Data Science Untuk Pemula Dengan Rapidminer
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Data Science Untuk Pemula Dengan Rapidminer
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Author : Widarto Rachbini
language : id
Publisher: CV. AA. Rizky
Release Date : 2025-02-20
Data Science Untuk Pemula Dengan Rapidminer written by Widarto Rachbini and has been published by CV. AA. Rizky this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
"Data Science untuk Pemula dengan RapidMiner" adalah panduan praktis bagi siapa saja yang ingin memahami konsep dasar Sains Data (Data Science) dan penerapannya menggunakan RapidMiner, sebuah platform analisis data berbasis visual yang kuat dan intuitif, tanpa perlu koding. Buku ini dirancang untuk membantu pembaca, baik mahasiswa, peneliti, maupun praktisi, dalam mempelajari teknik pengolahan data, eksplorasi dataset, serta membangun model prediksi dan analisis klasifikasi. Dengan pendekatan yang sistematis dan berbasis studi kasus, pembaca akan diajak untuk memahami setiap tahapan dalam proses Data Science, mulai dari pengolahan data (data preparation), eksplorasi data, pemodelan machine learning, evaluasi model, hingga implementasi dalam pengambilan keputusan bisnis. Beberapa topik utama yang dibahas meliputi: ✅ Pengenalan Data Science dan Perannya di Era Digital ✅ Penggunaan RapidMiner sebagai Alat Data Mining Tanpa Koding ✅ Teknik Pemrosesan Data: Data Cleaning, Transformasi, dan Integrasi ✅ Pembangunan Model dengan Decision Tree, Regresi, Clustering, dan SVM ✅ Evaluasi Model dengan Metrik Akurasi, Precision-Recall, dan AUC-ROC ✅ Implementasi Studi Kasus di Berbagai Bidang, termasuk Bisnis dan Keuangan Buku ini dilengkapi dengan latihan praktis dan contoh dataset yang bisa diakses melalui olahdata.net atau dengan menghubungi [email protected] dan 0815-9696-995. Dengan bahasa yang mudah dipahami dan langkah-langkah yang jelas, buku ini sangat cocok bagi pemula yang ingin belajar Data Science secara efisien dan aplikatif.
Data Mining Dengan Python Untuk Pemula
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Author : Muhammad Fhadli & Firman Tempola
language : id
Publisher: SPASI MEDIA
Release Date :
Data Mining Dengan Python Untuk Pemula written by Muhammad Fhadli & Firman Tempola and has been published by SPASI MEDIA this book supported file pdf, txt, epub, kindle and other format this book has been release on with Antiques & Collectibles categories.
Data Mining Dengan Python Untuk Pemula PENULIS: Muhammad Fhadli & Firman Tempola Ukuran : 14 x 21 cm ISBN : 978-623-281-522-3 Terbit : Juli 2020 www.guepedia.com Sinopsis: Mulai dari bangun tidur sampai Anda tidur lagi, Anda tak bisa melepaskan diri dari data mining. Facebook yang selalu memberikan kabar ter-update, online shop yang selalu Anda buka setiap hari, bahkan pengaturan letak barang di supermarket adalah contoh penggunaan data yang nyata. Data mining mencoba membaca pola dan menyajikan informasi menarik tidak dapat dilihat secara kasat mata dari data yang sangat banyak. Hal tersebut tentunya dilakukan dengan algoritma-algoritma yang terus berkembang setiap hari. Pada tahun 2019, Glass door menjadikan data scientist pada urutan pertama sebagai pekerjaan terbaik dengan gaji sekitar $108.000 per tahun. Orang dari berbagai kalangan pun ikut berlomba memahami data mining yang merupakan inti dari data science. Jika Anda tidak berlari cepat, seberapa jauh lagi Anda akan tertinggal? Anda bukan seorang lulusan IT? Tenang, jangan panik dulu. Buku ini memang di desain khusus untuk semua kalangan. Buku ini tidak hanya membahas teori-teori yang definitif, tetapi juga perhitungan secara manual dan tentunya implementasi berupa source code python. Tugas dan contoh soal pada buku ini akan membuat Anda memahami teori dibalik data mining dengan cepat. Source code yang disajikan pada buku ini dijelaskan dengan sederhana sehingga semua kalangan bisa memahaminya dengan mudah. Siapa bilang hanya orang IT yang bisa paham data mining? Ayo buktikan! www.guepedia.com Email : [email protected] WA di 081287602508 Happy shopping & reading Enjoy your day, guys
Data Science Untuk Pemula
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Author : Dewi Retno Sari Saputro
language : id
Publisher: PT. Star Digital Publishing, Yogyakarta-Indonesia
Release Date : 2025-05-09
Data Science Untuk Pemula written by Dewi Retno Sari Saputro and has been published by PT. Star Digital Publishing, Yogyakarta-Indonesia this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-09 with Computers categories.
Buku Data Science Untuk Pemula : Teori, Penerapan, dan Implementasi merupakan panduan komprehensif bagi pembaca yang ingin memahami konsep dasar Data Science dan penerapannya. Buku ini membahas berbagai aspek penting, mulai dari pengenalan Data Science, dasar-dasar statistik, hingga teknik pengolahan dan manajemen data. Selain itu, pembaca juga akan diperkenalkan dengan metode visualisasi data serta konsep dasar Machine Learning yang menjadi inti dari perkembangan Data Science. Lebih dari sekadar teori, buku ini mengeksplorasi penerapan Data Science dalam berbagai bidang, seperti bisnis dan pemasaran, kesehatan, serta pengembangan Smart City dan IoT. Pembaca akan memahami bagaimana analisis data dapat digunakan untuk meningkatkan efisiensi bisnis, membantu pengambilan keputusan di sektor medis, serta mendukung pembangunan kota pintar yang lebih terintegrasi. Buku ini juga mengulas teknologi pendukung seperti Big Data dan infrastruktur yang mendukung analisis data berskala besar. Sebagai penutup, buku ini membahas best practices dalam pengembangan model Data Science serta peluang karier di bidang ini. Dengan pendekatan yang mudah dipahami, buku ini menjadi referensi tepat bagi pemula yang ingin menguasai Data Science dari teori hingga implementasi.
Data Driven Entrepreneur
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Author : Ivan Diryana Sudirman
language : id
Publisher: Penerbit Salemba
Release Date : 2023-11-08
Data Driven Entrepreneur written by Ivan Diryana Sudirman and has been published by Penerbit Salemba this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-08 with Computers categories.
Buku yang berjudul Data-Driven Entrepreneur: Bisnis Berdaya Saing dengan Data Science dan RapidMiner merupakan panduan penting bagi siapa pun yang ingin memanfaatkan kekuatan data dalam memajukan bisnis. Buku ini ditulis oleh seorang dosen dan pengusaha berpengalaman. Buku ini menjelaskan konsep-konsep dasar data science dan petunjuk penggunaan perangkat lunak RapidMiner untuk mengolah dan memahami data. Buku ini ditulis dengan bahasa yang mudah dipahami oleh masyarakat umum, khususnya para pebisnis dan pelaku Usaha Kecil dan Menengah (UKM), tanpa banyak berkutat di hal-hal teknis yang membingungkan. Melalui contoh-contoh aplikasi di berbagai bisnis, penulis berusaha menjembatani gap antara ilmu data science yang sering kali dianggap kompleks dengan kebutuhan praktis di lapangan. Buku ini tidak hanya memberikan teori, tetapi juga pengajaran praktis Structured Query Language (SQL) dan RapidMiner, dua alat yang penting dalam dunia data science. Pembaca akan dipandu untuk memahami pentingnya data dalam pengambilan keputusan bisnis, bagaimana mengolah data dengan SQL dan RapidMiner, serta cara menginterpretasikan hasil pengolahan data untuk kepentingan bisnis. Dilengkapi dengan kasus dan contoh yang sesuai dengan dunia bisnis, buku ini bukan hanya sebuah buku teori, tetapi merupakan panduan praktis untuk siapa pun yang ingin membuat bisnisnya lebih berdaya saing, khususnya di era digital. Melalui buku ini, kita akan belajar bahwa data bukanlah sekadar angka, tetapi kunci untuk memahami pasar dan meraih keberhasilan. Materi yang dibahas dalam buku ini mencakup: Bab 1 Memanfaatkan Data untuk Pengambilan Keputusan Bab 2 Data dan Kualitas Data Bab 3 Data dan Manajemen Data Bab 4 Structured Query Language Bab 5 Statistika_Tulang Punggung Data Science Bab 6 Mencari Wawasan dengan Data Mining Bab 7 Klasifikasi Menggunakan RapidMiner Bab 8 Regresi Linear Menggunakan RapidMiner Bab 9 Clustering dengan RapidMiner Bab 10 Prediksi Data Time-Series Bab 11 Analisis Asosiasi-Menemukan Koneksi Tersembunyi Bab 12 Text Mining dan Sentiment Analysis Bab 13 Neural Network Bab 14 Membangun Bisnis Berbasiskan Data
Becoming A Data Head
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Author : Alex J. Gutman
language : en
Publisher: John Wiley & Sons
Release Date : 2021-04-13
Becoming A Data Head written by Alex J. Gutman 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 2021-04-13 with Business & Economics categories.
"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful." Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage You've heard the hype around data - now get the facts. In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.
Data Mining For The Masses
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Author : Matthew North
language : en
Publisher:
Release Date : 2012-08-18
Data Mining For The Masses written by Matthew North and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-18 with Data mining categories.
Have you ever found yourself working with a spreadsheet full of data and wishing you could make more sense of the numbers? Have you reviewed sales or operations reports, wondering if there's a better way to anticipate your customers' needs? Perhaps you've even thought to yourself: There's got to be more to these figures than what I'm seeing! Data Mining can help, and you don't need a Ph.D. in Computer Science to do it. You can forecast staffing levels, predict demand for inventory, even sift through millions of lines of customer emails looking for common themes-all using data mining. It's easier than you might think. In Data Mining for the Masses, professor Matt North-a former risk analyst and database developer for eBay.com-uses simple examples, clear explanations and free, powerful, easy-to-use software to teach you the basics of data mining; techniques that can help you answer some of your toughest business questions. You've got data and you know it's got value, if only you can figure out how to unlock it. This book can show you how. Let's start digging! Through an agreement with the Global Text Project, an electronic version of this text is available online at (http://globaltext.terry.uga.edu/books). Proceeds from the sales of printed copies through Amazon enable the author to support the Global Text Project's goal of making electronic texts available to students in developing economies.
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
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
Artificial Intelligence With Python
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Author : Alberto Artasanchez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31
Artificial Intelligence With Python written by Alberto Artasanchez and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.