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Book Web App Development Made Simple with Streamlit

Download or read book Web App Development Made Simple with Streamlit written by Rosario Moscato and published by Packt Publishing Ltd. This book was released on 2024-02-09 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the full potential of Streamlit, mastering web app development from setup to deployment with practical guidance, advanced techniques, and real-world examples Key Features Identify and overcome web development challenges, crafting dedicated application skeletons using Streamlit Understand how Streamlit's widgets and components work to implement any kind of web app Manage web application development and deployment with ease using the Streamlit Cloud service Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis book is a comprehensive guide to the Streamlit open-source Python library and simplifying the process of creating web applications. Through hands-on guidance and realistic examples, you’ll progress from crafting simple to sophisticated web applications from scratch. This book covers everything from understanding Streamlit's central principles, modules, basic features, and widgets to advanced skills such as dealing with databases, hashes, sessions, and multipages. Starting with fundamental concepts like operation systems virtualization, IDEs, development environments, widgets, scripting, and the anatomy of web apps, the initial chapters set the groundwork. You’ll then apply this knowledge to develop some real web apps, gradually advancing to more complex apps, incorporating features like natural language processing (NLP), computer vision, dashboards with interactive charts, file uploading, and much more. The book concludes by delving into the implementation of advanced skills and deployment techniques. By the end of this book, you’ll have transformed into a proficient developer, equipped with advanced skills for handling databases, implementing secure login processes, managing session states, creating multipage applications, and seamlessly deploying them on the cloud.What you will learn Develop interactive web apps with Streamlit and deploy them seamlessly on the cloud Acquire in-depth theoretical and practical expertise in using Streamlit for app development Use themes and customization for visually appealing web apps tailored to specific needs Implement advanced features including secure login, signup processes, file uploaders, and database connections Build a catalog of scripts and routines to efficiently implement new web apps Attain autonomy in adopting new Streamlit features rapidly and effectively Who this book is for This book is for Python programmers, web developers, computer science students, and IT enthusiasts with a foundation in Python (or any programming language) who have a passion for creating visually appealing applications. If you already know how to write programs, this book will help you evolve into an adept web application developer skilled at converting command-line tools into impressive, cloud-hosted applications.

Book Web Application Development with Streamlit

Download or read book Web Application Development with Streamlit written by Mohammad Khorasani and published by Apress. This book was released on 2022-08-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transition from a back-end developer to a full-stack developer with knowledge of all the dimensions of web application development, namely, front-end, back-end and server-side software. This book provides a comprehensive overview of Streamlit, allowing developers and programmers of all backgrounds to get up to speed in as little time as possible. Streamlit is a pure Python web framework that will bridge the skills gap and shorten development time from weeks to hours. This book walks you through the complete cycle of web application development, from an introductory to advanced level with accompanying source code and resources. You will be exposed to developing basic, intermediate, and sophisticated user interfaces and subsequently you will be acquainted with data visualization, database systems, application security, and cloud deployment in Streamlit. In a market with a surplus demand for full stack developers, this skill set could not possibly come at a better time. In one sentence, Streamlit is a means for the empowerment of developers everywhere and all stand to gain from it. What You’ll Learn Mutate big data in real-time Visualize big data interactively Implement web application security and privacy protocols Deploy Streamlit web applications to the cloud using Streamlit, Linux and Windows servers Who is this Book for? Developers with solid programming experience wanting to learn Streamlit; Back-end developers looking to upskill and transition to become a full-stack developers; Those who wish to learn and become more acquainted with data visualization, database systems, security and cloud deployment with Steamlit

Book Getting Started with Streamlit for Data Science

Download or read book Getting Started with Streamlit for Data Science written by Tyler Richards and published by Packt Publishing Ltd. This book was released on 2021-08-20 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create, deploy, and test your Python applications, analyses, and models with ease using Streamlit Key Features Learn how to showcase machine learning models in a Streamlit application effectively and efficiently Become an expert Streamlit creator by getting hands-on with complex application creation Discover how Streamlit enables you to create and deploy apps effortlessly Book DescriptionStreamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.What you will learn Set up your first development environment and create a basic Streamlit app from scratch Explore methods for uploading, downloading, and manipulating data in Streamlit apps Create dynamic visualizations in Streamlit using built-in and imported Python libraries Discover strategies for creating and deploying machine learning models in Streamlit Use Streamlit sharing for one-click deployment Beautify Streamlit apps using themes, Streamlit Components, and Streamlit sidebar Implement best practices for prototyping your data science work with Streamlit Who this book is for This book is for data scientists and machine learning enthusiasts who want to create web apps using Streamlit. Whether you’re a junior data scientist looking to deploy your first machine learning project in Python to improve your resume or a senior data scientist who wants to use Streamlit to make convincing and dynamic data analyses, this book will help you get there! Prior knowledge of Python programming will assist with understanding the concepts covered.

Book Beginner s Guide to Streamlit with Python

Download or read book Beginner s Guide to Streamlit with Python written by Sujay Raghavendra and published by Apress. This book was released on 2022-12-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you’ll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You’ll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you’ll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit. After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own. What You Will Learn How to start developing web applications using Streamlit What are Streamlit's components Media elements in Streamlit How to visualize data using various interactive and dynamic Python libraries How to implement models in Streamlit web applications Who This Book Is ForProfessionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development.

Book Streamlit Essentials

    Book Details:
  • Author : Surabhi Pandey
  • Publisher : BPB Publications
  • Release : 2024-09-20
  • ISBN : 9365890829
  • Pages : 395 pages

Download or read book Streamlit Essentials written by Surabhi Pandey and published by BPB Publications. This book was released on 2024-09-20 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: DESCRIPTION Streamlit Essentials is a comprehensive guide aimed at helping you build interactive data applications using Python. With easy-to-use syntax, it allows developers to quickly build visualizations, dashboards, and machine learning models. This book is a practical guide to building data science applications using the Streamlit framework. It covers everything from installation to advanced topics like ML integration and deployment. With real-world projects and examples, you will learn how to use Streamlit's widgets, styling, and data visualization tools to create dynamic real-time dashboards, containerize your applications with Docker, securely handle sensitive data, and deploy the applications on leading cloud platforms, all while building practical projects that can be added to enhance your portfolio. Throughout the book, you will develop the skills needed to turn data insights into interactive visualizations, ensuring your projects are not only functional but also engaging. The focus is hands-on learning, with step-by-step guidance to help you build, optimize, and share your work. By the time you have completed this book, you will be able to confidently deploy applications, showcase your skills through a professional portfolio, and position yourself for success. KEY FEATURES ● Learn how to present data insights quickly and clearly using Streamlit for smoother collaboration between business and tech teams. ● Master Streamlit’s core and advanced features through hands-on projects like product recommenders. ● Build and deploy data applications while exploring over 25 project ideas to enhance your Streamlit skills. ● Explore the Gen AI toolkit to speed up your development cycle from ideation to deployment. WHAT YOU WILL LEARN ● Understanding of Streamlit's capabilities, from its core functionalities to advanced features. ● Create engaging and informative visualizations using Streamlit's extensive library of charts, graphs, and maps. ● Develop efficiently using time-saving techniques for rapid prototyping and iterative development. ● Optimize app performance with advanced topics like caching, session tracking, and theming. ● Create a compelling portfolio to demonstrate your Streamlit proficiency. WHO THIS BOOK IS FOR Whether you are a data scientist, analyst, developer, or business professional, this book will provide you with the knowledge and skills needed to build engaging and informative dashboards, visualizations, and ML models. TABLE OF CONTENTS 1. Introduction to Streamlit 2. Getting Started with Streamlit 3. Exploring Streamlit Widgets 4. Styling and Layouts in Streamlit 5. Data Visualization with Streamlit 6. Streamlit and Machine Learning 7. Advanced Streamlit Concepts 8. Deployment of Streamlit Apps 9. Hands-On Projects: Easy 10. Hands-On Projects: Intermediate 11. Hands-On Projects: Advanced 12. Build and Enhance Your Portfolio 13. Enhancing Streamlit Development with AI Tools Appendix A: Streamlit Cheat Sheet Appendix B: Additional Resources and References Appendix C: Docker 101: Beginner’s Guide to Containers

Book Streamlit for Data Science

Download or read book Streamlit for Data Science written by Tyler Richards and published by Packt Publishing Ltd. This book was released on 2023-09-29 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: An easy-to-follow and comprehensive guide to creating data apps with Streamlit, including how-to guides for working with cloud data warehouses like Snowflake, using pretrained Hugging Face and OpenAI models, and creating apps for job interviews. Key Features Create machine learning apps with random forest, Hugging Face, and GPT-3.5 turbo models Gain an insight into how experts harness Streamlit with in-depth interviews with Streamlit power users Discover the full range of Streamlit’s capabilities via hands-on exercises to effortlessly create and deploy well-designed apps Book DescriptionIf you work with data in Python and are looking to create data apps that showcase ML models and make beautiful interactive visualizations, then this is the ideal book for you. Streamlit for Data Science, Second Edition, shows you how to create and deploy data apps quickly, all within Python. This helps you create prototypes in hours instead of days! Written by a prolific Streamlit user and senior data scientist at Snowflake, this fully updated second edition builds on the practical nature of the previous edition with exciting updates, including connecting Streamlit to data warehouses like Snowflake, integrating Hugging Face and OpenAI models into your apps, and connecting and building apps on top of Streamlit databases. Plus, there is a totally updated code repository on GitHub to help you practice your newfound skills. You'll start your journey with the fundamentals of Streamlit and gradually build on this foundation by working with machine learning models and producing high-quality interactive apps. The practical examples of both personal data projects and work-related data-focused web applications will help you get to grips with more challenging topics such as Streamlit Components, beautifying your apps, and quick deployment. By the end of this book, you'll be able to create dynamic web apps in Streamlit quickly and effortlessly.What you will learn Set up your first development environment and create a basic Streamlit app from scratch Create dynamic visualizations using built-in and imported Python libraries Discover strategies for creating and deploying machine learning models in Streamlit Deploy Streamlit apps with Streamlit Community Cloud, Hugging Face Spaces, and Heroku Integrate Streamlit with Hugging Face, OpenAI, and Snowflake Beautify Streamlit apps using themes and components Implement best practices for prototyping your data science work with Streamlit Who this book is forThis book is for data scientists and machine learning enthusiasts who want to get started with creating data apps in Streamlit. It is terrific for junior data scientists looking to gain some valuable new skills in a specific and actionable fashion and is also a great resource for senior data scientists looking for a comprehensive overview of the library and how people use it. Prior knowledge of Python programming is a must, and you’ll get the most out of this book if you’ve used Python libraries like Pandas and NumPy in the past.

Book Streamlit   FOR EVERYTHING

Download or read book Streamlit FOR EVERYTHING written by Deivison Viana Andrade and published by Independently Published. This book was released on 2024-05-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Streamlit for Everything!" is your ultimate compass for navigating the universe of Streamlit, from the first steps to advanced techniques. This meticulously crafted guide is suitable for both beginners eager to enter the world of interactive web application development and experienced professionals looking to deepen their skills in data science and complex visualizations. Deivison Viana, with his rich and multifaceted experience, unfolds Streamlit in chapters that are true gems: learn to install and configure, create dynamic dashboards, integrate APIs, and even use websockets for real-time data analysis. Discover how Streamlit can be applied in Human Resources, optimizing evaluation and recruitment processes, and dive into financial applications, simulating markets and monitoring portfolios. Not only that, but marketing professionals will find strategies to leverage data and conduct A/B testing for more effective campaigns. Each chapter is reinforced with practical challenges, encouraging you to apply the knowledge and build an impressive portfolio. Whether you are a student, a data scientist, a web developer, or a manager, "Streamlit for Everything!" promises to elevate your skills and understanding of Streamlit to new heights.

Book Building Production Grade Web Applications with Supabase

Download or read book Building Production Grade Web Applications with Supabase written by David Lorenz and published by Packt Publishing Ltd. This book was released on 2024-08-09 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Craft resilient web applications with Supabase by leveraging advanced features such as authentication, data and user management, and seamless AI integration using its powerful Postgres infrastructure Key Features Learn how to integrate Supabase and Next.js to create powerful and scalable web apps Explore real-world scenarios with a multi-tenant ticket system Master real-time data handling, secure file storage, and application security enhancement, while discovering the full potential of the database beyond holding data Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDiscover the powerful capabilities of Supabase, the cutting-edge, open-source platform flipping the script on backend architecture. Guided by David Lorenz, a battle-tested software architect with over two decades of development experience, this book will transform the way you approach your projects and make you a Supabase expert. In this comprehensive guide, you'll build a secure, production-grade multi-tenant ticket system, seamlessly integrated with Next.js. You’ll build essential skills for effective data manipulation, authentication, and file storage, as well as master Supabase's advanced capabilities including automating tasks with cron scheduling, performing similarity searches with artificial intelligence, testing your database, and leveraging real-time updates. By the end of the book, you'll have a deeper understanding of the platform and be able to confidently utilize Supabase in your own web applications, all thanks to David's excellent expertise.What you will learn Explore essential features for effective web app development Handle user registration, login/logout processes, and user metadata Navigate multi-tenant applications and understand the potential pitfalls and best practices Discover how to implement real-time functionality Find out how to upload, download, and manipulate files Explore preventive measures against data manipulation and security breaches, ensuring robust web app security Increase efficiency and streamline task automation through personalized email communication, webhooks, and cron jobs Who this book is for This book is for developers looking for a hassle-free, universal solution to building robust apps using Supabase and its integration libraries. While a basic understanding of JavaScript is useful, it’s not essential as the book focuses on Supabase for creating high-performance web apps using Next.js. Experienced professionals from non-JavaScript backgrounds will find this book useful. Familiarity with Postgres, although helpful, is not mandatory as the book explains all the SQL statements used.

Book Cheminformatics  QSAR and Machine Learning Applications for Novel Drug Development

Download or read book Cheminformatics QSAR and Machine Learning Applications for Novel Drug Development written by Kunal Roy and published by Elsevier. This book was released on 2023-05-23 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book.The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates. - Presents chemometrics, cheminformatics and machine learning methods under a single reference - Showcases the different structure-based, ligand-based and machine learning tools currently used in drug design - Highlights special topics of computational drug design and available tools and databases

Book Computational Intelligence in Communications and Business Analytics

Download or read book Computational Intelligence in Communications and Business Analytics written by Kousik Dasgupta and published by Springer Nature. This book was released on 2023-11-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set constitutes the refereed proceedings of the 5th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2023, held in Kalyani, India, during January 27–28, 2023. The 52 full papers presented in this volume were carefully reviewed and selected from 187 submissions. The papers present recent research on intersection of computational intelligence, communications, and business analytics, fostering international collaboration and the dissemination of cutting-edge research.

Book Continuous Machine Learning with Kubeflow

Download or read book Continuous Machine Learning with Kubeflow written by Aniruddha Choudhury and published by BPB Publications. This book was released on 2021-11-20 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: An insightful journey to MLOps, DevOps, and Machine Learning in the real environment. KEY FEATURES ● Extensive knowledge and concept explanation of Kubernetes components with examples. ● An all-in-one knowledge guide to train and deploy ML pipelines using Docker and Kubernetes. ● Includes numerous MLOps projects with access to proven frameworks and the use of deep learning concepts. DESCRIPTION 'Continuous Machine Learning with Kubeflow' introduces you to the modern machine learning infrastructure, which includes Kubernetes and the Kubeflow architecture. This book will explain the fundamentals of deploying various AI/ML use cases with TensorFlow training and serving with Kubernetes and how Kubernetes can help with specific projects from start to finish. This book will help demonstrate how to use Kubeflow components, deploy them in GCP, and serve them in production using real-time data prediction. With Kubeflow KFserving, we'll look at serving techniques, build a computer vision-based user interface in streamlit, and then deploy it to the Google cloud platforms, Kubernetes and Heroku. Next, we also explore how to build Explainable AI for determining fairness and biasness with a What-if tool. Backed with various use-cases, we will learn how to put machine learning into production, including training and serving. After reading this book, you will be able to build your ML projects in the cloud using Kubeflow and the latest technology. In addition, you will gain a solid knowledge of DevOps and MLOps, which will open doors to various job roles in companies. WHAT YOU WILL LEARN ● Get comfortable with the architecture and the orchestration of Kubernetes. ● Learn to containerize and deploy from scratch using Docker and Google Cloud Platform. ● Practice how to develop the Kubeflow Orchestrator pipeline for a TensorFlow model. ● Create AWS SageMaker pipelines, right from training to deployment in production. ● Build the TensorFlow Extended (TFX) pipeline for an NLP application using Tensorboard and TFMA. WHO THIS BOOK IS FOR This book is for MLOps, DevOps, Machine Learning Engineers, and Data Scientists who want to continuously deploy machine learning pipelines and manage them at scale using Kubernetes. The readers should have a strong background in machine learning and some knowledge of Kubernetes is required. TABLE OF CONTENTS 1. Introduction to Kubeflow & Kubernetes Cloud Architecture 2. Developing Kubeflow Pipeline in GCP 3. Designing Computer Vision Model in Kubeflow 4. Building TFX Pipeline 5. ML Model Explainability & Interpretability 6. Building Weights & Biases Pipeline Development 7. Applied ML with AWS Sagemaker 8. Web App Development with Streamlit & Heroku

Book Programming Large Language Models with Azure Open AI

Download or read book Programming Large Language Models with Azure Open AI written by Francesco Esposito and published by Microsoft Press. This book was released on 2024-04-03 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use LLMs to build better business software applications Autonomously communicate with users and optimize business tasks with applications built to make the interaction between humans and computers smooth and natural. Artificial Intelligence expert Francesco Esposito illustrates several scenarios for which a LLM is effective: crafting sophisticated business solutions, shortening the gap between humans and software-equipped machines, and building powerful reasoning engines. Insight into prompting and conversational programming—with specific techniques for patterns and frameworks—unlock how natural language can also lead to a new, advanced approach to coding. Concrete end-to-end demonstrations (featuring Python and ASP.NET Core) showcase versatile patterns of interaction between existing processes, APIs, data, and human input. Artificial Intelligence expert Francesco Esposito helps you: Understand the history of large language models and conversational programming Apply prompting as a new way of coding Learn core prompting techniques and fundamental use-cases Engineer advanced prompts, including connecting LLMs to data and function calling to build reasoning engines Use natural language in code to define workflows and orchestrate existing APIs Master external LLM frameworks Evaluate responsible AI security, privacy, and accuracy concerns Explore the AI regulatory landscape Build and implement a personal assistant Apply a retrieval augmented generation (RAG) pattern to formulate responses based on a knowledge base Construct a conversational user interface For IT Professionals and Consultants For software professionals, architects, lead developers, programmers, and Machine Learning enthusiasts For anyone else interested in natural language processing or real-world applications of human-like language in software

Book Deep Learning for Genomics

    Book Details:
  • Author : Upendra Kumar Devisetty
  • Publisher : Packt Publishing Ltd
  • Release : 2022-11-11
  • ISBN : 1804613010
  • Pages : 270 pages

Download or read book Deep Learning for Genomics written by Upendra Kumar Devisetty and published by Packt Publishing Ltd. This book was released on 2022-11-11 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industries Key FeaturesApply deep learning algorithms to solve real-world problems in the field of genomicsExtract biological insights from deep learning models built from genomic datasetsTrain, tune, evaluate, deploy, and monitor deep learning models for enabling predictions in genomicsBook Description Deep learning has shown remarkable promise in the field of genomics; however, there is a lack of a skilled deep learning workforce in this discipline. This book will help researchers and data scientists to stand out from the rest of the crowd and solve real-world problems in genomics by developing the necessary skill set. Starting with an introduction to the essential concepts, this book highlights the power of deep learning in handling big data in genomics. First, you'll learn about conventional genomics analysis, then transition to state-of-the-art machine learning-based genomics applications, and finally dive into deep learning approaches for genomics. The book covers all of the important deep learning algorithms commonly used by the research community and goes into the details of what they are, how they work, and their practical applications in genomics. The book dedicates an entire section to operationalizing deep learning models, which will provide the necessary hands-on tutorials for researchers and any deep learning practitioners to build, tune, interpret, deploy, evaluate, and monitor deep learning models from genomics big data sets. By the end of this book, you'll have learned about the challenges, best practices, and pitfalls of deep learning for genomics. What you will learnDiscover the machine learning applications for genomicsExplore deep learning concepts and methodologies for genomics applicationsUnderstand supervised deep learning algorithms for genomics applicationsGet to grips with unsupervised deep learning with autoencodersImprove deep learning models using generative modelsOperationalize deep learning models from genomics datasetsVisualize and interpret deep learning modelsUnderstand deep learning challenges, pitfalls, and best practicesWho this book is for This deep learning book is for machine learning engineers, data scientists, and academicians practicing in the field of genomics. It assumes that readers have intermediate Python programming knowledge, basic knowledge of Python libraries such as NumPy and Pandas to manipulate and parse data, Matplotlib, and Seaborn for visualizing data, along with a base in genomics and genomic analysis concepts.

Book Web Service APIs and Libraries

Download or read book Web Service APIs and Libraries written by Jason Paul Michel and published by American Library Association. This book was released on 2013 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how to enhance an institution's presence on the Web with tools that integrate a variety of handy, popular programs. Application Programming Interfaces (APIs) are software tools that help different programs work together, and Michel shows readers how to integrate them into existing library websites as well as use them to launch new kinds of services. Offering step-by-step guidance, this book Uses real-world examples to show how APIs can be used to promote library materials and events, visualize data, educate patrons, and mobilize library services Demonstrates how to create and manage widgets for photo galleries, instant reporting on computer/printer availability, featured book titles and book reviews from library users, tracking usage data, and many other library functions Includes instructions for working with popular tools such as Flickr, YouTube, Vimeo, Twitter, Google Charts, OCLC, WordPress, Goodreads, LibraryThing, and the Hathi Trust Provides plentiful screenshots, snippets of HTML code, and easy-to-follow samples to ensure that even novices will feel comfortable integrating APIs into their marketing plans Focusing on widely adopted tools that all have immediate, useful applications, this practical book will help extend any library’s reach.

Book Deploy Machine Learning Models to Production

Download or read book Deploy Machine Learning Models to Production written by Pramod Singh and published by Apress. This book was released on 2020-12-15 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build and deploy machine learning and deep learning models in production with end-to-end examples. This book begins with a focus on the machine learning model deployment process and its related challenges. Next, it covers the process of building and deploying machine learning models using different web frameworks such as Flask and Streamlit. A chapter on Docker follows and covers how to package and containerize machine learning models. The book also illustrates how to build and train machine learning and deep learning models at scale using Kubernetes. The book is a good starting point for people who want to move to the next level of machine learning by taking pre-built models and deploying them into production. It also offers guidance to those who want to move beyond Jupyter notebooks to training models at scale on cloud environments. All the code presented in the book is available in the form of Python scripts for you to try the examples and extend them in interesting ways. What You Will Learn Build, train, and deploy machine learning models at scale using Kubernetes Containerize any kind of machine learning model and run it on any platform using Docker Deploy machine learning and deep learning models using Flask and Streamlit frameworks Who This Book Is For Data engineers, data scientists, analysts, and machine learning and deep learning engineers

Book Proceedings of 4th International Conference on Recent Trends in Machine Learning  IoT  Smart Cities and Applications

Download or read book Proceedings of 4th International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Generative AI with LangChain

Download or read book Generative AI with LangChain written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2023-12-22 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.