Mastering Python For Data Engineering
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Mastering Python For Data Engineering
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Author : Thompson Carter
language : en
Publisher: Independently Published
Release Date : 2025-01-09
Mastering Python For Data Engineering written by Thompson Carter and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-09 with Computers categories.
Mastering Python for Data Engineering: Transform and Manipulate Big Data with Python Unlock the true potential of Python for big data manipulation and engineering with Mastering Python for Data Engineering. This comprehensive guide is designed to help data engineers and aspiring professionals transform, process, and analyze massive datasets efficiently. By leveraging Python's powerful libraries and tools, you'll be equipped to build scalable data pipelines, integrate various data sources, and optimize data workflows for performance. From basic data wrangling to advanced engineering techniques, this book provides a practical, hands-on approach to mastering data engineering tasks with Python, making it the perfect companion for anyone aiming to work with big data. What You'll Learn: The fundamentals of Python for data engineering, including essential libraries like pandas, NumPy, and Dask. Building efficient data pipelines for ETL (Extract, Transform, Load) processes. Working with large datasets using parallel and distributed processing tools like Apache Spark and Dask. Integrating data from various sources, such as databases, APIs, and streaming data. Data transformation and cleaning techniques to prepare data for analysis. Optimizing performance and scaling data workflows with Python. With step-by-step guidance and practical examples, Mastering Python for Data Engineering will show you how to handle data at scale, integrate different data sources, and build automated data workflows that are crucial for modern data infrastructure. Dive into the world of data engineering with Python and learn how to transform raw data into actionable insights while building systems that can handle vast amounts of information.
Mastering Python
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Author : Michael B. White
language : en
Publisher:
Release Date : 2019-01-13
Mastering Python written by Michael B. White and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-13 with Computers categories.
Unlike some guides that give you just the basics that you need to get started, this book teaches you everything you need to know about using Python, including what you can use it for. Python is a diverse language and is the foundation of much of what we use in the world today. The reader will be happy to know that this programming language is relatively easy to learn. The book is divided into five sections to make the journey easy for the student: ✅ Part 1 - Data Structures and Algorithms ✅ Part 2 - Machine Learning ✅ Part 3 - Django ✅ Part 4 - ArcGIS Programming ✅ Part 5 - Software Development and Testing ���� If you want to master python, order your copy today. ����
Data Engineering With Python
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Author : Paul Crickard
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-10-23
Data Engineering With Python written by Paul Crickard 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 2020-10-23 with Computers categories.
Build, monitor, and manage real-time data pipelines to create data engineering infrastructure efficiently using open-source Apache projects Key Features Become well-versed in data architectures, data preparation, and data optimization skills with the help of practical examples Design data models and learn how to extract, transform, and load (ETL) data using Python Schedule, automate, and monitor complex data pipelines in production Book DescriptionData engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.What you will learn Understand how data engineering supports data science workflows Discover how to extract data from files and databases and then clean, transform, and enrich it Configure processors for handling different file formats as well as both relational and NoSQL databases Find out how to implement a data pipeline and dashboard to visualize results Use staging and validation to check data before landing in the warehouse Build real-time pipelines with staging areas that perform validation and handle failures Get to grips with deploying pipelines in the production environment Who this book is for This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition. No previous knowledge of data engineering is required.
Mastering Python
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Author : Michael White
language : en
Publisher:
Release Date : 2018-10-12
Mastering Python written by Michael White and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-12 with categories.
Unlike some guides that give you just the basics that you need to get started, this book teaches you everything you need to know about using Python including what you can use it for. Python is a diverse language and is the foundation of much of what we use in the world today. Most data applications, many websites and machine learning are all powered by Python and you'll be pleased to learn that it really isn't difficult to learn. The book is divided into five sections to make it easier for the reader: Part 1 - Data Structures and Algorithms Part 2 - Machine Learning Part 3 - Django Part 4 - ArcGIS Programming Part 5 - Software Development and Testing
Python For Data Science
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Author : Kok Keong Teo
language : en
Publisher: Independently Published
Release Date : 2023-09-19
Python For Data Science written by Kok Keong Teo and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-19 with categories.
Embark on a Transformative Data Science Adventure with 'Python for Data Science: Zero to Hero in 10 Days'! Dive into Python's incredible capabilities for data analysis and machine learning, even if you're a complete beginner. In just a span of 10 days, this immersive guide will empower you to evolve from a novice to a skilled data science practitioner. And the best part? We've made it even more accessible for you. All the code examples featured in this book will be readily available on GitHub. Just head over to the Python for Data Science: Zero to Hero in 10 Days Facebook page, where we'll provide the link for your convenience. About the Author Teo Kok Keong holds a Master of Engineering degree from Nanyang Technological University, where he specialized in "Time-series Prediction using Wavelet Neural Network" for his thesis. With a diverse career path spanning research, software development, and teaching in institutes of higher learning, Teo has accumulated a wealth of experience. Over the course of a decade, he has been dedicated to education within the School of Engineering, where he has not only delivered instruction but also contributed to the development of curricula. His teaching portfolio ranges from Microcontroller and C/C++ Programming to Data Science, catering to both full-time students and part-time adult learners.
Python For Data Engineering
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Author : Greyson Chesterfield
language : en
Publisher: Independently Published
Release Date : 2025-01-02
Python For Data Engineering written by Greyson Chesterfield and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-02 with Computers categories.
Python for Data Engineering: Build ETL Pipelines and Handle Big Data Efficiently with Python Unlock the full potential of data engineering with "Python for Data Engineering", the essential guide for aspiring data engineers, data scientists, and IT professionals seeking to master the art of building robust ETL pipelines and managing big data using Python. Whether you're just beginning your data engineering journey or looking to enhance your existing skills, this comprehensive handbook provides the tools, techniques, and insights necessary to transform raw data into valuable assets for your organization. Dive into expertly structured chapters that blend theoretical knowledge with practical applications, covering everything from the fundamentals of data engineering and Python programming to advanced topics like distributed computing, real-time data processing, and cloud integration. Learn how to design, develop, and deploy scalable ETL pipelines that efficiently extract, transform, and load data from diverse sources. Discover best practices for handling large datasets, optimizing performance, and ensuring data quality and integrity throughout the data lifecycle. "Python for Data Engineering" empowers you to: Master ETL Processes: Understand the core principles of ETL and learn how to implement efficient data extraction, transformation, and loading strategies using Python. Handle Big Data: Explore techniques for managing and processing large-scale datasets with tools like Apache Spark, Hadoop, and Dask, all within the Python ecosystem. Automate Workflows: Streamline data engineering tasks by automating repetitive processes with Python scripts and workflow management tools such as Airflow and Luigi. Design Scalable Pipelines: Build resilient and scalable data pipelines that can handle increasing data volumes and complexity with ease. Ensure Data Quality: Implement robust data validation, cleansing, and monitoring practices to maintain high-quality data standards. Leverage Cloud Services: Integrate Python-based data engineering solutions with leading cloud platforms like AWS, Google Cloud, and Azure for enhanced flexibility and scalability. Optimize Performance: Fine-tune your data engineering workflows for maximum efficiency, reducing latency and improving throughput. Implement Security Best Practices: Protect sensitive data by applying security measures and ensuring compliance with industry standards and regulations. Visualize and Report Data: Create insightful visualizations and reports to communicate data findings effectively using libraries like Matplotlib, Seaborn, and Plotly. Stay Ahead with Advanced Topics: Delve into cutting-edge technologies such as machine learning integration, real-time analytics, and serverless computing to keep your skills current and in demand. Packed with real-world examples, hands-on exercises, and expert tips, "Python for Data Engineering" serves as your indispensable companion in navigating the dynamic field of data engineering. Whether you're building data pipelines for business intelligence, supporting data-driven decision-making, or driving innovation through data analytics, this book equips you with the knowledge and skills to excel. Key Features: Comprehensive coverage of data engineering fundamentals and advanced Python techniques Step-by-step tutorials for building and deploying ETL pipelines In-depth guides to handling and processing big data with Python-based tools Real-world case studies illustrating best practices and common challenges Practical exercises and projects to reinforce learning and develop hands-on experience Insights into the latest trends and technologies in the data engineering landscape
A Practical Guide To Data Engineering
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Author : Pedram Ariel Rostami
language : en
Publisher: Starseed AI
Release Date :
A Practical Guide To Data Engineering written by Pedram Ariel Rostami and has been published by Starseed AI this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.
"A Practical Guide to Machine Learning and AI: Part-I" is an essential resource for anyone looking to dive into the world of artificial intelligence and machine learning. Whether you're a complete beginner or have some experience in the field, this book will equip you with the fundamental knowledge and hands-on skills needed to harness the power of these transformative technologies. In this comprehensive guide, you'll embark on an engaging journey that starts with the basics of data engineering. You'll gain a solid understanding of big data, the key roles involved, and how to leverage the versatile Python programming language for data-centric tasks. From mastering Python data types and control structures to exploring powerful libraries like NumPy and Pandas, you'll build a strong foundation to tackle more advanced concepts. As you progress, the book delves into the realm of exploratory data analysis (EDA), where you'll learn techniques to clean, transform, and extract insights from your data. This sets the stage for the heart of the book - machine learning. You'll explore both supervised and unsupervised learning, diving deep into regression, classification, clustering, and dimensionality reduction algorithms. Along the way, you'll encounter real-world examples and hands-on exercises to reinforce your understanding and apply what you've learned. But this book goes beyond just the technical aspects. It also addresses the ethical considerations surrounding machine learning, ensuring you develop a well-rounded perspective on the responsible use of these powerful tools. Whether your goal is to jumpstart a career in data science, enhance your existing skills, or simply satisfy your curiosity about the latest advancements in AI, "A Practical Guide to Machine Learning and AI: Part-I" is your comprehensive companion. Prepare to embark on an enriching journey that will equip you with the knowledge and skills to navigate the exciting frontiers of artificial intelligence and machine learning.
Engineering With Python And Ai
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Author : Ahmed Abdulla
language : en
Publisher: Independently Published
Release Date : 2024-06-23
Engineering With Python And Ai written by Ahmed Abdulla and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-23 with Computers categories.
Unlock the power of Python and revolutionize your engineering projects with this comprehensive guide. "Engineering with Python: A Comprehensive Guide for Modern Engineers" is an essential resource for engineers and students looking to harness the versatility and efficiency of Python in their work. This book provides a practical, hands-on approach to using Python in various engineering disciplines, from data analysis and modeling to automation and machine learning. Whether you are a mechanical, electrical, civil, or chemical engineer, this guide covers the essential tools and techniques you need to tackle complex engineering problems and innovate solutions. Inside this book, you will find: Fundamentals of Python Programming: Learn the basics of Python, including variables, control flow, data structures, and functions. Set up your Python development environment with ease. Engineering Libraries and Tools: Master essential libraries like NumPy, SciPy, Pandas, Matplotlib, and Seaborn for numerical computation, data manipulation, and visualization. Explore advanced libraries for machine learning and deep learning. Data Analysis and Visualization: Import, process, and analyze engineering data from Excel and CSV files. Create professional graphs and visualizations to communicate your findings effectively. Modeling and Simulation: Develop mathematical models and simulate engineering systems using differential equations and linear algebra. Apply these techniques to real-world problems in mechanical, electrical, and civil engineering. Statistical Analysis and Optimization: Perform descriptive and inferential statistical analyses on engineering data. Use optimization techniques to enhance engineering designs and processes. Machine Learning and Artificial Intelligence: Implement machine learning algorithms to optimize engineering processes and predict outcomes. Dive into neural networks and deep learning to solve complex engineering problems. Automation and Scripting: Write Python scripts to automate repetitive engineering tasks and improve efficiency. Develop automated solutions for data analysis, modeling, and report generation. Advanced Projects and Case Studies: Explore integrated projects that demonstrate the application of Python in smart manufacturing, smart city traffic management, renewable energy, and structural health monitoring. Learn from detailed case studies based on real-world engineering challenges. Who is this book for? Engineering students seeking to enhance their programming skills. Professional engineers looking to incorporate Python into their workflows. Researchers and academics aiming to leverage Python for data analysis and modeling. Technical managers overseeing engineering projects and innovations. Why choose this book? "Engineering with Python" offers a unique blend of theoretical knowledge and practical applications, making it an invaluable resource for engineers at all levels. With clear explanations, step-by-step instructions, and real-world examples, this book empowers you to solve engineering problems efficiently and innovate in your field. Transform your engineering projects with the power of Python. Get your copy of "Engineering with Python: A Comprehensive Guide for Modern Engineers" today and take the first step towards mastering Python in engineering!
Data Mastery Python
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Author : Lauren Glass
language : en
Publisher:
Release Date : 2019-05-05
Data Mastery Python written by Lauren Glass and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-05 with categories.
Are you working on an exciting data project? Preparing for a data interview? This book Data Mastery - Python is a focused preparation guide--with brevity and efficiency in mind. You will learn Python syntax quickly, practice, and continue to use this book as a reference.It is meant for Software Engineers who already know other programming languages but want a reference for the top programming language for data work, Data Analysts or Scientists who need to learn enough Python for a project or an interview, and last but not least Data Engineers or Business Intelligence Developers refreshing for interviews.
Python Programming
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Author : Andrew Park
language : en
Publisher:
Release Date : 2020-11-14
Python Programming 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 2020-11-14 with Computers categories.
If you want to learn Python in one week (or less) and learn it well, with useful applications to Data Analysis, Machine Learning and Data Science, then keep reading. Python is one of the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also one of the major attractions for this language. That's the reason why Python is a perfect fit with Data Analysis, Machine Learning and Data Science. Data is the future. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations. The goal of this 4-in-1 bundle is simple: explaining everything you need to know to Master Python. With a special emphasis on the main steps that are needed to correctly implement Data Analysis and Machine Learning algorithms, In manuscript one, Python for Beginners, you will learn: How to install Python What are the different Python Data Types and Variables Basic Operators of Python Language Data Structures and Functions Conditional and Loops in Python And Much More! In manuscript two, Python Advanced Guide, you will master: Object-Oriented Programming (OOP), Inheritance and Polymorphism Essential Programming Tools Exception Handling Working with Files And Much More! In manuscript three, Python for Data Analysis, you will learn: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis The 7 Python libraries that make Python one of the best choices for Data Analysis Pandas, Jupyter and PyTorch And Much More! In manuscript four, Applications to Data Science, you will understand: How Data Visualization and Matplotlib can help you to understand the data you are working with. Neural Networks Decision Trees What industries are using data to improve their business with 14 real-world applications And So Much More! Where most books about Python programming are theoretical and have few or little practical examples, this book provides lots of simple, step-by-step examples and illustrations that are used to underline key concepts and help improve your understanding. Furthermore, topics are carefully selected to give you broad exposure to Python, while not overwhelming you with too much information. Also, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples. Even if you have never coded before, this is the perfect guide because it breaks down complex concepts into simple steps and in a concise and simple way that fits well with beginners. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them, and the most important real-world applications. Would you like to know more?Scroll Up and Click the BUY NOW Button to Get Your Copy!