Statistik Praktis Untuk Developer Dan Data Science
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Statistik Praktis Untuk Developer Dan Data Science
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Author : Agus Kurniawan
language : id
Publisher: Ilmu Data Publisher
Release Date :
Statistik Praktis Untuk Developer Dan Data Science written by Agus Kurniawan and has been published by Ilmu Data Publisher this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Dalam era digital yang penuh dengan data, kemampuan untuk memahami dan menerapkan prinsip statistik telah menjadi kebutuhan esensial bagi developer dan praktisi data science. "Statistik Praktis untuk Developer dan Data Science" menawarkan panduan komprehensif yang menggabungkan teori dan praktik, dirancang khusus untuk mereka yang bekerja di ranah teknologi. Mulai dari konsep dasar statistik, eksplorasi data, hingga penerapan statistik dalam machine learning dan pengembangan software, buku ini menyediakan alat dan teknik yang diperlukan untuk mengambil keputusan berdasarkan data. Dilengkapi dengan contoh kode dalam Python, latihan, dan studi kasus, buku ini menjadi sumber daya yang tak ternilai bagi siapa saja yang ingin mendalami peran statistik di dunia teknologi modern.
Pengantar Data Science
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Author : Grasberg Nahumarury
language : id
Publisher: Penerbit Andi
Release Date : 2025-07-30
Pengantar Data Science written by Grasberg Nahumarury and has been published by Penerbit Andi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-30 with Computers categories.
Data science merupakan bidang ilmu yang berfokus pada ekstraksi pengetahuan dan wawasan dari data. Tentunya ini melibatkan penggunaan berbagai teknik dan alat untuk menganalisis data, baik terstruktur maupun tidak terstruktur, untuk mengidentifikasi pola, tren, dan wawasan yang berguna untuk pengambilan keputusan. Dalam buku ini, pembaca dapat mempelajari berbagai konsep dasar dalam data sains, seperti pengumpulan dan pengolahan data, teknik analisis data, serta interpretasi data. Buku ini dirancang dengan bahasa yang mudah dipahami oleh siapa saja, tanpa memandang latar belakang pendidikan atau pengalaman kerja. Buku ini juga dilengkapi dengan contoh kasus dan latihan soal yang dapat membantu pembaca memahami konsep-konsep tersebut secara lebih mendalam. Dengan membaca buku ini, pembaca akan memiliki pemahaman yang lebih baiktentang data sains dan dapat menerapkannya dalam kehidupan sehari-hari.
Software Engineering With Uml
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Author : Bhuvan Unhelkar
language : en
Publisher: CRC Press
Release Date : 2017-12-14
Software Engineering With Uml written by Bhuvan Unhelkar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-14 with Computers categories.
This book presents the analysis, design, documentation, and quality of software solutions based on the OMG UML v2.5. Notably it covers 14 different modelling constructs including use case diagrams, activity diagrams, business-level class diagrams, corresponding interaction diagrams and state machine diagrams. It presents the use of UML in creating a Model of the Problem Space (MOPS), Model of the Solution Space (MOSS) and Model of the Architectural Space (MOAS). The book touches important areas of contemporary software engineering ranging from how a software engineer needs to invariably work in an Agile development environment through to the techniques to model a Cloud-based solution.
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
Applied Spatial Data Analysis With R
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Author : Roger S. Bivand
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-24
Applied Spatial Data Analysis With R written by Roger S. Bivand 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 2008-08-24 with Medical categories.
We began writing this book in parallel with developing software for handling and analysing spatial data withR (R Development Core Team, 2008). - though the book is now complete, software development will continue, in the R community fashion, of rich and satisfying interaction with users around the world, of rapid releases to resolve problems, and of the usual joys and frust- tions of getting things done. There is little doubt that without pressure from users, the development ofR would not have reached its present scale, and the same applies to analysing spatial data analysis withR. It would, however, not be su?cient to describe the development of the R project mainly in terms of narrowly de?ned utility. In addition to being a communityprojectconcernedwiththedevelopmentofworld-classdataana- sis software implementations, it promotes speci?c choices with regard to how data analysis is carried out.R is open source not only because open source software development, including the dynamics of broad and inclusive user and developer communities, is arguably an attractive and successful development model.
Neuromarketing In India
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Author : Tanusree Dutta
language : en
Publisher: Routledge
Release Date : 2018-06-27
Neuromarketing In India written by Tanusree Dutta and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-27 with Business & Economics categories.
How to understand human behaviour has been a very intriguing question to medicine, computer science, economics, psychology and finance. Each discipline has been trying to study and predict human behaviour through surveys, laboratory-based experiments, questionnaires, interviews, statistics, focus groups; the list is endless. The lack of precision in the existing techniques to predict human behaviour has motivated researchers to move beyond the traditional and search for new and improved techniques. Neuroscience has stepped in to fill this gap. It is based on the assumption that human behaviour is a complex process which has a neural basis and the locus of this process is the higher centre of the brain. Both conscious and unconscious processing of stimulus in the brain is responsible for generating behaviour. So if we could develop a deeper understanding of how the brain functions to generate behaviour, we would be more confident in our understanding and prediction of consumer behaviour. The use of neuroscientific techniques, like functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), Evoked Response Potential (ERP), and sensors to measure changes in one's physiological state, to understand the mind of the consumer has just begun, and professionals in the field see a huge opportunity for neuromarketing in India. In the domain of neuromarketing, one important question relates to the distinction between Indian and other global consumers of commercial products. Are we different from consumers across the globe? The answer is probably ‘yes’. This is documented by the fact that we find a distinct change in the marketing strategy of companies; the methods to influence Indian consumers are different from those adopted in other countries. This gives rise to the question: what makes us different? The next logical question that arises, assuming that we are different or similar, is can we quantify it? Answering why, what and how we are different marks the beginning of the book, followed by issues related to the ethicality of using such techniques to promote marketing, risk analysis in case of failure and future directions in neuromarketing. The book intends to address each of these issues so that a comprehensive reading in the subject matter would help academicians to decipher consumer behaviour and build theory for possible principles of application in the market.
Python Data Science Handbook
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Author : Jake VanderPlas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-11-21
Python Data Science Handbook written by Jake VanderPlas 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 2016-11-21 with Computers categories.
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Text Mining With R
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Author : Julia Silge
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-06-12
Text Mining With R written by Julia Silge 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 2017-06-12 with Computers categories.
Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document’s most important terms with frequency measurements Explore relationships and connections between words with the ggraph and widyr packages Convert back and forth between R’s tidy and non-tidy text formats Use topic modeling to classify document collections into natural groups Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages
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.
Streaming Systems
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Author : Tyler Akidau
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-07-16
Streaming Systems written by Tyler Akidau 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 2018-07-16 with Computers categories.
Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra