From Analysis To Visualization
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Bitcoin Analysis Visualization Forecasting And Prediction With Python Gui
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Author : Vivian Siahaan
language : en
Publisher: BALIGE PUBLISHING
Release Date : 2022-06-04
Bitcoin Analysis Visualization Forecasting And Prediction With 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 2022-06-04 with Business & Economics categories.
Bitcoin is a digital currency created in January 2009. It follows the ideas set out in a whitepaper by the mysterious and pseudonymous Satoshi Nakamoto.1 The identity of the person or persons who created the technology is still a mystery. Bitcoin offers the promise of lower transaction fees than traditional online payment mechanisms and, unlike government-issued currencies, it is operated by a decentralized authority. This dataset provides the history of daily prices of Bitcoin. The data starts from 17-Sep-2014 and is updated till 09-July-2021. It contains 2747 rows and 7 columns. The columns in the dataset are Date, Open, High, Low, Close, Adj Close, and Volume. In this project, you will involve technical indicators such as daily returns, Moving Average Convergence-Divergence (MACD), Relative Strength Index (RSI), Simple Moving Average (SMA), lower and upper bands, and standard deviation. To perform forecasting based on regression on Adj Close price of Bitcoin, you will use: Linear Regression, Random Forest regression, Decision Tree regression, Support Vector Machine regression, Naïve Bayes regression, K-Nearest Neighbor regression, Adaboost regression, Gradient Boosting regression, Extreme Gradient Boosting regression, Light Gradient Boosting regression, Catboost regression, MLP regression, Lasso regression, and Ridge regression. The machine learning models used predict Bitcoin daily returns as target variable are K-Nearest Neighbor classifier, Random Forest classifier, Naive Bayes classifier, Logistic Regression classifier, Decision Tree classifier, Support Vector Machine classifier, LGBM classifier, Gradient Boosting classifier, XGB classifier, MLP classifier, and Extra Trees classifier. Finally, you will develop GUI to plot boundary decision, distribution of features, feature importance, predicted values versus true values, confusion matrix, learning curve, performance of the model, and scalability of the model.
Introducing Data Science For Beginners 2025 Learn Data Analysis Visualization Machine Learning Basics
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Author : A. Ali
language : en
Publisher: Code Academy
Release Date : 2025-05-07
Introducing Data Science For Beginners 2025 Learn Data Analysis Visualization Machine Learning Basics written by A. Ali and has been published by Code Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
Introducing Data Science for Beginners 2025 is your essential guide to understanding the fundamentals of data science, even if you have no prior experience. This beginner-friendly book breaks down core concepts such as data analysis, visualization, statistics, and the basics of machine learning. With real-world examples and simplified explanations, it helps you build a strong foundation in Python, data handling, and decision-making through data. Whether you're a student, professional, or enthusiast, this book provides the perfect starting point to enter the world of data science with confidence.
Scientific Visualization
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Author : Charles D. Hansen
language : en
Publisher: Springer
Release Date : 2014-09-18
Scientific Visualization written by Charles D. Hansen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-18 with Mathematics categories.
Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. • Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation, • Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets, • Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications, • Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms. Scientific Visualization will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics, and those interested in knowing more about the visualization process.
Visualizing The Invisible
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Author : Joseph G. Martin III
language : en
Publisher: Universal-Publishers
Release Date :
Visualizing The Invisible written by Joseph G. Martin III and has been published by Universal-Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
In Situ Visualization For Computational Science
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Author : Hank Childs
language : en
Publisher: Springer Nature
Release Date : 2022-05-04
In Situ Visualization For Computational Science written by Hank Childs and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-04 with Mathematics categories.
This book provides an overview of the emerging field of in situ visualization, i.e. visualizing simulation data as it is generated. In situ visualization is a processing paradigm in response to recent trends in the development of high-performance computers. It has great promise in its ability to access increased temporal resolution and leverage extensive computational power. However, the paradigm also is widely viewed as limiting when it comes to exploration-oriented use cases. Furthermore, it will require visualization systems to become increasingly complex and constrained in usage. As research efforts on in situ visualization are growing, the state of the art and best practices are rapidly maturing. Specifically, this book contains chapters that reflect state-of-the-art research results and best practices in the area of in situ visualization. Our target audience are researchers and practitioners from the areas of mathematics computational science, high-performance computing, and computer science that work on or with in situ techniques, or desire to do so in future.
A Framework For Visualizing Information
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Author : E.H. Chi
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
A Framework For Visualizing Information written by E.H. Chi 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 2013-03-14 with Computers categories.
Fundamental solutions in understanding information have been elusive for a long time. The field of Artificial Intelligence has proposed the Turing Test as a way to test for the "smart" behaviors of computer programs that exhibit human-like qualities. Equivalent to the Turing Test for the field of Human Information Interaction (HII), getting information to the people that need them and helping them to understand the information is the new challenge of the Web era. In a short amount of time, the infrastructure of the Web became ubiquitious not just in terms of protocols and transcontinental cables but also in terms of everyday devices capable of recalling network-stored data, sometimes wire lessly. Therefore, as these infrastructures become reality, our attention on HII issues needs to shift from information access to information sensemaking, a relatively new term coined to describe the process of digesting information and understanding its structure and intricacies so as to make decisions and take action.
Data Visualization
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Author : Frits H. Post
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-12-31
Data Visualization written by Frits H. Post 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 2002-12-31 with Computers categories.
Data visualization is currently a very active and vital area of research, teaching and development. The term unites the established field of scientific visualization and the more recent field of information visualization. The success of data visualization is due to the soundness of the basic idea behind it: the use of computer-generated images to gain insight and knowledge from data and its inherent patterns and relationships. A second premise is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes, and simulations involving data sets from diverse scientific disciplines and large collections of abstract data from many sources. These concepts are extremely important and have a profound and widespread impact on the methodology of computational science and engineering, as well as on management and administration. The interplay between various application areas and their specific problem solving visualization techniques is emphasized in this book. Reflecting the heterogeneous structure of Data Visualization, emphasis was placed on these topics: -Visualization Algorithms and Techniques; -Volume Visualization; -Information Visualization; -Multiresolution Techniques; -Interactive Data Exploration. Data Visualization: The State of the Art presents the state of the art in scientific and information visualization techniques by experts in this field. It can serve as an overview for the inquiring scientist, and as a basic foundation for developers. This edited volume contains chapters dedicated to surveys of specific topics, and a great deal of original work not previously published illustrated by examples from a wealth of applications. The book will also provide basic material for teaching the state of the art techniques in data visualization. Data Visualization: The State of the Art is designed to meet the needs of practitioners and researchers in scientific and information visualization. This book is also suitable as a secondary text for graduate level students in computer science and engineering.
Visualizations And Dashboards For Learning Analytics
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Author : Muhittin Sahin
language : en
Publisher: Springer Nature
Release Date : 2021-12-16
Visualizations And Dashboards For Learning Analytics written by Muhittin Sahin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-16 with Education categories.
This edited volume fills the gaps in existing literature on visualization and dashboard design for learning analytics. To do so, it presents critical tips to stakeholders and acts as guide to efficient implementation. The book covers the following topics: visualization and dashboard design for learning analytics, visualization and dashboard preferences of stakeholders, learners’ patterns on the dashboard, usability of visualization techniques and the dashboard, dashboard and intervention design, learning and instructional design for learning analytics, privacy and security issues about the dashboard, and future directions of visualization and dashboard design. This book will be of interest to researchers with interest in learning analytics and data analytics, teachers and students in higher education institutions and instructional designers, as it includes contributions from a wide variety of educational and psychological researchers, engineers, instructional designers, learning scientists, and computer scientists interested in learning analytics.
Google Stock Price Time Series Analysis Visualization Forecasting And Prediction Using Machine Learning With Python Gui
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Author : Vivian Siahaan
language : en
Publisher: BALIGE PUBLISHING
Release Date : 2023-06-11
Google Stock Price Time Series Analysis Visualization Forecasting And Prediction Using Machine Learning With 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 2023-06-11 with Computers categories.
Google, officially known as Alphabet Inc., is an American multinational technology company. It was founded in September 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. Initially, it started as a research project to develop a search engine, but it rapidly grew into one of the largest and most influential technology companies in the world. Google is primarily known for its internet-related services and products, with its search engine being its most well-known offering. It revolutionized the way people access information by providing a fast and efficient search engine that delivers highly relevant results. Over the years, Google expanded its portfolio to include a wide range of products and services, including Google Maps, Google Drive, Gmail, Google Docs, Google Photos, Google Chrome, YouTube, and many more. In addition to its internet services, Google ventured into hardware with products like the Google Pixel smartphones, Google Home smart speakers, and Google Nest smart home devices. It also developed its own operating system called Android, which has become the most widely used mobile operating system globally. Google's success can be attributed to its ability to monetize its services through online advertising. The company introduced Google AdWords, a highly successful online advertising program that enables businesses to display ads on Google's search engine and other websites through its AdSense program. Advertising contributes significantly to Google's revenue, along with other sources such as cloud services, app sales, and licensing fees. The dataset used in this project starts from 19-Aug-2004 and is updated till 11-Oct-2021. It contains 4317 rows and 7 columns. The columns in the dataset are Date, Open, High, Low, Close, Adj Close, and Volume. You can download the dataset from https://viviansiahaan.blogspot.com/2023/06/google-stock-price-time-series-analysis.html. In this project, you will involve technical indicators such as daily returns, Moving Average Convergence-Divergence (MACD), Relative Strength Index (RSI), Simple Moving Average (SMA), lower and upper bands, and standard deviation. In this book, you will learn how to perform forecasting based on regression on Adj Close price of Google stock price, you will use: Linear Regression, Random Forest regression, Decision Tree regression, Support Vector Machine regression, Naïve Bayes regression, K-Nearest Neighbor regression, Adaboost regression, Gradient Boosting regression, Extreme Gradient Boosting regression, Light Gradient Boosting regression, Catboost regression, MLP regression, Lasso regression, and Ridge regression. The machine learning models used to predict Google daily returns as target variable are K-Nearest Neighbor classifier, Random Forest classifier, Naive Bayes classifier, Logistic Regression classifier, Decision Tree classifier, Support Vector Machine classifier, LGBM classifier, Gradient Boosting classifier, XGB classifier, MLP classifier, and Extra Trees classifier. Finally, you will develop GUI to plot boundary decision, distribution of features, feature importance, predicted values versus true values, confusion matrix, learning curve, performance of the model, and scalability of the model.
11th International Meeting On Visualizing Biological Data Vizbi 2021
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Author : Sean O’Donoghue
language : en
Publisher: Frontiers Media SA
Release Date : 2022-12-16
11th International Meeting On Visualizing Biological Data Vizbi 2021 written by Sean O’Donoghue and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-16 with Science categories.