Stock Market Data Analysis With Python

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Stock Market Data Analysis With Python

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Author : Khushabu Gupta
language : en
Publisher: Subrat Gupta
Release Date : 2025-10-01

Stock Market Data Analysis With Python written by Khushabu Gupta and has been published by Subrat Gupta this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-01 with Business & Economics categories.

Unlock the power of Python for advanced stock market data analysis with this comprehensive guide by Khushabu Gupta. Ideal for both beginners and experienced professionals, this book covers essential techniques in manipulating, analyzing, and visualizing financial data using Pandas and NumPy. Learn how to build robust algorithmic trading strategies, conduct time-series forecasting, and implement effective backtesting methods to validate your models. With hands-on examples and practical case studies, you'll gain the skills needed to tackle real-world financial challenges and optimize investment decisions. Whether you're an aspiring quantitative analyst, data scientist, or retail investor, 'Stock Market Data Analysis with Python' offers a thorough, step-by-step approach to automating your trading workflows and extracting actionable insights from stock market data. Stay ahead of the curve in today’s data-driven financial landscape by mastering the essential tools and techniques that empower successful algorithmic trading.

Python Algorithmic Trading For The Stock Market

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Author : Khushabu Gupta
language : en
Publisher: Subrat Gupta
Release Date : 2025-09-30

Python Algorithmic Trading For The Stock Market written by Khushabu Gupta and has been published by Subrat Gupta this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-30 with Business & Economics categories.

Unlock the power of automated trading with 'Python Algorithmic Trading for the Stock Market' by Khushabu Gupta. Designed for traders, investors, and programmers, this comprehensive guide shows you how to harness Python to build, backtest, and deploy algorithmic trading strategies in the stock market. Covering key concepts such as technical analysis, backtesting frameworks, data handling, and risk management, this book takes you step-by-step from the basics of Python programming to developing robust trading bots. Whether you are new to stock trading or a seasoned professional looking to automate your strategies, you’ll learn how to leverage the latest Python libraries, APIs, and real-world datasets for practical, hands-on results. With clear examples, actionable insights, and best practices for strategy optimization, this book empowers you to design, test, and execute your own profitable trading systems. Stay ahead of the market by discovering how machine learning, data visualization, and automation workflows can transform your investment returns. Start your journey to mastering algorithmic stock trading with Python today!

Problem Solving Python Programming

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Author : Sandhya Kumari
language : en
Publisher: RK Publication
Release Date : 2024-07-16

Problem Solving Python Programming written by Sandhya Kumari and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-16 with Computers categories.

Problem Solving & Python Programming is a comprehensive guide aimed at developing programming skills and logical thinking using Python. This book covers the fundamentals of Python, including data types, control structures, functions, and libraries, while emphasizing problem-solving techniques to tackle real-world challenges. Through practical examples and exercises, it teaches readers to break down complex problems, design algorithms, and implement solutions efficiently. Ideal for beginners and those new to programming, it equips learners with the tools needed to build a strong programming foundation and apply Python to diverse applicatio

Modern Graph Theory Algorithms With Python

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Author : Colleen M. Farrelly
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-07

Modern Graph Theory Algorithms With Python written by Colleen M. Farrelly 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 2024-06-07 with Computers categories.

Solve challenging and computationally intensive analytics problems by leveraging network science and graph algorithms Key Features Learn how to wrangle different types of datasets and analytics problems into networks Leverage graph theoretic algorithms to analyze data efficiently Apply the skills you gain to solve a variety of problems through case studies in Python Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWe are living in the age of big data, and scalable solutions are a necessity. Network science leverages the power of graph theory and flexible data structures to analyze big data at scale. This book guides you through the basics of network science, showing you how to wrangle different types of data (such as spatial and time series data) into network structures. You’ll be introduced to core tools from network science to analyze real-world case studies in Python. As you progress, you’ll find out how to predict fake news spread, track pricing patterns in local markets, forecast stock market crashes, and stop an epidemic spread. Later, you’ll learn about advanced techniques in network science, such as creating and querying graph databases, classifying datasets with graph neural networks (GNNs), and mining educational pathways for insights into student success. Case studies in the book will provide you with end-to-end examples of implementing what you learn in each chapter. By the end of this book, you’ll be well-equipped to wrangle your own datasets into network science problems and scale solutions with Python.What you will learn Transform different data types, such as spatial data, into network formats Explore common network science tools in Python Discover how geometry impacts spreading processes on networks Implement machine learning algorithms on network data features Build and query graph databases Explore new frontiers in network science such as quantum algorithms Who this book is for If you’re a researcher or industry professional analyzing data and are curious about network science approaches to data, this book is for you. To get the most out of the book, basic knowledge of Python, including pandas and NumPy, as well as some experience working with datasets is required. This book is also ideal for anyone interested in network science and learning how graph algorithms are used to solve science and engineering problems. R programmers may also find this book helpful as many algorithms also have R implementations.

Intelligent Computing And Communication Techniques

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Author : Arvind Dagur
language : en
Publisher: CRC Press
Release Date : 2025-06-10

Intelligent Computing And Communication Techniques written by Arvind Dagur and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-10 with Computers categories.

This book contains a prolific compilation of research papers presented at the International Conference on Intelligent Computing and Communication Techniques (ICICCT 2024). Some of its key features include: In-depth coverage of artificial intelligence, blockchain, and their role in enhancing smart living and security, with a focus on intelligent computing. Depiction of detailed system models and architecture to illustrate the practical applications of AI. Discussion on the role of AI and blockchain in banking, healthcare, navigation, communication, security, etc. Analysis of the challenges and opportunities presented by intelligent computing, communication techniques and blockchain in healthcare, education, banking and related industries. It is designed for academics, researchers, students, and professionals seeking to expand their knowledge and engage with current research on artificial intelligence, secure transactions, real-time monitoring, and security.

Big Data Analytics For Cyber Physical System In Smart City

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Author : Mohammed Atiquzzaman
language : en
Publisher: Springer Nature
Release Date : 2020-01-11

Big Data Analytics For Cyber Physical System In Smart City written by Mohammed Atiquzzaman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-11 with Technology & Engineering categories.

This book gathers a selection of peer-reviewed papers presented at the first Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2019) conference, held in Shengyang, China, on 28–29 December 2019. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Integrated Technologies In Electrical Electronics And Biotechnology Engineering

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Author : Gaurav Aggarwal
language : en
Publisher: CRC Press
Release Date : 2025-03-31

Integrated Technologies In Electrical Electronics And Biotechnology Engineering written by Gaurav Aggarwal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Science categories.

The conference was aimed to bring researchers, practicing engineers, faculty members and students from across the globe to a common platform to share their research ideas that would pave way to attain solution to various real time problems. Many eminent researchers from different countries participated and interacted with the young students and budding researchers from various institutions. The objective of this conference was to connect with junior and senior scholars working with educational architecture of the past, present or future in the area of Semiconductor Devices & Electronic Circuit Design, Machine Vision & Signal Processing, Communication Technologies and Systems, Electromagnetic, RF, Microwave & Wearable Technology, Nano-Technologies & IC Fabrication, Biotechnology, Automation & Robotics, Electrical Machines and Adjustable Speed Drives, Renewable Energy Sources, Smart grids Technologies & Applications. Key features included keynote presentations from renowned experts, paper presentations showcasing novel research, interactive panel discussions, and exploring practical applications of emerging technologies.

Data Analytics For Finance Using Python

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Author : Nitin Jaglal Untwal
language : en
Publisher: CRC Press
Release Date : 2024-12-30

Data Analytics For Finance Using Python written by Nitin Jaglal Untwal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Computers categories.

Unlock the power of data analytics in finance with this comprehensive guide. Data Analytics for Finance Using Python is your key to unlocking the secrets of the financial markets. In this book, you’ll discover how to harness the latest data analytics techniques, including machine learning and inferential statistics, to make informed investment decisions and drive business success. With a focus on practical application, this book takes you on a journey from the basics of data preprocessing and visualization to advanced modeling techniques for stock price prediction. Through real-world case studies and examples, you’ll learn how to: Uncover hidden patterns and trends in financial data Build predictive models that drive investment decisions Optimize portfolio performance using data-driven insights Stay ahead of the competition with cutting-edge data analytics techniques Whether you’re a finance professional seeking to enhance your data analytics skills or a researcher looking to advance the field of finance through data-driven insights, this book is an essential resource. Dive into the world of data analytics in finance and discover the power to make informed decisions, drive business success, and stay ahead of the curve. This book will be helpful for students, researchers, and users of machine learning and financial tools in the disciplines of commerce, management, and economics.

Python For Financial Data Analysis

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Author : J.P.Morgan
language : en
Publisher: J.P.Morgan
Release Date :

Python For Financial Data Analysis written by J.P.Morgan and has been published by J.P.Morgan this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

Python for Financial Data Analysis: Unlock the Secrets of the Market Master the Art of Financial Data Analysis with Python! Are you ready to unlock the secrets of the financial markets? Dive into Python for Financial Data Analysis: Unlock the Secrets of the Market, your ultimate guide to mastering the intricacies of financial data using Python. Tailored for Python programmers, web developers, web application developers, students, and trading enthusiasts, this book is your gateway to making informed investment decisions and thriving in the world of finance. Key Features: Comprehensive Coverage: Gain a deep understanding of how to use Python for financial analysis and visualization. From basic concepts to advanced techniques, this book covers it all, ensuring you have the knowledge to tackle any financial data challenge. Practical Examples and Case Studies: Learn by doing! This book is packed with practical examples and real-world case studies that demonstrate how to apply Python for financial data analysis. See firsthand how to make sense of market trends, identify investment opportunities, and predict future movements. Step-by-Step Guidance: Whether you're a seasoned Python programmer or just starting out, this book provides step-by-step instructions on using Python for financial analysis. Each chapter builds on the previous one, ensuring a smooth learning curve. Eliminate Guesswork: Make informed investment decisions by eliminating guesswork. Learn how to leverage Python to uncover hidden patterns, trends, and insights within financial data. Say goodbye to speculation and hello to data-driven decision-making. Tools and Techniques: Discover a wide range of tools and techniques for financial data analysis, including data cleaning, exploratory data analysis, statistical modeling, and visualization. Equip yourself with the skills needed to analyze financial data with Python and navigate the complexities of the financial markets. Why Choose This Book? Tailored for Your Needs: Whether you're a Python programmer looking to expand your skillset, a web developer interested in financial applications, a student exploring data analysis, or a trading enthusiast seeking to improve your investment strategies, this book is designed with you in mind. Learn how to use Python for financial analysis and become a proficient financial analyst. Informed Investment Decisions: By the end of this book, you'll have the confidence and skills to analyze financial data like a pro. Make informed investment decisions, maximize your returns, and stay ahead of the competition by utilizing Python for data analysis. Learn Essential Skills: Understand how to get financial data in Python, use Python libraries for financial analysis, and apply Python code for financial analysis. Master the integration of Python and statistics for financial analysis and explore financial statement analysis using Python. Don't miss out on the opportunity to elevate your financial data analysis skills. Get your copy of Python for Financial Data Analysis: Unlock the Secrets of the Market today and start your journey towards financial mastery! Click "Buy Now" to Unlock the Secrets of the Financial Market with Python!

Python For Programmers

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Author : Paul Deitel
language : en
Publisher: Prentice Hall
Release Date : 2019-03-15

Python For Programmers written by Paul Deitel and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Computers categories.

The professional programmer’s Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today’s most compelling, leading-edge computing technologies and programming in Python–one of the world’s most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you’ll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you’ll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You’ll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter® Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualizations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Accompanying code examples are available here: http://ptgmedia.pearsoncmg.com/imprint_downloads/informit/bookreg/9780135224335/9780135224335_examples.zip. Register your product for convenient access to downloads, updates, and/or corrections as they become available. See inside book for more information.