelligence, neural networks, big data analytics and deep learning, applications of AI can be developed to improve workflow and system efficiency as well. Moreover, industries and businesses can greatly promote their sales, profits and performance by considering the techniques and methods set out in this book. However, this book is not only for beginners. Researchers and experts can learn about the latest the findings on artificial intelligence and machine learning for developing powerful algorithms and models. Artificial intelligence and machine learning approaches will definitely help in bringing positive changes to our daily lives. For learning and adopting the major findings, rules and techniques of artificial intelligence and deep learning, reading "Machine Learning For Beginners: The Ultimate Guide to Understand Artificial Intelligence and Big Data Analytics. Learn the Building Block Algorithms and the Machine Learning's Application in the Modern Life" will surely prove to be of great benefit for students and researchers.