Learn Data Mining Through Excel: A Step-By-Step Approach for Understanding Machine Learning Methods, Zhou Hong
Автор: Isayev O Название: Materials Informatics: Methods, Tools, and Applications ISBN: 3527341218 ISBN-13(EAN): 9783527341214 Издательство: Wiley Рейтинг: Цена: 102380.00 T Наличие на складе: Поставка под заказ. Описание: Provides everything readers need to know for applying the power of informatics to materials science There is a tremendous interest in materials informatics and application of data mining to materials science. This book is a one-stop guide to the latest advances in these emerging fields. Bridging the gap between materials science and informatics, it introduces readers to up-to-date data mining and machine learning methods. It also provides an overview of state-of-the-art software and tools. Case studies illustrate the power of materials informatics in guiding the experimental discovery of new materials. Materials Informatics: Methods, Tools and Applications is presented in two parts?Methodological Aspects of Materials Informatics and Practical Aspects and Applications. The first part focuses on developments in software, databases, and high-throughput computational activities. Chapter topics include open quantum materials databases; the ICSD database; open crystallography databases; and more. The second addresses the latest developments in data mining and machine learning for materials science. Its chapters cover genetic algorithms and crystal structure prediction; MQSPR modeling in materials informatics; prediction of materials properties; amongst others. -Bridges the gap between materials science and informatics -Covers all the known methodologies and applications of materials informatics -Presents case studies that illustrate the power of materials informatics in guiding the experimental quest for new materials -Examines the state-of-the-art software and tools being used today Materials Informatics: Methods, Tools and Applications is a must-have resource for materials scientists, chemists, and engineers interested in the methods of materials informatics.
Автор: Witten, Ian H. Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed. ISBN: 0128042915 ISBN-13(EAN): 9780128042915 Издательство: Elsevier Science Рейтинг: Цена: 61750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Samantha Kleinberg Название: Time and Causality Across the Sciences ISBN: 1108476678 ISBN-13(EAN): 9781108476676 Издательство: Cambridge Academ Рейтинг: Цена: 61240.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides an entry point for researchers in any field, bringing together perspectives collected from a large body of work on causality across disciplines. Topics include whether quantum mechanics allows causes to precede their effects, the integration of mechanisms, and insight into the role played by intervention and timing information.
Автор: Bergmeir Название: Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data ISBN: 3658203668 ISBN-13(EAN): 9783658203665 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Philipp Bergmeir works on the development and enhancement of data mining and machine learning methods with the aim of analysing automatically huge amounts of load spectrum data that are recorded for large hybrid electric vehicle fleets.
The truth is...In the modern world, data has become fundamental, and companies are finding new ways to use the insights provided by data to improve their bottom line and customer experience. This is sometimes a challenge. There is so much data that figuring out what steps to take, and what is found in that data is not always as easy as we would like.
The good news is that working with data science can help you learn more about your customers and your industry, with the use of a simple coding language, and give you the insights and predictions that you need to see some great improvements with your business. And that's what you'll learn in Python for Data Science.
Python for Data Science is going to spend some time looking at all of the neat things that we can do with data science, so you can finally beat out the competition and increase your bottom line, all while helping out the customer.
You will learn:
Why Data Science is so Important in our Fast-Paced World of Today
5 Practical Applications of Data Science
Best Data Science Library that will help us to Get our Work Done with Python
A Simple Technique to Set Up our Virtual Environment
Proven Strategies to Get High-Quality Data
Tips and Tricks to Get your Data Organized
Data Analytics and Why It is so Important
What Machine Learning is all About and How it Fit into your Data Science Projects
Learning how data science works and how to complete your own data analysis in the process is going to be very important to the amount of success that you are going to see.
Even if you're completely new to data science or you've done some programming before and are looking to switch to an exciting new career track in Data Science, Python for Data Science will teach you all the practical techniques used by real-world data scientists and analysts to solve problems.
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Do you want to know everything about Data science?
This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful
There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business.
Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started.
The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started.
There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together.
This book covers:
What Is Data Science?
How Can I Use Data Science?
The Best Python Libraries for Data Science
Setting Up Your Virtual Environments for Data Science
The Importance of the NumPy Arrays
Gathering and Collecting Your Data
Loading and Preparing Your Dataset
Data Mining
Completing the Data Analysis
How Machine Learning Can Help
How to Work with Data Visualization
Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.
★ 55% OFF for Bookstores NOW at $ 34,97 instead of $ 44.97 LAST DAYS ★
Your Customers Never Stop to Use this Awesome book
Do you want to know everything about Data science?
This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful
There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business.
Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started.
The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started.
There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together.
This book covers:
What Is Data Science?
How Can I Use Data Science?
The Best Python Libraries for Data Science
Setting Up Your Virtual Environments for Data Science
The Importance of the NumPy Arrays
Gathering and Collecting Your Data
Loading and Preparing Your Dataset
Data Mining
Completing the Data Analysis
How Machine Learning Can Help
How to Work with Data Visualization
Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.
★ 55% OFF for Bookstores NOW at $ 22,97 instead of $ 32.97 LAST DAYS ★
Your Customers Never Stop to Use this Awesome book
Do you want to know everything about Data science?
This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful
There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business.
Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started.
The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started.
There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together.
This book covers:
What Is Data Science?
How Can I Use Data Science?
The Best Python Libraries for Data Science
Setting Up Your Virtual Environments for Data Science
The Importance of the NumPy Arrays
Gathering and Collecting Your Data
Loading and Preparing Your Dataset
Data Mining
Completing the Data Analysis
How Machine Learning Can Help
How to Work with Data Visualization
Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.
★ 55% OFF for Bookstores NOW at $ 32,97 instead of $ 42.97 LAST DAYS ★
Your Customers Never Stop to Use this Awesome book
Do you want to know everything about Data science?
This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful
There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business.
Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started.
The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started.
There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together.
This book covers:
What Is Data Science?
How Can I Use Data Science?
The Best Python Libraries for Data Science
Setting Up Your Virtual Environments for Data Science
The Importance of the NumPy Arrays
Gathering and Collecting Your Data
Loading and Preparing Your Dataset
Data Mining
Completing the Data Analysis
How Machine Learning Can Help
How to Work with Data Visualization
Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.
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Автор: Ivezic?, Z?eljko, Название: Statistics, data mining, and machine learning in astronomy : ISBN: 0691198306 ISBN-13(EAN): 9780691198309 Издательство: Wiley Рейтинг: Цена: 82370.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, engage with the different methods, and adapt them to their own fields of interest.
An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.
Fully revised and expanded
Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets
Features real-world data sets from astronomical surveys
Uses a freely available Python codebase throughout
Ideal for graduate students, advanced undergraduates, and working astronomers
Автор: Pablo Duboue Название: The Art of Feature Engineering: Essentials for Machine Learning ISBN: 1108709389 ISBN-13(EAN): 9781108709385 Издательство: Cambridge Academ Рейтинг: Цена: 46470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.
Автор: Thakuriah Piyushimita (Vonu), Tilahun Nebiyou, Zellner Moira Название: Seeing Cities Through Big Data: Research, Methods and Applications in Urban Informatics ISBN: 3319822136 ISBN-13(EAN): 9783319822136 Издательство: Springer Рейтинг: Цена: 232910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduction to Seeing Cities Through Big Data - Research, Methods, and Applications in Urban Informatics.- Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery.- Analytics of user-generated content.- Using User-Generated Content to Understand Cities.- Developing an Interactive Mobile Volunteered Geographic Information Platform to Integrate Environmental Big Data and Citizen Science in Urban Management.- CyberGIS-enabled Urban Sensing from Volunteered Citizen Participation Using Mobile Devices.- Challenges and opportunities of urban Big Data.- The Potential for Big Data to Improve Neighborhood-Level Census Data.- Big Data and Survey Research: Supplement or Substitute?.- Big Spatio-temporal Network Data Analytics for Smart Cities: Research Needs.- A review of heteroscedasticity treatment with Gaussian Processes and Quantile Regression meta-models.- Changing organizational and educational perspectives with urban Big Data.- Urban Informatics: Critical Data and Technology Considerations.- Emerging Urban Digital Infomediaries and Civic Hacking in an Era of Big Data and Open Data Initiatives.- How Should Urban Planners Be Trained to Handle Big Data?.- Energy Planning in Big data Era: A Theme Study of the Residential Sector.- Urban data management.- Using an online spatial analytics workbench for understanding housing affordability in Sydney.- A Big Data Mashing Tool for Measuring Transit System Performance.- Developing a Comprehensive U.S. Transit Accessibility Database.- Seeing Chinese Cities through Big Data and Statistics.- Urban knowledge discovery applied to different urban contexts.- Planning for the Change: Mapping Sea Level Rise and Storm Inundation in Sherman Island Using 3Di Hydrodynamic Model and LiDAR.- The Impact of Land-Use Variables on Free-floating Carsharing Vehicle Rental Choice and Parking Duration.- Dynamic Agent Based Simulation of an Urban Disaster Using Synthetic Big Data.- Estimation of Urban Transport Accessibility at the Spatial Resolution of an Individual Traveler.- Modeling Taxi Demand and Supply in New York City Using Large-Scale Taxi GPS Data.- Detecting stop episodes from GPS trajectories with gaps.- Emergencies and Crisis.- Using Social Media and Satellite Data for Damage Assessment in Urban Areas During Emergencies.- Health and well-being.- 'Big Data': Pedestrian Volume Using Google Street View Images.- Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments.- Mapping Urban Soundscapes via Citygram.- Social equity and data democracy.- Big Data and Smart (Equitable) Cities.- Big Data, Small Apps: Premises and Products of the Civic Hackathon.
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