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Ultimate Python for Fintech Solutions

Author : Bhagvan Kommadi

Publisher : Orange Education Pvt Ltd

Page : 302 pages

File Size : 11,11 MB

Release : 2024-07-12

Category : Computers

ISBN : 8197256209

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Book Description

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



Ultimate Cardano Smart Contracts

Author : Lawrence Arthur Ley

Publisher : Orange Education Pvt Ltd

Page : 407 pages

File Size : 16,67 MB

Release : 2024-06-14

Category : Computers

ISBN : 8197396531

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Book Description

TAGLINE Build Decentralized Applications Today for a Better Tomorrow KEY FEATURES ● Build secure, scalable, and resilient Web3 Cardano Blockchain applications. ● Project-based learning connects blockchain concepts to project architecture and source code. ● Discover new employment opportunities, business models, and markets. DESCRIPTION Unlock the full potential of the Cardano blockchain for building decentralized Web 3.0 apps with Ultimate Cardano Smart Contracts. This book takes you on a journey from the basics of blockchain evolution, cryptography, and Cardano's unique consensus algorithm, to the intricacies of transactions and smart contracts. You'll dive deep into Plutus, Cardano's native smart contract language, and master essential tools like the Transaction Builder and Validators. Learn how to mint your own tokens and utilize the best development tools available. Through a real-world ticketing application project, you'll design, implement, test, and deploy a decentralized application, ensuring robust security and scalability. Troubleshoot common issues and explore the vibrant Cardano ecosystem, filled with resources and communities to support your ongoing development journey. By the end of this book, you'll have the skills and confidence to create sophisticated smart contracts and contribute to the innovative world of Cardano. WHAT WILL YOU LEARN ● Gain a comprehensive understanding of blockchain technology and Cardano's innovative approach. ● Develop and deploy a variety of smart contracts on the Cardano blockchain. ● Master the creation and interaction with both Fungible Tokens (FTs) and Non-Fungible Tokens (NFTs) for diverse use cases. ● Implement advanced testing methodologies to ensure the security and reliability of your smart contracts. ● Design and build scalable decentralized applications (dApps) using Cardano's Plutus language. ● Explore real-world case studies and best practices for successful smart contract development. ● Engage with the vibrant Cardano community and contribute confidently to the ecosystem. WHO IS THIS BOOK FOR? This book is tailored for software developers, architects, analysts, computer science students, and blockchain enthusiasts looking to expand their knowledge and skills. It’s ideal for entrepreneurs who want to learn about Cardano's capabilities to build decentralized applications and create new business opportunities. TABLE OF CONTENTS 1. Blockchain Evolution 2. Cryptography and Consensus Algorithms Overview 3. Transactions 4. Plutus 5. Transaction Builder 6. Validators 7. Minting 8. Tooling 9. Ticket Application Design 10. Ticket Application Implementation 11. Testing, Security, and Scaling 12. Troubleshooting 13. Cardano Ecosystem 14. Closing Remarks Bibliography Index



Data-Centric Machine Learning with Python

Author : Jonas Christensen

Publisher : Packt Publishing Ltd

Page : 378 pages

File Size : 40,71 MB

Release : 2024-02-29

Category : Computers

ISBN : 1804612413

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Book Description

Join the data-centric revolution and master the concepts, techniques, and algorithms shaping the future of AI and ML development, using Python Key Features Grasp the principles of data centricity and apply them to real-world scenarios Gain experience with quality data collection, labeling, and synthetic data creation using Python Develop essential skills for building reliable, responsible, and ethical machine learning solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn the rapidly advancing data-driven world where data quality is pivotal to the success of machine learning and artificial intelligence projects, this critically timed guide provides a rare, end-to-end overview of data-centric machine learning (DCML), along with hands-on applications of technical and non-technical approaches to generating deeper and more accurate datasets. This book will help you understand what data-centric ML/AI is and how it can help you to realize the potential of ‘small data’. Delving into the building blocks of data-centric ML/AI, you’ll explore the human aspects of data labeling, tackle ambiguity in labeling, and understand the role of synthetic data. From strategies to improve data collection to techniques for refining and augmenting datasets, you’ll learn everything you need to elevate your data-centric practices. Through applied examples and insights for overcoming challenges, you’ll get a roadmap for implementing data-centric ML/AI in diverse applications in Python. By the end of this book, you’ll have developed a profound understanding of data-centric ML/AI and the proficiency to seamlessly integrate common data-centric approaches in the model development lifecycle to unlock the full potential of your machine learning projects by prioritizing data quality and reliability.What you will learn Understand the impact of input data quality compared to model selection and tuning Recognize the crucial role of subject-matter experts in effective model development Implement data cleaning, labeling, and augmentation best practices Explore common synthetic data generation techniques and their applications Apply synthetic data generation techniques using common Python packages Detect and mitigate bias in a dataset using best-practice techniques Understand the importance of reliability, responsibility, and ethical considerations in ML/AI Who this book is for This book is for data science professionals and machine learning enthusiasts looking to understand the concept of data-centricity, its benefits over a model-centric approach, and the practical application of a best-practice data-centric approach in their work. This book is also for other data professionals and senior leaders who want to explore the tools and techniques to improve data quality and create opportunities for small data ML/AI in their organizations.



Python for Finance

Author : Yves J. Hilpisch

Publisher : "O'Reilly Media, Inc."

Page : 682 pages

File Size : 38,6 MB

Release : 2018-12-05

Category : Computers

ISBN : 1492024295

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Book Description

The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.



Robo-Advisor with Python

Author : Aki Ranin

Publisher : Packt Publishing Ltd

Page : 250 pages

File Size : 17,4 MB

Release : 2023-02-28

Category : Computers

ISBN : 1801819009

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Book Description

Build your own robo-advisor in Python to manage your investments and get up and running in no time Purchase of the print or Kindle book includes a free PDF eBook Key FeaturesExplore the use cases, workflow, and features that make up robo-advisorsLearn how to build core robo-advisor capabilities for goals, risk questions, portfolios, and projectionsDiscover how to operate the automated processes of a built and deployed robo-advisorBook Description Robo-advisors are becoming table stakes for the wealth management industry across all segments, from retail to high-net-worth investors. Robo-advisors enable you to manage your own portfolios and financial institutions to create automated platforms for effective digital wealth management. This book is your hands-on guide to understanding how Robo-advisors work, and how to build one efficiently. The chapters are designed in a way to help you get a comprehensive grasp of what Robo-advisors do and how they are structured with an end-to-end workflow. You'll begin by learning about the key decisions that influence the building of a Robo-advisor, along with considerations on building and licensing a platform. As you advance, you'll find out how to build all the core capabilities of a Robo-advisor using Python, including goals, risk questionnaires, portfolios, and projections. The book also shows you how to create orders, as well as open accounts and perform KYC verification for transacting. Finally, you'll be able to implement capabilities such as performance reporting and rebalancing for operating a Robo-advisor with ease. By the end of this book, you'll have gained a solid understanding of how Robo-advisors work and be well on your way to building one for yourself or your business. What you will learnExplore what Robo-advisors do and why they existCreate a workflow to design and build a Robo-advisor from the bottom upBuild and license Robo-advisors using different approachesOpen and fund accounts, complete KYC verification, and manage ordersBuild Robo-advisor features for goals, projections, portfolios, and moreOperate a Robo-advisor with P&L, rebalancing, and fee managementWho this book is for If you are a finance professional or a data professional working in wealth management and are curious about how robo-advisors work, this book is for you. It will be helpful to have a basic understanding of Python and investing concepts. This is a great handbook for developers interested in building their own robo-advisor to manage personal investments or build a platform for their business to operate, as well as for product managers and business leaders in financial services looking to lease, buy, or build a robo-advisor.



Hands-On Data Science and Python Machine Learning

Author : Frank Kane

Publisher : Packt Publishing Ltd

Page : 415 pages

File Size : 14,72 MB

Release : 2017-07-31

Category : Computers

ISBN : 1787280225

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Book Description

This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.



Data Structures Through C in Depth

Author : Suresh Kumar Srivastava

Publisher :

Page : 0 pages

File Size : 42,77 MB

Release : 2004-05

Category : C (Computer program language)

ISBN : 9788176567411

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Book Description

This book is written in very simple manner and is very easy to understand. It describes the theory with examples step by step. It contains the description of writing these steps in programs in very easy and understandable manner. The book gives full understanding of each therotical topic and easy implementaion in programming. This book will help the students in Self-Learning of Data structures and in understanding how these concepts are implemented in programs. This book is useful for any level of students. It covers the syllabus of B.E. ,B.Tech, DOEACC Society, IGNOU.



Python for Finance

Author : Yuxing Yan

Publisher : Packt Publishing Ltd

Page : 586 pages

File Size : 39,59 MB

Release : 2017-06-30

Category : Computers

ISBN : 1787125025

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Book Description

Learn and implement various Quantitative Finance concepts using the popular Python libraries About This Book Understand the fundamentals of Python data structures and work with time-series data Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance Who This Book Is For This book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data. What You Will Learn Become acquainted with Python in the first two chapters Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models Learn how to price a call, put, and several exotic options Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options Understand the concept of volatility and how to test the hypothesis that volatility changes over the years Understand the ARCH and GARCH processes and how to write related Python programs In Detail This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM's market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option. Style and approach This book takes a step-by-step approach in explaining the libraries and modules in Python, and how they can be used to implement various aspects of quantitative finance. Each concept is explained in depth and supplemented with code examples for better understanding.



Rational Decisions in Organisations

Author : Frédéric Adam

Publisher : CRC Press

Page : 245 pages

File Size : 20,31 MB

Release : 2022-05-30

Category : Business & Economics

ISBN : 1000543102

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Book Description

Managers in organisations must make rational decisions. Rational decision making is the opposite of intuitive decision making. It is a strict procedure utilising objective knowledge and logic. It involves identifying the problem to solve, gathering facts, identifying options and outcomes, analysing them, considering all the relationships and selecting the decision. Rational decision making requires support: methods and software tools. The identification of the problem to solve needs methods that would measure and evaluate the current situation. Identification and evaluation of options and analysis of the available possibilities involves analysis and optimisation methods. Incorporating intuition into rational decision making needs adequate methods that would translate ideas or observed behaviours into hard data. Communication, observation and opinions recording is hardly possible today without adequate software. Information and data that form the input, intermediate variables and the output must be stored, managed and made accessible in a user-friendly manner. Rational Decisions in Organisations: Theoretical and Practical Aspects presents selected recent developments in the support of the widely understood rational decision making in organisations, illustrated through case studies. The book shows not only the variety of perspectives involved in decision making, but also the variety of domains where rational decision support systems are needed. The case studies present decision making by medical doctors, students and managers of various universities, IT project teams, construction companies, banks and small and large manufacturing companies. Covering the richness of relationships in which the decisions should and must be taken, the book illustrates how modern organisations operate in chains and networks; they have multiple responsibilities, including social, legal, business and ethical duties. Nowadays, managers in organisations can make transparent decisions and consider a multitude of stakeholders and their diverse features, incorporating diverse criteria, using multiple types and drivers of information and decision-making patterns, and referring to numerous lessons learned. As the book makes clear, the marriage of theoretical ideas with the possibilities offered by technology can make the decisions in organisations more rational and, at the same time, more human.



The Future of Finance

Author : Henri Arslanian

Publisher : Springer

Page : 318 pages

File Size : 38,3 MB

Release : 2019-07-15

Category : Business & Economics

ISBN : 3030145336

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Book Description

This book, written jointly by an engineer and artificial intelligence expert along with a lawyer and banker, is a glimpse on what the future of the financial services will look like and the impact it will have on society. The first half of the book provides a detailed yet easy to understand educational and technical overview of FinTech, artificial intelligence and cryptocurrencies including the existing industry pain points and the new technological enablers. The second half provides a practical, concise and engaging overview of their latest trends and their impact on the future of the financial services industry including numerous use cases and practical examples. The book is a must read for any professional currently working in finance, any student studying the topic or anyone curious on how the future of finance will look like.