“…The book, however, is not recommended for readers aiming to get an in-depth theoretical understanding of the mathematics behind NLP. …”

“…What's Inside Set up secure access policies Implement a Web Application Firewall Deploy MS Sentinel for monitoring and threat detection Establish compliance with business rules About the Reader For software and security engineers building and securing Azure applications. …”

“…What's Inside Writing and running concurrent programs Patterns for performance, scalability, and resilience Choosing the right hardware Asynchronous communication About the Reader Examples in Python. No prior experience with concurrency or high-performance computing required. …”

“…The book assumes familiarity with the C++ programming language, data structures, and algorithms. Additionally, readers should have a basic understanding of finance and trading concepts, such as market data, trading strategies, and risk management…”

“…Their collective knowledge and insights illuminate the multifaceted landscape of AI and ML in drug design and development, offering a roadmap for navigating its complexities and harnessing its potential. In each section, readers will find a rich tapestry of knowledge, case studies, and expert opinions, providing a 360-degree view of AI and ML's role in drug design and development. …”

“…What you will learn Gain a solid understanding of ChatGPT and its capabilities and limitations Understand how to use ChatGPT for conversation design Discover how to use advanced LangChain techniques, such as prompting, memory, agents, chains, vector stores, and tools Create a ChatGPT chatbot that can answer questions about your own data Develop a chatbot powered by ChatGPT API Explore the future of conversational AI, LLMs, and ChatGPT alternatives Who this book is for This book is for tech-savvy readers, conversational AI practitioners, engineers, product owners, business analysts, and entrepreneurs wanting to integrate ChatGPT into conversational experiences and explore the possibilities of this game-changing technology. …”

“…What's Inside Fundamental concepts and algorithms of NLP Extracting information from raw text Useful Python libraries Topic labeling Building a search algorithm About the Reader You'll need basic Python skills. No experience with NLP required. …”

“…What's Inside Caesar cipher solver: Use an I/O filter to generate customized output Duplicate file finder: Use recursion to explore a directory tree Daily greetings: Writing the moon phase algorithm Lotto pics: Working with random numbers And 11 more fun projects! About the Reader For C programmers of all skill levels. About the Author Dan Gookin has over 30 years of experience writing about complex topics. …”

“…Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. about the audience For readers comfortable with machine learning basics. about the author Alessandro Negro is Chief Scientist at GraphAware. …”

“…Realistic downloadable datasets help you learn from the kind of messy data you'll find in the real world. about the audience For readers experienced with spreadsheets and basic Python programming. about the author Boris Paskhaver is a software engineer, Agile consultant, and online educator. …”

“…What's Inside Identify and squash code-level bugs Avoid problems with application structure and design Perfect your data and control structures Optimize your code by eliminating inefficiencies About the Reader For developers proficient with Go programming and syntax. …”

“…What's Inside Structure PowerShell code for sharing and reusability Store and secure your automations Execute automation with Azure Automation, Jenkins, Task Scheduler, and Cron Store and retrieve data, credentials, and variables Use source control solutions to maintain and test code changes About the Reader For sysadmin and IT professionals who manage backend systems. …”

“…In the end, you'll be confident in your skills because you can see the results. about the audience For readers who know the basics of Python. No prior data science or machine learning skills required. about the author Leonard Apeltsin is the Head of Data Science at Anomaly, where his team applies advanced analytics to uncover healthcare fraud, waste, and abuse. …”

“…Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. about the audience For readers comfortable with machine learning basics. about the author Alessandro Negro is Chief Scientist at GraphAware. …”

“…What's Inside Kubernetes base components Storage and the Container Storage Interface Kubernetes security Different ways of creating a Kubernetes cluster Details about the control plane, networking, and other core components About the Reader For intermediate Kubernetes developers and administrators. …”

“…What's Inside How human descriptions are translated into computer programs How a digital computer thinks about print documents How a program decides where to print ink on a page How the history of typesetting shows up in modern books About the Reader For the curious-but-clueless about computer science--and anyone interested in how computers make books! …”

“…What's Inside First steps with serverless computing The principles of serverless design Important patterns and architectures Real-world architectures and their tradeoffs About the Reader For server-side and full-stack software developers. …”

“…What's Inside Set up secure access policies Implement a Web Application Firewall Deploy MS Sentinel for monitoring and threat detection Establish compliance with business rules About the Reader For software and security engineers building and securing Azure applications. …”

“…What's Inside Bagging, boosting, and gradient boosting Methods for classification, regression, and retrieval Interpretability and explainability for ensemble methods Feature engineering and ensemble diversity About the Reader For Python programmers with machine learning experience. …”

“…What's Inside Bagging, boosting, and gradient boosting Methods for classification, regression, and retrieval Interpretability and explainability for ensemble methods Feature engineering and ensemble diversity About the Reader For Python programmers with machine learning experience. …”