Download or read book Powerful Python written by Aaron Maxwell and published by . This book was released on 2017-05-07 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many books for those new to Python, new to programming, or both. Powerful Python is different. Written for experienced developers like you, its carefully crafted chapters teach intermediate and advanced strategies, patterns, and tools for modern Python. Focused on Python 3, with full support for 2.7. DRM-free digital upgrade: powerfulpython.com/book-upgrade "Feels like Neo learning Jiu jitsu in the Matrix." - John Beauford (@johnbeauford) "I just wanted to let you know what an excellent book this is... I keep going back to your book to learn Python." - Fahad Qazi, London, UK "Thanks. Keep up the good work. Your chapter on decorators is the best I have seen on that topic." - Leon Tietz, Minnesota, USA "Powerful Python is already helping me get huge optimization gains." - Timothy Dobbins (@TmthyDobbins) "What have I found good and valuable about the book so far? Everything honestly. The clear explanations, solid code examples have really helped me advance as a Python coder... Thank you! It has really helped me grasp some advanced concepts that I felt were beyond my abilities." - Nick S., Colorado, USA For data scientists, back-end engineers, web developers, sysadmins, devops, QA testers and more. What's included: An unrelenting selective spotlight on what's most valuable and impactful to working, full-time, professional Python developers Well-researched, detailed, realistic code on almost every page, powerfully illustrating key points. Very little "toy code" How to use decorators to add rich features to functions and classes; untangle distinct, frustratingly intertwined concerns in your code; and build powerful, extensible software frameworks How to use Python in ways that incentivize other developers to use and re-use your code, again and again... amplifying the impact of the code you write, and boosting your reputation among your peers Powerfully and easily weave iterators and generators throughout your applications, making them massively scalable, highly performant, and far more readable and maintainable How to fully leverage Python's exception and error model... giving you a detailed understanding even experienced Pythonistas often lack, and putting some of the most powerfully Pythonic exception-handling patterns in your toolbox How "magic methods" imbue natural, readable, expressive syntax into your classes and objects... and how to "break the rules" to craft stunningly intuitive, compellingly reusable library interfaces Valuable and powerful design patterns, and how Python's special language features give you uniquely powerful implementations not possible in other languages Deep and detailed instruction on how to write practical, realistic unit tests... using test-driven development to easily get into a state of flow... where you find yourself implementing feature after feature, keeping your focus with ease for long periods of time How to rapidly set up effective logging for scripts, sprawling Python applications, and everything in between An enthusiastic and unapologetic focus on Python 3, and what makes it great... with full explanation and support for getting the same results with Python 2.7 More at PowerfulPython.com.

Download or read book Python Powered Strategies written by John Anderson and published by Independently Published. This book was released on 2024-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embark on a transformative journey with 'Python-Powered Strategies: Unleashing Vision and Language Models from Pretraining to Seamless AWS Deployment.' This comprehensive exploration navigates the dynamic landscape of model development, offering insights into the versatile capabilities of Python in crafting robust vision and language models. From the foundational principles of pretraining to the intricacies of seamless deployment on AWS, this topic unveils powerful strategies that propel your models into the future. Immerse yourself in the synergy of Python's prowess and AWS infrastructure, unlocking the full potential of cutting-edge technologies for a seamless and impactful model deployment experience.

Download or read book Switching Strategies for Power Electronic Converters written by Shivkumar V. Iyer and published by Springer Nature. This book was released on 2023-11-18 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a concise introduction to switching strategies for power electronics. It provides an in-depth examination of this one concept giving a newcomer a complete immersive experience which has both the depth that is needed to gain confidence yet is simple to understand. The authors examine the basic operation of power electronic systems from scratch and with the help of simulations, how these systems can be constructed. The approach used treats power electronics similar to puzzles and rather than merely presenting them and describing how they work, explore why they came to have the construction they have, and how they could potentially be modified. The authors make extensive use of simulations, with every theory and every result accompanied by a simulation. All simulations are performed by the free and open source Python programming language and the free and open source circuit simulator Python Power Electronics.

Download or read book Structural Optimizations in Strategic Medium Voltage Power System Planning written by Leon Thurner and published by kassel university press GmbH. This book was released on 2018-06-25 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis introduces a comprehensive methodology for the automation of the strategic power system planning process in the medium voltage level. The methodology takes the predicted development of load and distributed generation as well as the age structure of the components into account. Target grid structures are computed with a heuristic search that considers constraints for the grid topology, power flow parameters in normal as well as contingency operation, fault currents and service reliability. The implementation is based on the newly presented open source power systems analysis tool pandapower, which allows grid modelling and analysis with a high degree of automation. The developed methodology is applied to three real case study grids from different power system operators. The structural optimization leads to a reduction of investment and operational costs within the planning horizon of up to 56% in the target grids compared to the present grid structures. The successful application of the developed method to a diverse set of case studies demonstrates its general applicability in realistic planning problems.

Download or read book Ultimate Python for Fintech Solutions written by Bhagvan Kommadi and published by Orange Education Pvt Ltd. This book was released on 2024-07-12 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: TAGLINE Creating Next Gen Apps in Finance KEY FEATURES ● Master the Python libraries and packages essential for financial applications, enabling robust development. ● Utilize Python for developing applications that process financial information, visualize data in diverse formats, and create insightful representations. ● Derive analytical insights from mathematical models integrated into Python applications for data-driven decision-making in finance and fintech. DESCRIPTION Dive into the dynamic world where finance meets fintech with Python's versatile capabilities in this 'Ultimate Python for Fintech Solutions'. Whether you're aiming to build secure trading platforms, conduct deep statistical analysis, or pioneer next-generation financial technologies, this book quips you with the knowledge, tools, and practical insights to succeed. This book starts with Python's foundational programming techniques, essential for understanding financial principles and laying the groundwork for robust applications. You will learn to build scalable solutions that handle complex financial data with ease by using Python for analysis, forecasting, and data visualization. Next, it moves to explore advanced topics like AI/ML applications tailored for finance, enabling you to unlock predictive insights and streamline decision-making processes. You will discover how Python integrates cutting-edge technologies such as Big Data and Blockchain, to offer innovative solutions for modern fintech challenges. By the end of this expansive book, you will gain the expertise needed to develop sophisticated financial applications, visualize data effectively across desktop and web platforms, and drive innovation in fintech. WHAT WILL YOU LEARN ● Learn to build robust applications tailored for financial analysis, modeling, and fintech solutions using Python. ● Learn to analyze large volumes of financial data, and visualize insights effectively. ● Apply advanced AI/ML techniques to predict trends, optimize financial strategies, and automate decision-making processes. ● Integrate Python with Big Data platforms and Blockchain technologies to work with massive datasets and decentralized financial systems. ● Acquire the knowledge and skills to innovate in the fintech space to address modern financial challenges and opportunities. WHO IS THIS BOOK FOR? This book is for working professionals, students, business managers, consultants, technical/functional analysts, anyone wishing to improve their skills in Fintech with Python. This book will be a great start for a programmer who wants to start on the Python tech stack and make a career in Fintech space. The prerequisites for the reader will be basic mathematics and advanced math topics such as time series, derivatives, and integrals. The outcome for the reader will be to understand mathematical modeling and to have capability to develop next gen financial apps. TABLE OF CONTENTS 1. Getting Started on Python Infrastructure and Building Financial Apps 2. Learning Financial Concepts Using Python 3. Data Structures and Algorithms Using Python 4. Object Oriented Programming Using Python 5. Building Simulation and Mathematical Analysis Tools Using Python 6. Stochastic Mathematics and Building Models Using Python 7. Prediction Algorithms Using Python 8. Data Science and Statistical Algorithms Using Python 9. Desktop and Web Charting Using Python 10. AI/ML Apps Using Python 11. Big Data/Blockchain-Based Solutions Using Python 12. Next Generation FinTech Apps Using Python with Financial Singularity Index

Download or read book Python for Algorithmic Trading written by Yves Hilpisch and published by O'Reilly Media. This book was released on 2020-11-12 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

Download or read book Learn Python 3 the Hard Way written by Zed A. Shaw and published by Addison-Wesley Professional. This book was released on 2017-06-26 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Python 3 the Hard Way, you’ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises. Install a complete Python environment Organize and write code Fix and break code Basic mathematics Variables Strings and text Interact with users Work with files Looping and logic Data structures using lists and dictionaries Program design Object-oriented programming Inheritance and composition Modules, classes, and objects Python packaging Automated testing Basic game development Basic web development It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Python programmer. This Book Is Perfect For Total beginners with zero programming experience Junior developers who know one or two languages Returning professionals who haven’t written code in years Seasoned professionals looking for a fast, simple, crash course in Python 3

Download or read book Machine Learning for FInance written by Vincent Bisette and published by Independently Published. This book was released on 2024-05-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reactive Publishing Unlock the full potential of your financial analysis with "Machine Learning for Finance." This comprehensive guide takes you from the basics of Python programming to advanced machine learning techniques tailored specifically for financial applications. Perfect for finance professionals, data scientists, and anyone eager to harness the power of AI in finance, this book provides: Step-by-step tutorials on Python and key machine learning libraries. Practical case studies demonstrating real-world financial applications. Techniques for predicting stock prices, managing risk, and optimizing portfolios. Insights into the latest trends in financial technology. Written by an industry expert, "Machine Learning for Finance" bridges the gap between finance and technology, equipping you with the tools to make data-driven decisions and stay ahead in the competitive financial landscape. Whether you're a seasoned professional or a curious beginner, this book is your ultimate resource for mastering the intersection of finance and machine learning. Transform your financial strategies with Python and join the future of finance today!

Download or read book Python for Finance written by Dmytro Zherlitsyn and published by BPB Publications. This book was released on 2024-07-30 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: DESCRIPTION Python's intuitive syntax and beginner-friendly nature makes it an ideal programming language for financial professionals. It acts as a bridge between the world of finance and data analysis. This book will introduce essential concepts in financial analysis methods and models, covering time-series analysis, graphical analysis, technical and fundamental analysis, asset pricing and portfolio theory, investment and trade strategies, risk assessment and prediction, and financial ML practices. The Python programming language and its ecosystem libraries, such as Pandas, NumPy, SciPy, Statsmodels, Matplotlib, Seaborn, Scikit-learn, Prophet, and other data science tools will demonstrate these rooted financial concepts in practice examples. This book will help you understand the concepts of financial market dynamics, estimate the metrics of financial asset profitability, predict trends, evaluate strategies, optimize portfolios, and manage financial risks. You will also learn data analysis techniques using Python programming language to understand the basics of data preparation, visualization, and manipulation in the world of financial data. KEY FEATURES ● Comprehensive guide to Python for financial data analysis and modeling. ● Practical examples and real-world applications for immediate implementation. ● Covers advanced topics like regression, Machine Learning and time series forecasting. WHAT YOU WILL LEARN ● Learn financial data analysis using Python data science libraries and techniques. ● Learn Python visualization tools to justify investment and trading strategies. ● Learn asset pricing and portfolio management methods with Python. ● Learn advanced regression and time series models for financial forecasting. ● Learn risk assessment and volatility modeling methods with Python. WHO THIS BOOK IS FOR This book is designed for financial analysts and other professionals interested in the financial industry with a basic understanding of Python programming and statistical analysis. It is also suitable for students in finance and data science who wish to apply Python tools to financial data analysis and decision-making. TABLE OF CONTENTS 1. Getting Started with Python for Finance 2. Python Tools for Data Analysis: Primer to Pandas and NumPy 3. Financial Data Manipulation with Python 4. Exploratory Data Analysis for Finance 5. Investment and Trading Strategies 6. Asset Pricing and Portfolio Management 7. Time Series Analysis and Financial Data Forecasting 8. Risk Assessment and Volatility Modelling 9. Machine Learning and Deep Learning in Finance 10. Time Series Analysis and Forecasting with FB Prophet Library Appendix A: Python Code Examples for Finance Appendix B: Glossary Appendix C: Valuable Resources

Download or read book Python Strategy written by Tigran Petrosian and published by Quality Chess. This book was released on 2015-06-17 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tigran Petrosian is a titan of chess history. All agree he was a genius of strategy, defense and sacrifice, but didn t he take too many draws? Possibly so, but when Petrosian selected and annotated his best games, that flaw disappeared, leaving only brilliance and profound chess understanding. As Garry Kasparov said: "My games with the 9th World Champion broadened my understanding of chess. Had it not been for these two defeats, I would possibly not have reached the top in chess." This book is an English translation of a Russian classic that is a favorite of many grandmasters, including Mihail Marin and Levon Aronian. A literal translation of the Russian title might be 'The Strategy of Soundness' but Python Strategy is a better fit for Petrosian s more ambitious games. As another World Champion, Max Euwe, once wrote: "Petrosian is not a tiger that pounces on its prey, but rather a python that smothers its victim."

Download or read book Gamification Based E Learning Strategies for Computer Programming Education written by Alexandre Peixoto de Queirós, Ricardo and published by IGI Global. This book was released on 2016-08-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer technologies are forever evolving and it is vital that computer science educators find new methods of teaching programming in order to maintain the rapid changes occurring in the field. One of the ways to increase student engagement and retention is by integrating games into the curriculum. Gamification-Based E-Learning Strategies for Computer Programming Education evaluates the different approaches and issues faced in integrating games into computer education settings. Featuring emergent trends on the application of gaming to pedagogical strategies and technological tactics, as well as new methodologies and approaches being utilized in computer programming courses, this book is an essential reference source for practitioners, researchers, computer science teachers, and students pursuing computer science.

Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.

Download or read book Artificial Intelligence in Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2020-10-14 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

Download or read book Python for Algorithmic Trading written by J P Morgan and published by Independently Published. This book was released on 2024-08-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the Secrets of Python for Algorithmic Trading: A Step-by-Step Guide to Consistent Profits Discover the power of Python for Algorithmic Trading and elevate your trading game with "Python for Algorithmic Trading: Mastering Strategies for Consistent Profits." This comprehensive guide provides step-by-step instructions on creating and implementing advanced algorithmic trading strategies. Whether you're a Python programmer, web developer, trading enthusiast, student, or professional, this book is your ticket to navigating the complexities of the trading world and boosting your profitability. Key Features and Benefits: Step-by-Step Guidance: Create Advanced Strategies: Develop sophisticated strategies with clear, easy-to-follow instructions in this python for algorithmic trading book. Implement with Confidence: Learn to implement your strategies effectively, minimizing errors and maximizing efficiency using algorithmic trading python code. Enhance Trading Efficiency: Automate Your Trades: Leverage Python to automate trading processes, reducing manual intervention and increasing accuracy with algorithmic trading python libraries. Optimize Performance: Fine-tune your algorithms to enhance trading performance and ensure consistent results in your algorithmic trading python projects. Boost Your Profitability: Maximize Returns: Discover techniques to maximize your trading returns through data-driven strategies. Minimize Risks: Learn to identify and mitigate potential risks, ensuring more reliable and profitable trades. Navigate Complexities: Comprehensive Coverage: Gain a thorough understanding of the complexities involved in algorithmic trading with Python for algorithmic trading from idea to cloud deployment. Practical Insights: Benefit from practical insights and real-world examples that illustrate key concepts and techniques. Tailored for All Skill Levels: Beginner-Friendly: Start with the basics and gradually progress to more advanced topics, making it suitable for all skill levels. Expert Tips: Access tips and tricks from seasoned professionals to take your trading strategies to the next level, aligning with what you'd find in a Python for algorithmic trading course. Who Should Read This Book? Python Programmers: Enhance your programming skills with finance-specific applications using Python for finance and algorithmic trading. Web Developers: Integrate financial analytics and trading systems into your projects with ease. Trading Enthusiasts: Develop and implement data-driven trading strategies to improve your trading game. Students: Build a solid foundation in algorithmic trading, preparing you for a successful career in finance and technology. Technology Professionals: Stay ahead in your field by mastering the latest tools and techniques in algorithmic trading. Why Choose This Book? Expert Author: Learn from an experienced professional who has successfully implemented algorithmic trading strategies in real-world scenarios. Hands-On Learning: Engage with practical examples and projects that provide real-world applications of the concepts covered. Optimized for Success: Whether you're new to algorithmic trading or looking to refine your strategies, this book offers valuable insights and guidance to help you succeed. Order your copy today and unlock the potential of algorithmic trading with Python!

Download or read book Python for Algorithmic Trading written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2020-11-12 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

Download or read book Offensive Security Using Python written by Rejah Rehim and published by Packt Publishing Ltd. This book was released on 2024-09-30 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock Python's hacking potential and discover the art of exploiting vulnerabilities in the world of offensive cybersecurity Key Features Get in-depth knowledge of Python's role in offensive security, from fundamentals through to advanced techniques Discover the realm of cybersecurity with Python and exploit vulnerabilities effectively Automate complex security tasks with Python, using third-party tools and custom solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionOffensive Security Using Python is your go-to manual for mastering the quick-paced field of offensive security. This book is packed with valuable insights, real-world examples, and hands-on activities to help you leverage Python to navigate the complicated world of web security, exploit vulnerabilities, and automate challenging security tasks. From detecting vulnerabilities to exploiting them with cutting-edge Python techniques, you’ll gain practical insights into web security, along with guidance on how to use automation to improve the accuracy and effectiveness of your security activities. You’ll also learn how to design personalized security automation tools. While offensive security is a great way to stay ahead of emerging threats, defensive security plays an equal role in protecting organizations from cyberattacks. In this book, you’ll get to grips with Python secure coding techniques to improve your ability to recognize dangers quickly and take appropriate action. As you progress, you’ll be well on your way to handling the contemporary challenges in the field of cybersecurity using Python, as well as protecting your digital environment from growing attacks. By the end of this book, you’ll have a solid understanding of sophisticated offensive security methods and be able to stay ahead in the constantly evolving cybersecurity space.What you will learn Familiarize yourself with advanced Python techniques tailored to security professionals' needs Understand how to exploit web vulnerabilities using Python Enhance cloud infrastructure security by utilizing Python to fortify infrastructure as code (IaC) practices Build automated security pipelines using Python and third-party tools Develop custom security automation tools to streamline your workflow Implement secure coding practices with Python to boost your applications Discover Python-based threat detection and incident response techniques Who this book is for This book is for a diverse audience interested in cybersecurity and offensive security. Whether you're an experienced Python developer looking to enhance offensive security skills, an ethical hacker, a penetration tester eager to learn advanced Python techniques, or a cybersecurity enthusiast exploring Python's potential in vulnerability analysis, you'll find valuable insights. If you have a solid foundation in Python programming language and are eager to understand cybersecurity intricacies, this book will help you get started on the right foot.

Download or read book Python for MBAs written by Mattan Griffel and published by Columbia University Press. This book was released on 2021-05-04 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the ads that track us to the maps that guide us, the twenty-first century runs on code. The business world is no different. Programming has become one of the fastest-growing topics at business schools around the world. An increasing number of MBAs are choosing to pursue careers in tech. For them and other professionals, having some basic coding knowledge is a must. This book is an introduction to programming with Python for MBA students and others in business positions who need a crash course. One of the most popular programming languages, Python is used for tasks such as building and running websites, data analysis, machine learning, and natural-language processing. Drawing on years of experience providing instruction in this material at Columbia Business School as well as extensive backgrounds in technology, entrepreneurship, and consulting, Mattan Griffel and Daniel Guetta teach the basics of programming from scratch. Beginning with fundamentals such as variables, strings, lists, and functions, they build up to data analytics and practical ways to derive value from large and complex datasets. They focus on business use cases throughout, using the real-world example of a major restaurant chain to offer a concrete look at what Python can do. Written for business students with no previous coding experience and those in business roles that include coding or working with coding teams, Python for MBAs is an indispensable introduction to a versatile and powerful programming language.