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Data Science A Modern Approach With Python


Data Science A Modern Approach With Python
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Data Science A Modern Approach With Python


Data Science A Modern Approach With Python
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Author : Mr.A.Pramod Kumar
language : en
Publisher: Leilani Katie Publication
Release Date : 2025-03-25

Data Science A Modern Approach With Python written by Mr.A.Pramod Kumar and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-25 with Computers categories.


Mr.A.Pramod Kumar, Assistant Professor, Department of (CSE-CyS, DS) and AI & DS, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India. Dr.G.Shyama Chandra Prasad, Senior Professor and HOD, Department of Information Technology, Matrusri Engineering College, Saidabad, Hyderabad, India. Dr.Yuvaraju Macha, Associate Professor, Department of Mathematics, Matrusri Engineering College, Saidabad, Hyderabad, Telangana, India. R.Madhavi, Assistant Professor, Deparment of Mathematics, Matrusri Engineering College, Saidabad, Hyderabad, India.



Python For Data Science Fundamentals


Python For Data Science Fundamentals
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Author : Dr.S.Peerbasha
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-07-21

Python For Data Science Fundamentals written by Dr.S.Peerbasha and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-21 with Language Arts & Disciplines categories.


Dr.S.Peerbasha, Assistant Professor, Department of Computer Science, Jamal Mohamed College, Tiruchirappalli, Tamil Nadu, India. Mr.A.Basheer Ahamed, Assistant Professor, Department of Computer Science, Jamal Mohamed College, Tiruchirappalli, Tamil Nadu, India. Mr.P.Shivaathmajan, Student, B.Tech IT, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India. Dr.Pavithra.M, Assistant Professor, Department of Computer Science and Engineering, Jansons Institute of Technology, Karumathampatti, Coimbatore, Tamil Nadu, India. Dr.T.Suresh, Assistant Professor, Department of Artificial Intelligence Machine Learning, K.Ramakrishnan College of Engineering, Tiruchirappalli, Tamil Nadu, India.



Data Analysis With Python


Data Analysis With Python
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Author : David Taieb
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31

Data Analysis With Python written by David Taieb 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 2018-12-31 with Computers categories.


Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key FeaturesBridge your data analysis with the power of programming, complex algorithms, and AIUse Python and its extensive libraries to power your way to new levels of data insightWork with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time seriesExplore this modern approach across with key industry case studies and hands-on projectsBook Description Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence. What you will learnA new toolset that has been carefully crafted to meet for your data analysis challengesFull and detailed case studies of the toolset across several of today’s key industry contextsBecome super productive with a new toolset across Python and Jupyter NotebookLook into the future of data science and which directions to develop your skills nextWho this book is for This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.



Data Science


Data Science
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Author : Tiffany Timbers
language : en
Publisher: CRC Press
Release Date : 2022-07-15

Data Science written by Tiffany Timbers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-15 with Business & Economics categories.


Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. The text emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. All source code is available online, demonstrating the use of good reproducible project workflows. Based on educational research and active learning principles, the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The book will leave readers well-prepared for data science projects. The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia’s DSCI100: Introduction to Data Science course.



Business Data Science Combining Machine Learning And Economics To Optimize Automate And Accelerate Business Decisions


Business Data Science Combining Machine Learning And Economics To Optimize Automate And Accelerate Business Decisions
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Author : Matt Taddy
language : en
Publisher: McGraw Hill Professional
Release Date : 2019-08-23

Business Data Science Combining Machine Learning And Economics To Optimize Automate And Accelerate Business Decisions written by Matt Taddy and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-23 with Business & Economics categories.


Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.



Data Science


Data Science
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Author : Tiffany Timbers
language : en
Publisher: CRC Press
Release Date : 2024-08-23

Data Science written by Tiffany Timbers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-23 with Mathematics categories.


Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. It emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. Based on educational research and active learning principles, the book uses a modern approach to Python and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The text will leave readers well-prepared for data science projects. It is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates at the University of British Columbia. Key Features: Includes autograded worksheets for interactive, self-directed learning. Introduces readers to modern data analysis and workflow tools such as Jupyter notebooks and GitHub, and covers cutting-edge data analysis and manipulation Python libraries such as pandas, scikit-learn, and altair. Is designed for a broad audience of learners from all backgrounds and disciplines.



Data Analysis With Python


Data Analysis With Python
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Author : Marco Bonzanini
language : en
Publisher:
Release Date : 2017

Data Analysis With Python written by Marco Bonzanini and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.


"This course introduces the audience to the field of Data Science using Python tools to manage and analyze data. You can learn some of the fundamental tools of the trade and apply them to real data problems. And along the way it discusses the use of Python stack for data analysis and scientific computing, and expands on concepts of data acquisition, data cleaning, data analysis and machine learning."--Resource description page.



Machine Learning And Deep Learning Using Python And Tensorflow


Machine Learning And Deep Learning Using Python And Tensorflow
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Author : Venkata Reddy Konasani
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-04-29

Machine Learning And Deep Learning Using Python And Tensorflow written by Venkata Reddy Konasani and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Technology & Engineering categories.


Understand the principles and practices of machine learning and deep learning This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text. Coverage includes: Machine learning and deep learning concepts Python programming and statistics fundamentals Regression and logistic regression Decision trees Model selection and cross-validation Cluster analysis Random forests and boosting Artificial neural networks TensorFlow and Keras Deep learning hyperparameters Convolutional neural networks Recurrent neural networks and long short-term memory



Python And R For The Modern Data Scientist


Python And R For The Modern Data Scientist
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Author : Rick Scavetta
language : en
Publisher:
Release Date : 2021

Python And R For The Modern Data Scientist written by Rick Scavetta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.


Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. With this book, data scientists from the Python and R communities will learn how to speak the dialects of each language. By recognizing the strengths of working with both, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Boyan Angelov and Rick Scavetta explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. Not only will you learn how to use Python and R together in real-world settings, but you'll also broaden your knowledge and job opportunities by working as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a real-world case study that demonstrates ways to use these languages together.



Data Science For Beginners


Data Science For Beginners
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Author : Andrew Park
language : en
Publisher:
Release Date : 2021-02-09

Data Science For Beginners written by Andrew Park and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-09 with categories.


★ 55% OFF for Bookstores! Now at $49.95 instead of $59.95! ★ Your Customers Will Never Stop To Use This Complete Guide! Did you know that according to Harvard Business Review the Data Scientist is the sexiest job of the 21st century? And for a reason! If "sexy" means having rare qualities that are much in demand, data scientists are already there. They are expensive to hire and, given the very competitive market for their services, difficult to retain. There simply aren't a lot of people with their combination of scientific background and computational and analytical skills. Data Science is all about transforming data into business value using math and algorithms. And needless to say, Python is the must-know programming language of the 21st century. If you are interested in coding and Data Science, then you must know Python to succeed in these industries! Data Science for Beginners is the perfect place to start learning everything you need to succeed. Contained within these four essential books are the methods, concepts, and important practical examples to help build your foundation for excelling at the discipline that is shaping the modern word. This bundle is perfect for programmers, software engineers, project managers and those who just want to keep up with technology. With these books in your hands, you will: ● Learn Python from scratch including the basic operations, how to install it, data structures and functions, and conditional loops ● Build upon the fundamentals with advanced techniques like Object-Oriented Programming (OOP), Inheritance, and Polymorphism ● Discover the importance of Data Science and how to use it in real-world situations ● Learn the 5 steps of Data Analysis so you can comprehend and analyze data sitting right in front of you ● Increase your income by learning a new, valuable skill that only a select handful of people take the time to learn ● Discover how companies can improve their business through practical examples and explanations ● And Much More! This bundle is essential for anyone who wants to study Data Science and learn how the world is moving to an open-source platform. Whether you are a software engineer or a project manager, jump to the next level by developing a data-driven approach and learning how to define a data-driven vision of your business! Order Your Copy of the Bundle and Let Your Customers Start Their New Career Path Today!