TradeStation EasyLanguage for Algorithmic Trading. Discover real-world institutional applications of Equities, Futures, and Forex markets

Domenico D'Errico

With AI revolutionizing financial markets, every trader will soon get easy access to AI models through free Python libraries and datasets, with all of them making the same trades! This behavior will modify prices and trading volumes, potentially altering future datasets, leading to major corporations investing heavily in technology, big data, and expert teams.However, individual traders need not be intimidated because this dynamic has been seen before whenever new technologies have entered the trading market. Written by a quantitative algorithmic trading developer with over 15 years of experience in the finance industry, this book will ground you by taking a rational approach to algorithmic trading, where EasyLanguage, datasets, charts, and AI are tools for your journey toward mastering the markets. Your unique human intelligence remains invaluable in navigating and understanding market complexities as you explore the realm of institutional insights, satisfying your hunger to learn real-world algorithmic trading applications from the institutional perspective.By the end of this book, you’ll be able to confidently apply TradeStation EasyLanguage to algorithmic trading, integrate machine learning to refine your strategies, and craft a personalized approach to confidently navigate the financial markets.

Hadoop Blueprints. Click here to enter text

Sudheesh Narayan, Anurag Shrivastava, Tanmay Deshpande

If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level.Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book.The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space.

Mastering Python for Finance. Implement advanced state-of-the-art financial statistical applications using Python - Second Edition

James Ma Weiming

The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples.You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and scikit-learn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance.By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis.

Python Data Analysis. Learn how to apply powerful data analysis techniques with popular open source Python modules

Ivan Idris

Python Natural Language Processing Cookbook. Over 60 recipes for building powerful NLP solutions using Python and LLM libraries - Second Edition

Zhenya Antić, Saurabh Chakravarty, Edward A. Fox

Harness the power of Natural Language Processing (NLP) to overcome real-world text analysis challenges with this recipe-based roadmap written by two seasoned NLP experts with vast experience transforming various industries with their NLP prowess.You’ll be able to make the most of the latest NLP advancements, including large language models (LLMs), and leverage their capabilities through Hugging Face transformers. Through a series of hands-on recipes, you’ll master essential techniques such as extracting entities and visualizing text data. The authors will expertly guide you through building pipelines for sentiment analysis, topic modeling, and question-answering using popular libraries like spaCy, Gensim, and NLTK. You’ll also learn to implement RAG pipelines to draw out precise answers from a text corpus using LLMs.This second edition expands your skillset with new chapters on cutting-edge LLMs like GPT-4, Natural Language Understanding (NLU), and Explainable AI (XAI)—fostering trust in your NLP models.By the end of this book, you'll be equipped with the skills to apply advanced text processing techniques, use pre-trained transformer models, build custom NLP pipelines to extract valuable insights from text data to drive informed decision-making.

OUYA Game Development by Example. An all-inclusive, fun guide to making professional 3D games for the OUYA console

John Donovan

The OUYA console and development kit gives you the power to publish video games for the players, creating a console marketplace of the gamers, for the gamers, and by the gamers. Using the OUYA developer kit and the Unity3D game engine, even beginners with a captivating game idea can bring it to life with a hint of imagination.OUYA Game Development by Example uses a series of feature-based, step-by-step tutorials that teach beginners how to integrate essential elements into a game engine and then combine them to form a polished gaming experience.

Raspberry Pi Blueprints. Design and build your own hardware projects that interact with the real world using the Raspberry Pi

Jack Creasy, Dan Nixon

Building and Delivering Microservices on AWS. Master software architecture patterns to develop and deliver microservices to AWS Cloud

Amar Deep Singh, Jeff Carpenter

Reliable automation is crucial for any code change going into production. A release pipeline enables you to deliver features for your users efficiently and promptly. AWS CodePipeline, with its powerful integration and automation capabilities of building, testing, and deployment, offers a unique solution to common software delivery issues such as outages during deployment, a lack of standard delivery mechanisms, and challenges faced in creating sustainable pipelines.You’ll begin by developing a Java microservice and using AWS services such as CodeCommit, CodeArtifact, and CodeGuru to manage and review the source code. You’ll then learn to use the AWS CodeBuild service to build code and deploy it to AWS infrastructure and container services using the CodeDeploy service. As you advance, you’ll find out how to provision cloud infrastructure using CloudFormation templates and Terraform. The concluding chapters will show you how to combine all these AWS services to create a reliable and automated CodePipeline for delivering microservices from source code check-in to deployment without any downtime. Finally, you’ll discover how to integrate AWS CodePipeline with third-party services such as Bitbucket, Blazemeter, Snyk, and Jenkins.By the end of this microservices book, you’ll have gained the hands-on skills to build release pipelines for your applications.