Pendekatan Machine Learning Panduan Praktis Melalui Data Besar Dan Analisis Regresi
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Pendekatan Machine Learning Panduan Praktis Melalui Data Besar Dan Analisis Regresi
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Author : Noviyanti. P, S.Kom., M.Kom.
language : id
Publisher: Uwais Inspirasi Indonesia
Release Date : 2025-03-12
Pendekatan Machine Learning Panduan Praktis Melalui Data Besar Dan Analisis Regresi written by Noviyanti. P, S.Kom., M.Kom. and has been published by Uwais Inspirasi Indonesia this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-12 with Antiques & Collectibles categories.
PENDEKATAN MACHINE LEARNING: Panduan Praktis Melalui Data Besar dan Analisis Regresi Buku ini dirancang untuk memberikan pemahaman mendalam tentang penerapan Machine Learning dalam pengolahan data besar. Ditujukan bagi mahasiswa, peneliti, dan praktisi yang tertarik mengintegrasikan pendekatan Machine Learning dalam berbagai studi kasus, buku ini menawarkan panduan praktis yang mencakup: Dasar-dasar machine learning Analisis regresi Pemrosesan data skala besar Penerapan studi kasus Evaluasi dan validasi model machine learning Melalui pembahasan yang sistematis dan ilustrasi nyata, buku ini membantu pembaca memahami bagaimana Machine Learning dapat digunakan untuk menghasilkan wawasan dari data besar, sekaligus mempermudah proses analisis menggunakan metode yang telah teruji. Buku ini cocok bagi siapa saja yang ingin menguasai metode machine learning untuk mendukung pengambilan keputusan berbasis data di era digital.
Analisis Kuantitatif Dan Panduan Praktis Business Intelligence Damera Press
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Author : Rd. Heri Solehudin
language : id
Publisher: Damera Press
Release Date : 2025-03-13
Analisis Kuantitatif Dan Panduan Praktis Business Intelligence Damera Press written by Rd. Heri Solehudin and has been published by Damera Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Education categories.
Buku ini memaparkan analisis kuantitatif dan panduan praktis business intelligence.Analisis kuantitatif memainkan peran penting dalam pengambilan keputusan dan pengembangan strategi yang efektif di dunia bisnis. Dalam era informasi yang semakin berkembang pesat ini, kebutuhan akan sumber daya manusia yang tidak hanya memahami teori, tetapi juga memiliki keterampilan praktis dalam menganalisis data serta mengelola informasi bisnis sangatlah mendesak. Buku ini dirancang untuk menjawab kebutuhan tersebut dengan memberikan pembaca pengetahuan dan keterampilan yang diperlukan untuk menjadi analis bisnis yang andal dan inovatif.
Data Lake Architecture
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Author : Bill Inmon
language : en
Publisher:
Release Date : 2016
Data Lake Architecture written by Bill Inmon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Big data categories.
Data Lake Architecture will explain how to build a useful data lake, where data scientists and data analysts can solve business challenges and identify new business opportunities
All Of Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11
All Of Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Mathematics categories.
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Introduction To Data Science
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Author : Rafael A. Irizarry
language : en
Publisher: CRC Press
Release Date : 2019-11-12
Introduction To Data Science written by Rafael A. Irizarry and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-12 with Mathematics categories.
Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert. A complete solutions manual is available to registered instructors who require the text for a course.
Advanced Rails
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Author : Brad Ediger
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2007-12-21
Advanced Rails written by Brad Ediger and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-21 with Computers categories.
Ready to go to the next level with Rails? From examining the parts of Ruby that make this framework possible to deploying large Rails applications, Advanced Rails offers you an in-depth look at techniques for dealing with databases, security, performance, web services and much more. Chapters in this book help you understand not only the tricks and techniques used within the Rails framework itself, but also how to make use of ideas borrowed from other programming paradigms. Advanced Rails pays particular attention to building applications that scale -- whether "scale" means handling more users, or working with a bigger and more complex database. You'll find plenty of examples and code samples that explain: Aspects of Ruby that are often confusing or misunderstood Metaprogramming How to develop Rails plug-ins Different database management systems Advanced database features, including triggers, rules, and stored procedures How to connect to multiple databases When to use the Active Support library for generic, reusable functions Security principles for web application design, and security issues endemic to the Web When and when not to optimize performance Why version control and issue tracking systems are essential to any large or long-lived Rails project Advanced Rails also gives you a look at REST for developing web services, ways to incorporate and extend Rails, how to use internationalization, and many other topics. If you're just starting out with rails, or merely experimenting with the framework, this book is not for you. But if you want to improve your skills with Rails through advanced techniques, this book is essential.
Math Adventures With Python
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Author : Peter Farrell
language : en
Publisher:
Release Date : 2019
Math Adventures With Python written by Peter Farrell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Mathematics categories.
Math Adventures with Python will show you how to harness the power of programming to keep math relevant and fun. With the aid of the Python programming language, you'll learn how to visualize solutions to a range of math problems as you use code to explore key mathematical concepts like algebra, trigonometry, matrices, and cellular automata. Once you've learned the programming basics like loops and variables, you'll write your own programs to solve equations quickly, make cool things like an interactive rainbow grid, and automate tedious tasks like factoring numbers and finding square roots. You'll learn how to write functions to draw and manipulate shapes, create oscillating sine waves, and solve equations graphically. You'll also learn how to: -Draw and transform 2D and 3D graphics with matrices -Make colorful designs like the Mandelbrot and Julia sets with complex numbers -Use recursion to create fractals like the Koch snowflake and the Sierpinski triangle -Generate virtual sheep that graze on grass and multiply autonomously -Crack secret codes using genetic algorithms As you work through the book's numerous examples and increasingly challenging exercises, you'll code your own solutions, create beautiful visualizations, and see just how much more fun math can be!
A Primer On Scientific Programming With Python
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Author : Hans Petter Langtangen
language : en
Publisher: Springer
Release Date : 2014-08-01
A Primer On Scientific Programming With Python written by Hans Petter Langtangen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-01 with Computers categories.
The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012
Data Science And Big Data Analytics
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Author : EMC Education Services
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-27
Data Science And Big Data Analytics written by EMC Education Services and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-27 with Computers categories.
Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
Markov Logic
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Author : Pedro Domingos
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2009
Markov Logic written by Pedro Domingos and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit. Inference algorithms for Markov logic combine ideas from satisfiability, Markov chain Monte Carlo, belief propagation, and resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been successfully applied to problems in information extraction and integration, natural language processing, robot mapping, social networks, computational biology, and others, and is the basis of the open-source Alchemy system.