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Implementasi Data Science Berbasis Proyek Dengan Python Gui


Implementasi Data Science Berbasis Proyek Dengan Python Gui
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Implementasi Data Science Berbasis Proyek Dengan Python Gui


Implementasi Data Science Berbasis Proyek Dengan Python Gui
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Author : Vivian Siahaan
language : id
Publisher: BALIGE PUBLISHING
Release Date : 2021-08-16

Implementasi Data Science Berbasis Proyek Dengan Python Gui written by Vivian Siahaan and has been published by BALIGE PUBLISHING this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-16 with Computers categories.


Buku ini merupakan versi bahasa Indonesia dari buku kami yang berjudul “Step by Step Project-Based Tutorials for Data Science with Python GUI: Traffic and Heart Attack Analysis and Prediction”. Anda dapat menemukannya di Google Books dan Amazon. Pada Bab 1, Anda akan mempelajari dasar-dasar pemrograman Python GUI dengan PyQ5. Anda akan belajar menciptakan sejumlah GUI dengan bantuan Qt Designer. Pada proyek di Bab 2, Anda akan belajar menggunakan dan menerapkan modul Scikit-Learn, NumPy, Pandas, dan sejumlah modul lain untuk menganalisa dan memprediksi serangan jantung menggunakan Heart Attack Analysis & Prediction Dataset yang disediakan di Kaggle. Di sini, Anda akan mengembangkan sebuah GUI untuk menampilkan distribusi tiap fitur pada dataset, matriks korelasi, confusion matrix, dan nilai-nilai sebenarnya versus nilai-nilai prediksi. Model-model machine learning yang dipakai pada proyek ini adalah Logistic Regression, K-Nearest Neighbor, Support Vector Machine, Decision Tree, Random Forest, Adaboost, Gradient Boosting, SGBoost, dan MLP. Pada proyek di Bab 3, Anda akan belajar dan menerapkan Scikit-Learn, Scipy, dan sejumlah pustaka lain untuk mengimplementasikan bagaimana menganalisa dan memprediksi trafik kendaraan pada empat persimpangan jalan menggunakan Traffic Prediction Dataset yang disediakan di Kaggle. Dataset memuat 48.1k (48120) observasi banyaknya kendaraan tiap jam di empat persimpangan jalan berbeda. Dataset ini memuat empat kolom: 1) DateTime; 2) Juction; 3) Vehicles; dan 4) ID. Pada proyek ini, Anda akan mengembangkan sebuah GUI untuk menampilkan distribusi kerapatan probabilitas tiap fitur, data pada tiap persimpangan dalam runtun waktu, distribusi banyak kendaraan berdasarkan waktu (tahun, bulan, dan hari) dan persimpangan, matriks korelasi, korelasi-diri parsial, hasil pelatihan model-model Random Forest, keutamaan fitur, dan banyak kendaraan berdasarkan hari untuk beberapa bulan ke depan.



Data Science Dengan Python Gui Untuk Programmer


Data Science Dengan Python Gui Untuk Programmer
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Author : Vivian Siahaan
language : id
Publisher: BALIGE PUBLISHING
Release Date : 2021-08-19

Data Science Dengan Python Gui Untuk Programmer written by Vivian Siahaan and has been published by BALIGE PUBLISHING this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-19 with Computers categories.


Buku 1: Pemrograman DATA SCIENCE dengan Python GUI: Studi Kasus Dataset Diabetes Dan Kanker Payudara Buku ini merupakan versi bahasa Indonesia dari buku kami yang berjudul “Practical Data Science Programming for Medical Datasets Analysis and Prediction with Python GUI”. Anda dapat menemukannya di Google Books dan Amazon. Pada proyek pertama, Anda akan mempelajari cara menggunakan Scikit-Learn, SVM, NumPy, Pandas, dan library lainnya untuk melakukan cara memprediksi diabetes tahap awal menggunakan Early Stage Diabetes Risk Prediction Dataset yang disediakan di Kaggle. Dataset ini berisi data tanda dan gejala penderita diabetes atau pasien yang berpotensi mengidap diabetes. Dataset telah dikumpulkan dengan menggunakan kuesioner langsung dari pasien Rumah Sakit Sylhet Diabetes di Sylhet, Bangladesh dan disetujui oleh dokter. Dataset terdiri dari total 15 fitur dan satu variabel target bernama class. Pada proyek ini, Anda akan mengembangkan GUI menggunakan PyQt5 untuk menampilkan distribusi fitur, feature importance, skor validasi silang, dan nilai terprediksi versus nilai sebenarnya, dan confusion matrix. Pada proyek kedua, Anda akan belajar bagaimana menerapkan Scikit-Learn, NumPy, Pandas, dan sejumlah pustaka lain untuk menganalisa dan memprediksi kanker payudara menggunakan Breast Cancer Prediction Dataset yang disediakan di Kaggle. Di seluruh dunia, kanker payudara adalah jenis kanker yang paling umum pada wanita dan tertinggi kedua dalam hal angka kematian. Diagnosis kanker payudara dilakukan ketika ditemukan benjolan abnormal (dari pemeriksaan sendiri atau x-ray) atau setitik kecil dari kalsium yang terlihat (pada x-ray). Setelah benjolan yang mencurigakan ditemukan, dokter akan melakukan diagnosis untuk menentukan apakah itu kanker dan, jika ya, apakah sudah menyebar ke bagian tubuh lain. Dataset kanker payudara ini diperoleh dari University of Wisconsin Hospitals, Madison dari Dr. William H. Wolberg. Pada proyek ini, Anda juga akan mengembangkan GUI menggunakan PyQt5 untuk menampilkan decision boundary, ROC, distribusi fitur, feature importance, skor validasi silang, dan nilai terprediksi versus nilai sebenarnya, dan confusion matrix. Buku 2: IMPLEMENTASI DATA SCIENCE BERBASIS PROYEK DENGAN PYTHON GUI Buku ini merupakan versi bahasa Indonesia dari buku kami yang berjudul “Step by Step Project-Based Tutorials for Data Science with Python GUI: Traffic and Heart Attack Analysis and Prediction”. Anda dapat menemukannya di Google Books dan Amazon. Pada Bab 1, Anda akan mempelajari dasar-dasar pemrograman Python GUI dengan PyQ5. Anda akan belajar menciptakan sejumlah GUI dengan bantuan Qt Designer. Pada proyek di Bab 2, Anda akan belajar menggunakan dan menerapkan modul Scikit-Learn, NumPy, Pandas, dan sejumlah modul lain untuk menganalisa dan memprediksi serangan jantung menggunakan Heart Attack Analysis & Prediction Dataset yang disediakan di Kaggle. Di sini, Anda akan mengembangkan sebuah GUI untuk menampilkan distribusi tiap fitur pada dataset, matriks korelasi, confusion matrix, dan nilai-nilai sebenarnya versus nilai-nilai prediksi. Model-model machine learning yang dipakai pada proyek ini adalah Logistic Regression, K-Nearest Neighbor, Support Vector Machine, Decision Tree, Random Forest, Adaboost, Gradient Boosting, SGBoost, dan MLP. Pada proyek di Bab 3, Anda akan belajar dan menerapkan Scikit-Learn, Scipy, dan sejumlah pustaka lain untuk mengimplementasikan bagaimana menganalisa dan memprediksi trafik kendaraan pada empat persimpangan jalan menggunakan Traffic Prediction Dataset yang disediakan di Kaggle. Dataset memuat 48.1k (48120) observasi banyaknya kendaraan tiap jam di empat persimpangan jalan berbeda. Dataset ini memuat empat kolom: 1) DateTime; 2) Juction; 3) Vehicles; dan 4) ID. Pada proyek ini, Anda akan mengembangkan sebuah GUI untuk menampilkan distribusi kerapatan probabilitas tiap fitur, data pada tiap persimpangan dalam runtun waktu, distribusi banyak kendaraan berdasarkan waktu (tahun, bulan, dan hari) dan persimpangan, matriks korelasi, korelasi-diri parsial, hasil pelatihan model-model Random Forest, keutamaan fitur, dan banyak kendaraan berdasarkan hari untuk beberapa bulan ke depan. Buku 3: TUMOR OTAK: Analisis, Klasifikasi, dan Deteksi Menggunakan Machine Learning dan Deep Learning dengan Python GUI Buku ini merupakan versi bahasa Indonesia dari buku kami yang berjudul “BRAIN TUMOR: Analysis, Classification, and Detection Using Machine Learning and Deep Learning with Python GUI”. Anda dapat menemukannya di Google Books dan Amazon. Tentu, Anda telah banyak menjumpai buku-buku yang memberikan pemahaman fundamental dan teoritis yang berkaitan dengan Machine Learning dan Deep Learning. Berbeda dari buku-buku tersebut, buku ini diperuntukkan bagi Anda yang ingin mengupas data science, khususnya Machine Learning dan Deep Learning, dengan secara langsung mempraktekkannya dalam sebuah proyek. Hal ini akan meningkatkan kemampuan pemrograman Anda ketika Anda nantinya berniat untuk menjadi seorang Data Scientist. Pada proyek ini, Anda akan mempelajari cara menggunakan Scikit-Learn, TensorFlow, Keras, NumPy, Pandas, Seaborn, dan pustaka lainnya untuk menerapkan analisis, klasifikasi dan deteksi tumor otak dengan pembelajaran mesin (Machine Learning) dan Deep Learning menggunakan dataset Brain Tumor yang disediakan di Kaggle. Dataset ini berisi lima fitur orde pertama: Mean (kontribusi intensitas piksel individu untuk seluruh gambar), Variance (digunakan untuk menemukan bagaimana setiap piksel bervariasi dari piksel tetangga 0, Standard Deviation (deviasi nilai terukur atau data dari mean), Skewness (ukuran simetri), dan Kurtosis (menggambarkan puncak, misalnya, distribusi frekuensi). Dataset ini juga berisi delapan fitur orde kedua: Contrast, Energy, ASM (Angular second moment), Entropy, Homogeneity, Dissimilarity, Correlation, dan Coarseness. Model machine learning yang digunakan dalam proyek ini adalah K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, dan Support Vector Machine. Model deep learning yang digunakan dalam proyek ini adalah MobileNet dan ResNet50. Pada proyek ini, Anda akan mengembangkan GUI menggunakan PyQt5 untuk menampilkan decision boundary, ROC, distribusi fitur, feature importance, skor validasi silang, dan nilai terprediksi versus nilai sebenarnya, confusion matrix, rugi pelatihan, dan akurasi pelatihan.



Data Lake Architecture


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



The Failure Of Risk Management


The Failure Of Risk Management
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Author : Douglas W. Hubbard
language : en
Publisher: John Wiley & Sons
Release Date : 2009-04-27

The Failure Of Risk Management written by Douglas W. Hubbard 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 2009-04-27 with Business & Economics categories.


An essential guide to the calibrated risk analysis approach The Failure of Risk Management takes a close look at misused and misapplied basic analysis methods and shows how some of the most popular "risk management" methods are no better than astrology! Using examples from the 2008 credit crisis, natural disasters, outsourcing to China, engineering disasters, and more, Hubbard reveals critical flaws in risk management methods–and shows how all of these problems can be fixed. The solutions involve combinations of scientifically proven and frequently used methods from nuclear power, exploratory oil, and other areas of business and government. Finally, Hubbard explains how new forms of collaboration across all industries and government can improve risk management in every field. Douglas W. Hubbard (Glen Ellyn, IL) is the inventor of Applied Information Economics (AIE) and the author of Wiley's How to Measure Anything: Finding the Value of Intangibles in Business (978-0-470-11012-6), the #1 bestseller in business math on Amazon. He has applied innovative risk assessment and risk management methods in government and corporations since 1994. "Doug Hubbard, a recognized expert among experts in the field of risk management, covers the entire spectrum of risk management in this invaluable guide. There are specific value-added take aways in each chapter that are sure to enrich all readers including IT, business management, students, and academics alike" —Peter Julian, former chief-information officer of the New York Metro Transit Authority. President of Alliance Group consulting "In his trademark style, Doug asks the tough questions on risk management. A must-read not only for analysts, but also for the executive who is making critical business decisions." —Jim Franklin, VP Enterprise Performance Management and General Manager, Crystal Ball Global Business Unit, Oracle Corporation.



Developing 2d Games With Unity


Developing 2d Games With Unity
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Author : Jared Halpern
language : en
Publisher:
Release Date : 2019

Developing 2d Games With Unity written by Jared Halpern and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with C# (Computer program language) categories.


Follow a walkthrough of the Unity Engine and learn important 2D-centric lessons in scripting, working with image assets, animations, cameras, collision detection, and state management. In addition to the fundamentals, you'll learn best practices, helpful game-architectural patterns, and how to customize Unity to suit your needs, all in the context of building a working 2D game. While many books focus on 3D game creation with Unity, the easiest market for an independent developer to thrive in is 2D games. 2D games are generally cheaper to produce, more feasible for small teams, and more likely to be completed. If you live and breathe games and want to create them then 2D games are a great place to start. By focusing exclusively on 2D games and Unity's ever-expanding 2D workflow, this book gives aspiring independent game developers the tools they need to thrive. Various real-world examples of independent games are used to teach fundamental concepts of developing 2D games in Unity, using the very latest tools in Unity's updated 2D workflow. New all-digital channels for distribution, such as Nintendo eShop, XBox Live Marketplace, the Playstation Store, the App Store, Google Play, itch.io, Steam, and GOG.com have made it easier than ever to discover, buy, and sell games. The golden age of independent gaming is upon us, and there has never been a better time to get creative, roll up your sleeves, and build that game you've always dreamed about. Developing 2D Games with Unity can show you the way.



Python Data Science Handbook


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



Software Engineering


Software Engineering
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Author : Roger S. Pressman
language : en
Publisher:
Release Date : 2019-09-09

Software Engineering written by Roger S. Pressman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-09 with Computers categories.


For almost four decades, Software Engineering: A Practitioner's Approach (SEPA) has been the world's leading textbook in software engineering. The ninth edition represents a major restructuring and update of previous editions, solidifying the book's position as the most comprehensive guide to this important subject.



Programming Php


Programming Php
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Author : Rasmus Lerdorf
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2002-03-26

Programming Php written by Rasmus Lerdorf 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 2002-03-26 with Computers categories.


This is a comprehensive guide to PHP, a simple yet powerful language for creating dynamic web content. It is a detailed reference to the language and its applications, including such topics as form processing, sessions, databases, XML, and graphics and Covers PHP 4, the latest version.



Math Adventures With Python


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!



Optical Wdm Networks


Optical Wdm Networks
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Author : Biswanath Mukherjee
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-06-15

Optical Wdm Networks written by Biswanath Mukherjee 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 2006-06-15 with Computers categories.


Research and development on optical wavelength-division multiplexing (WDM) networks have matured considerably. While optics and electronics should be used appropriately for transmission and switching hardware, note that "intelligence'' in any network comes from "software,'' for network control, management, signaling, traffic engineering, network planning, etc.The role of software in creating powerful network architectures for optical WDM networks is emphasized. Optical WDM Networks is a textbook for graduate level courses. Its focus is on the networking aspects of optical networking, but it also includes coverage of physical layers in optical networks. The author introduces WDM and its enabling technologies and discusses WDM local, access, metro, and long-haul network architectures. Each chapter is self-contained, has problems at the end of each chapter, and the material is organized for self study as well as classroom use. The material is the most recent and timely in capturing the state-of-the-art in the fast-moving field of optical WDM networking.