Algorithms Analytics the Ultimate Step-By-Step Guide PDF Download
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Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9780655533405
Category :
Languages : en
Pages : 282
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Book Description
Do several people in different organizational units assist with the Algorithms Analytics process? Who is the main stakeholder, with ultimate responsibility for driving Algorithms Analytics forward? Where is Algorithms Analytics data gathered? How do you manage Algorithms Analytics Knowledge Management (KM)? Are there any disadvantages to implementing Algorithms Analytics? There might be some that are less obvious? This one-of-a-kind Algorithms Analytics self-assessment will make you the accepted Algorithms Analytics domain standout by revealing just what you need to know to be fluent and ready for any Algorithms Analytics challenge. How do I reduce the effort in the Algorithms Analytics work to be done to get problems solved? How can I ensure that plans of action include every Algorithms Analytics task and that every Algorithms Analytics outcome is in place? How will I save time investigating strategic and tactical options and ensuring Algorithms Analytics costs are low? How can I deliver tailored Algorithms Analytics 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 Algorithms Analytics essentials are covered, from every angle: the Algorithms Analytics self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Algorithms Analytics outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Algorithms Analytics 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 Algorithms Analytics are maximized with professional results. Your purchase includes access details to the Algorithms Analytics 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 Algorithms Analytics 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.
Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9780655533405
Category :
Languages : en
Pages : 282
Get Book Here
Book Description
Do several people in different organizational units assist with the Algorithms Analytics process? Who is the main stakeholder, with ultimate responsibility for driving Algorithms Analytics forward? Where is Algorithms Analytics data gathered? How do you manage Algorithms Analytics Knowledge Management (KM)? Are there any disadvantages to implementing Algorithms Analytics? There might be some that are less obvious? This one-of-a-kind Algorithms Analytics self-assessment will make you the accepted Algorithms Analytics domain standout by revealing just what you need to know to be fluent and ready for any Algorithms Analytics challenge. How do I reduce the effort in the Algorithms Analytics work to be done to get problems solved? How can I ensure that plans of action include every Algorithms Analytics task and that every Algorithms Analytics outcome is in place? How will I save time investigating strategic and tactical options and ensuring Algorithms Analytics costs are low? How can I deliver tailored Algorithms Analytics 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 Algorithms Analytics essentials are covered, from every angle: the Algorithms Analytics self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Algorithms Analytics outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Algorithms Analytics 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 Algorithms Analytics are maximized with professional results. Your purchase includes access details to the Algorithms Analytics 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 Algorithms Analytics 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.
Author: Albert Torres
Publisher:
ISBN: 9781802673180
Category :
Languages : en
Pages : 186
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Book Description
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Author: Thomas H. Cormen
Publisher: MIT Press
ISBN: 0262258102
Category : Computers
Languages : en
Pages : 1313
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Book Description
The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.
Author: Mark Graph
Publisher: Independently Published
ISBN: 9781708031510
Category :
Languages : en
Pages : 239
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Book Description
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.
Author: Daneyal Anis
Publisher:
ISBN:
Category :
Languages : en
Pages : 68
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Book Description
*Start your Data Science career using Python today!* Are you ready to start your new exciting career? Ready to crush your machine learning career goals? Are you overwhelmed with complexity of the books on this subject?Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days! First part of this book introduces Python basics including: 1) Data Structures like Pandas 2) Foundational libraries like Numpy, Seaborn and Scikit-Learn Second part of this book shows you how to build predictive machine learning models step by step using techniques such as: 1) Regression analysis 2) Decision tree analysis 3) Training and testing data models 4) And much more! After reading this book you will be able to: 1) Code in Python with confidence 2) Build new machine learning models from scratch 3) Know how to clean and prepare your data for analytics 4) Speak confidently about statistical analysis techniques Data Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world! If you are on the fence about making the leap to a new and lucrative career, this is the book for you! What sets this book apart from other books on the topic of Python and Machine learning: 1) Step by step code examples and explanation 2) Complex concepts explained visually 3) Real world applicability of the machine learning models introduced 4) Bonus free code samples that you can try yourself without any prior experience in Python! What do I need to get started? You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and machine learning and start lucrative and rewarding career! Ready to dive in to the exciting world of Python and Machine Learning? Then scroll up to the top and hit that BUY BUTTON!
Author: ML and Ai Academy
Publisher:
ISBN:
Category :
Languages : en
Pages : 186
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Book Description
Are you looking for a complete guide of machine learning and artificial intelligence? Then you have found just the book you need to understand and master the fundamentals of machine learning and artificial intelligence technology to kick-start your business and master the Python programming language to develop a winning machine-learning model. With the rise of the modern-day smart customer, a competitive race has been ignited among the businesses that are starting to rely upon innovative technologies. The most important technologies are machine-learning, data mining technology, and artificial intelligence technology to gain an edge over the competition; resulting in high paying and rewarding jobs for people like you who have the in-demand machine learning technical skillset. However, performing a simple Google search on "what is machine learning?" unhinges a "Pandora's box" of forums, academic research, and hearsay. However, it is essentials to master the basics of these technologies as well as the basic concepts of Python coding and how you can utilize your coding skills to analyze a large volume of data and uncover valuable information that can otherwise be easily lost in the volume. Python was designed primarily to emphasize the readability of the programming code, and its syntax enables programmers to convey ideas using fewer lines of code. Python programming language increases the speed of operation while allowing for higher efficiency in creating system integrations. The power of programming languages in our digital world cannot be underestimated. Some of the highlights of this book include: Deep dive into the data mining process, the benefits of using data mining technology, the challenges facing the data mining technology and learn about some data mining tools that you can leverage for your business. Gain an in-depth understanding of various machine-learning algorithms do assess the best Machine-learning algorithm applicable to your business model. Dig deep into the development and application of some of the most popular supervised and unsupervised machine learning algorithms. Step by step instructions on how to install Python on your operating systems (Windows, Mac, and Linux). Basic concepts of writing efficient and effective Python codes, focusing on various programming elements such as Booleans, Tuples, Sets, Dictionaries, and much more. Learn everything you need to know for successful development and training of neural network models using one of the most popular machine learning libraries called "TensorFlow." Deep dive into the concept of personalized marketing, predictive analytics, customer analytics and exploratory data analysis presented with details on how you can make sense out of all your customer behavioral data. Remember knowledge is power, and with the great power you will gather from this book, you will be armed to make sound personal and professional technological choices. Your understanding of Python, Artificial Intelligence and machine learning will improve drastically, and you will be poised to develop your very own machine-learning model. Therefore, be a Good Samaritan, spread the word to your tech-savvy friends and family, and help them get access to this power! Even if you have never studied Python language before, you can learn it quickly. So what are you waiting for? Go to the top of the page and click Buy Now!
Author: Robert Sedgewick
Publisher: Addison-Wesley Professional
ISBN: 0133847268
Category : Computers
Languages : en
Pages : 973
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Book Description
This book is Part II of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part II contains Chapters 4 through 6 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.
Author: Rodney Anderson
Publisher:
ISBN: 9781983380747
Category : Computers
Languages : en
Pages : 130
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Book Description
An easy & simple guide to analyzing programs and algorithms using Big-O, Big Omega, & Big Theta, including cheat sheets and practice problems.
Author: Daneyal Anis
Publisher:
ISBN:
Category :
Languages : en
Pages : 200
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Book Description
*Start your Data Science career using Python today!*Are you ready to start your new exciting career? Ready to master artificial intelligence and deep learning concepts?Are you overwhelmed with complexity of the books on this subject?Then let this breezy and fun little book on Python, Machine Learning and Deep Learning models make you a Data Scientist in 7 days!This book continues from where the first book in the series, Ultimate Step by Step Guide to Machine Learning Using Python, left of. In the first book you were introduced to Python concepts such as: -Data Structures like Pandas -Foundational libraries like Numpy, Seaborn and Scikit-Learn-Regression analysis-Classification-Clustering-Association Learning-Dimension ReductionThis book builds on those concepts to expand on Machine Learning algorithms like: -Linear and Logistical regression-Decision tree-Support vector machines (SVM)After that, this book takes you on a journey into Deep Learning and Neural Networks with important concepts and libraries like: -Convolutional and Recurrent Neural Networks-TensorFlow-Keras-PyTorch-Keras-Apache MXNet-Microsoft Cognitive Toolkit (CNTK)The final part of the book covers all foundational concepts that are required for Amazon Web Services (AWS) Certified Machine Learning Specialization by explaining how to deploy your models at scale on Cloud technologies. While AWS is used in the book for illustrative purposes, Microsoft Azure and Google Cloud are also introduced as alternative cloud technologies. After reading this book you will be able to: -Code in Python with confidence-Build new machine learning and deep learning models from scratch-Know how to clean and prepare your data for analytics-Speak confidently about statistical analysis techniquesData Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world!If you are on the fence about making the leap to a new and lucrative career, this is the book for you!What sets this book apart from other books on the topic of Python and Machine learning: -Step by step code examples and explanation-Complex concepts explained visually-Real world applicability of the machine learning and deep learning models introducedWhat do I need to get started?You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and artificial intelligence and start a lucrative and rewarding career! Ready to dive in to the exciting world of Python and Deep Learning?Then scroll up to the top and hit that BUY BUTTON!
Author: Axel Ross
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Many people think that python, data science, machine learning, and artificial intelligence are difficult concepts to understand.You're fascinated by these topics, but don't you think you can understand them?Read on. Data science uses scientific strategies and Science to process data and separate information from it. It chips away at a similar idea as Big Data and Data Mining. It requires ground-breaking equipment alongside a useful calculation and programming to take care of the data issues or to process the data for acquiring meaningful learning from it. The present information patterns are giving us 80% of data in unstructured mannered while the rest 20% organized in organization for snappy dissecting. The unorganized or semi-organized details require processing to make it valuable for the present-day business person condition. For the most part, this information or details are produced from a wide assortment of sources, for example, content records, money-related logs, instruments and sensors, and sight and sound structures. Drawing important and profitable experiences from this information require propelled calculations and tools. This Science is proposing an offer for this purpose, and this is making it a useful science for the present-day mechanical world. The improvement and exceedingly useful inquire about in the world of Computer Science and Technology has made the importance of its most basic and essential concepts ascend by a thousand-crease. This principle concept is the thing that we have been everlastingly alluding to as data, and it is this data that solitary holds the way to everything in the world. The greatest of organizations and firms in the world have fabricated their establishment and philosophies and determined a unique piece of their pay totally through data. Fundamentally, the value and importance of data can be comprehended by the straightforward certainty that a legitimate store/distribution center of data is a million times more profitable than a mine of pure gold in the advanced world. Like this, the vast spread and escalated examines in the field of data has genuinely opened up a lot of potential outcomes and doors (as far as a calling) wherein curating such vast amounts of data are the absolute most lucrative employments a specialized individual can discover today. This guide will focus on the following: Applications and role of data scienceData science and applicationsGUI programming with Tkinter.Working with raw dataBuild your own sentiment analysis toolExploration of NLTKK-means clusteringOperations on dataVariable scope and lifetime in python functionsMachine learning & neural networksPrincipal components analysisSetting up your TensorFlow environmentAnd more! Don't miss the opportunity to learn more about these topics. The future has never been closer and the opportunities it offers are endless.Even if you are a beginner, if you are starting from scratch, this book will allow you to understand topics that you have already heard about and that fascinate you, but that you probably never had the courage to go into.This is the best time to start. Click the "Buy now" button!
