A Practical Approach To Dbms Using Python
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A Practical Approach To Dbms Using Python
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Author : Dr. Rupak Chakraborty
language : en
Publisher: Chyren Publication
Release Date : 2025-03-22
A Practical Approach To Dbms Using Python written by Dr. Rupak Chakraborty and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-22 with Antiques & Collectibles categories.
Streamlining Etl A Practical Guide To Building Pipelines With Python And Sql
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Author : Peter Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-11
Streamlining Etl A Practical Guide To Building Pipelines With Python And Sql written by Peter Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-11 with Computers categories.
Unlock the potential of data with "Streamlining ETL: A Practical Guide to Building Pipelines with Python and SQL," the definitive resource for creating high-performance ETL pipelines. This essential guide is meticulously designed for data professionals seeking to harness the data-intensive capabilities of Python and SQL. From establishing a development environment and extracting raw data to optimizing and securing data processes, this book offers comprehensive coverage of every aspect of ETL pipeline development. Whether you're a data engineer, IT professional, or a scholar in data science, this book provides step-by-step instructions, practical examples, and expert insights necessary for mastering the creation and management of robust ETL pipelines. By the end of this guide, you will possess the skills to transform disparate data into meaningful insights, ensuring your data processes are efficient, scalable, and secure. Dive into advanced topics with ease and explore best practices that will make your data workflows more productive and error-resistant. With this book, elevate your organization's data strategy and foster a data-driven culture that thrives on precision and performance. Embrace the journey to becoming an adept data professional with a solid foundation in ETL processes, equipped to handle the challenges of today's data demands.
A Practical Approach For Machine Learning And Deep Learning Algorithms
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Author : Abhishek Kumar Pandey
language : en
Publisher: BPB Publications
Release Date : 2019-09-18
A Practical Approach For Machine Learning And Deep Learning Algorithms written by Abhishek Kumar Pandey and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-18 with Computers categories.
Guide covering topics from machine learning, regression models, neural network to tensor flow DESCRIPTION Machine learning is mostly sought in the research field and has become an integral part of many research projects nowadays including commercial applications, as well as academic research. Application of machine learning ranges from finding friends on social networking sites to medical diagnosis and even satellite processing. In this book, we have made an honest effort to make the concepts of machine learning easy and give basic programs in MATLAB right from the installation part. Although the real-time application of machine learning is endless, however, the basic concepts and algorithms are discussed using MATLAB language so that not only graduation students but also researchers are benefitted from it. KEY FEATURES Machine learning in MATLAB using basic concepts and algorithms. Deriving and accessing of data in MATLAB and next, pre-processing and preparation of data. Machine learning workflow for health monitoring. The neural network domain and implementation in MATLAB with explicit explanation of code and results. How predictive model can be improved using MATLAB? MATLAB code for an algorithm implementation, rather than for mathematical formula. Machine learning workflow for health monitoring. WHAT WILL YOU LEARN Pre-requisites to machine learning Finding natural patterns in data Building classification methods Data pre-processing in Python Building regression models Creating neural networks Deep learning WHO THIS BOOK IS FOR The book is basically meant for graduate and research students who find the algorithms of machine learning difficult to implement. We have touched all basic algorithms of machine learning in detail with a practical approach. Primarily, beginners will find this book more effective as the chapters are subdivided in a manner that they find the building and implementation of algorithms in MATLAB interesting and easy at the same time. Table of Contents _1. Ê Ê Pre-requisite to Machine Learning 2. Ê Ê An introduction to Machine Learning 3. Ê Ê Finding Natural Patterns in Data 4. Ê Ê Building Classification Methods 5. Ê Ê Data Pre-Processing in Python 6. Ê Ê Building Regression Models 7. Ê Ê Creating Neural Networks 8. Ê Ê Introduction to Deep Learning
Database Systems
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Author : Thomas M. Connolly
language : en
Publisher: Pearson Education
Release Date : 2005
Database Systems written by Thomas M. Connolly and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
This book places a strong emphasis on good design practice, allowing readers to master design methodology in an accessible, step-by-step fashion. In this book, database design methodology is explicitly divided into three phases: conceptual, logical, and physical. Each phase is described in a separate chapter with an example of the methodology working in practice. Extensive treatment of the Web as an emerging platform for database applications is covered alongside many code samples for accessing databases from the Web including JDBC, SQLJ, ASP, ISP, and Oracle's PSP. A thorough update of later chapters covering object-oriented databases, Web databases, XML, data warehousing, data mining is included in this new edition. A clear introduction to design implementation and management issues, as well as an extensive treatment of database languages and standards, make this book an indispensable, complete reference for database professionals.
A Practical Guide To Artificial Intelligence And Data Analytics
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Author : Rayan Wali
language : en
Publisher: Rayan Wali
Release Date : 2021-06-12
A Practical Guide To Artificial Intelligence And Data Analytics written by Rayan Wali and has been published by Rayan Wali this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-12 with Computers categories.
Whether you are looking to prepare for AI/ML/Data Science job interviews or you are a beginner in the field of Data Science and AI, this book is designed for engineers and AI enthusiasts like you at all skill levels. Taking a different approach from a traditional textbook style of instruction, A Practical Guide to AI and Data Analytics touches on all of the fundamental topics you will need to understand deeper into machine learning and artificial intelligence research, literature, and practical applications with its four parts: Part I: Concept Instruction Part II: 8 Full-Length Case Studies Part III: 50+ Mixed Exercises Part IV: A Full-Length Assessment With an illustrative approach to instruction, worked examples, and case studies, this easy-to-understand book simplifies many of the AI and Data Analytics key concepts, leading to an improvement of AI/ML system design skills.
Practical Guide To Machine Learning Nlp And Generative Ai Libraries Algorithms And Applications
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Author : T. Mariprasath
language : en
Publisher: CRC Press
Release Date : 2024-12-23
Practical Guide To Machine Learning Nlp And Generative Ai Libraries Algorithms And Applications written by T. Mariprasath and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-23 with Computers categories.
This is an essential resource for beginners and experienced practitioners in machine learning. This comprehensive guide covers a broad spectrum of machine learning topics, starting with an in-depth exploration of popular machine learning libraries. Readers will gain a thorough understanding of Scikit-learn, TensorFlow, PyTorch, Keras, and other pivotal libraries like XGBoost, LightGBM, and CatBoost, which are integral for efficient model development and deployment. The book delves into various neural network architectures, providing readers with a solid foundation in understanding and applying these models. Beginning with the basics of the Perceptron and its application in digit classification, it progresses to more complex structures such as multilayer perceptrons for financial forecasting, radial basis function networks for air quality prediction, and convolutional neural networks (CNNs) for image classification. Additionally, the book covers recurrent neural networks (RNNs) and their variants like long short-term memory (LSTM) and gated recurrent units (GRUs), which are crucial for time-series analysis and sequential data applications. Supervised machine learning algorithms are meticulously explained, with practical examples to illustrate their application. The book covers logistic regression and its use in predicting sports outcomes, decision trees for plant classification, random forests for traffic prediction, and support vector machines for house price prediction. Gradient boosting machines and their applications in genomics, AdaBoost for bioinformatics data classification, and extreme gradient boosting (XGBoost) for churn prediction are also discussed, providing readers with a robust toolkit for various predictive tasks. Unsupervised learning algorithms are another significant focus of the book, introducing readers to techniques for uncovering hidden patterns in data. Hierarchical clustering for gene expression data analysis, principal component analysis (PCA) for climate predictions, and singular value decomposition (SVD) for signal denoising are thoroughly explained. The book also explores applications like robot navigation and network security, demonstrating the versatility of these techniques. Natural language processing (NLP) is comprehensively covered, highlighting its fundamental concepts and various applications. The book discusses the overview of NLP, its fundamental concepts, and its diverse applications such as chatbots, virtual assistants, clinical NLP applications, and social media analytics. Detailed sections on text pre-processing, syntactic analysis, machine translation, text classification, named entity recognition, and sentiment analysis equip readers with the knowledge to build sophisticated NLP models. The final chapters of the book explore generative AI, including generative adversarial networks (GANs) for image generation, variational autoencoders for vibrational encoder training, and autoregressive models for time series forecasting. It also delves into Markov chain models for text generation, Boltzmann machines for pattern recognition, and deep belief networks for financial forecasting. Special attention is given to the application of recurrent neural networks (RNNs) for generation tasks, such as wind power plant predictions and battery range prediction, showcasing the practical implementations of generative AI in various fields.
Database Management System An Advanced Practical
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Author : Mr Vankamamidi Lakshmi Kartheek
language : en
Publisher: Nitya Publications
Release Date : 2022-01-01
Database Management System An Advanced Practical written by Mr Vankamamidi Lakshmi Kartheek and has been published by Nitya Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Computers categories.
This book aims to provide a broad DATABASE MANAGEMENT SYSTEMS AN ADVANCED PRACTICAL APPROACH for the importance of DATABASE MANAGEMENT SYSTEMS AN ADVANCED PRACTICAL APPROACH is well known in various engineering fields.
Python Data Cleaning And Preparation Best Practices
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Author : Maria Zervou
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-27
Python Data Cleaning And Preparation Best Practices written by Maria Zervou 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 2024-09-27 with Computers categories.
Take your data preparation skills to the next level by converting any type of data asset into a structured, formatted, and readily usable dataset Key Features Maximize the value of your data through effective data cleaning methods Enhance your data skills using strategies for handling structured and unstructured data Elevate the quality of your data products by testing and validating your data pipelines Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionProfessionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data products, often caused by inaccurate, incomplete, or inconsistent data. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, leading to valuable insights being missed that are difficult or impossible to obtain from structured data alone. To help you tackle these challenges, this book will take you on a journey through the upstream data pipeline, which includes the ingestion of data from various sources, the validation and profiling of data for high-quality end tables, and writing data to different sinks. You’ll focus on structured data by performing essential tasks, such as cleaning and encoding datasets and handling missing values and outliers, before learning how to manipulate unstructured data with simple techniques. You’ll also be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques to structure images, videos, and audio. By the end of this book, you’ll be proficient in data cleaning and preparation techniques for both structured and unstructured data.What you will learn Ingest data from different sources and write it to the required sinks Profile and validate data pipelines for better quality control Get up to speed with grouping, merging, and joining structured data Handle missing values and outliers in structured datasets Implement techniques to manipulate and transform time series data Apply structure to text, image, voice, and other unstructured data Who this book is for Whether you're a data analyst, data engineer, data scientist, or a data professional responsible for data preparation and cleaning, this book is for you. Working knowledge of Python programming is needed to get the most out of this book.
Jboss At Work A Practical Guide
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Author : Tom Marrs
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2005-10-13
Jboss At Work A Practical Guide written by Tom Marrs 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 2005-10-13 with Computers categories.
Consisting of a number of well-known open source products, JBoss is more a family of interrelated services than a single monolithic application. But, as with any tool that's as feature-rich as JBoss, there are number of pitfalls and complexities, too. Most developers struggle with the same issues when deploying J2EE applications on JBoss: they have trouble getting the many J2EE and JBoss deployment descriptors to work together; they have difficulty finding out how to get started; their projects don't have a packaging and deployment strategy that grows with the application; or, they find the Class Loaders confusing and don't know how to use them, which can cause problems. JBoss at Work: A Practical Guide helps developers overcome these challenges. As you work through the book, you'll build a project using extensive code examples. You'll delve into all the major facets of J2EE application deployment on JBoss, including JSPs, Servlets, EJBs, JMS, JNDI, web services, JavaMail, JDBC, and Hibernate. With the help of this book, you'll: Implement a full J2EE application and deploy it on JBoss Discover how to use the latest features of JBoss 4 and J2EE 1.4, including J2EE-compliant web services Master J2EE application deployment on JBoss with EARs, WARs, and EJB JARs Understand the core J2EE deployment descriptors and how they integrate with JBoss-specific descriptors Base your security strategy on JAAS Written for Java developers who want to use JBoss on their projects, the book covers the gamut of deploying J2EE technologies on JBoss, providing a brief survey of each subject aimed at the working professional with limited time. If you're one of the legions of developers who have decided to give JBoss a try, then JBoss at Work: A Practical Guide is your next logical purchase. It'll show you in plain language how to use the fastest growing open source tool in the industry today. If you've worked with JBoss before, this book will get you up to speed on JBoss 4, JBoss WS (web services), and Hibernate 3.
Distributed Database Management Systems
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Author : Saeed K. Rahimi
language : en
Publisher: John Wiley & Sons
Release Date : 2010-07-16
Distributed Database Management Systems written by Saeed K. Rahimi 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 2010-07-16 with Computers categories.
This book addresses issues related to managing data across a distributed database system. It is unique because it covers traditional database theory and current research, explaining the difficulties in providing a unified user interface and global data dictionary. The book gives implementers guidance on hiding discrepancies across systems and creating the illusion of a single repository for users. It also includes three sample frameworks—implemented using J2SE with JMS, J2EE, and Microsoft .Net—that readers can use to learn how to implement a distributed database management system. IT and development groups and computer sciences/software engineering graduates will find this guide invaluable.