Streamlit For Data Science Second Edition

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Streamlit For Data Science

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Author : Tyler Richards
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-09-29

Streamlit For Data Science written by Tyler Richards and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-29 with Computers categories.

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 for This 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.

Hands On Apis For Ai And Data Science

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Author : Ryan Day
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-04

Hands On Apis For Ai And Data Science written by Ryan Day and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-04 with Computers categories.

Are you ready to grow your skills in AI and data science? A great place to start is learning to build and use APIs in real-world data and AI projects. API skills have become essential for AI and data science success, because they are used in a variety of ways in these fields. With this practical book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit. As you complete the chapters in the book, you'll be creating portfolio projects that teach you how to: Design APIs that data scientists and AIs love Develop APIs using Python and FastAPI Deploy APIs using multiple cloud providers Create data science projects such as visualizations and models using APIs as a data source Access APIs using generative AI and LLMs

Getting Started With Streamlit For Data Science

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Author : Tyler Richards
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-08-20

Getting Started With Streamlit For Data Science written by Tyler Richards and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-20 with Computers categories.

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.

Web App Development Made Simple With Streamlit

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Author : Rosario Moscato
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-02-09

Web App Development Made Simple With Streamlit written by Rosario Moscato and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-09 with Computers categories.

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.

A Beginner S Guide To Streamlit For Data Science

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Author : Partha Mishra
language : en
Publisher: Partha Mishra
Release Date : 2023-09-04

A Beginner S Guide To Streamlit For Data Science written by Partha Mishra and has been published by Partha Mishra this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-04 with Computers categories.

This guide is for anyone interested in learning about Streamlit I believe in learning the subject hands-on, so all the topics discussed will be immediately followed by examples, which allow you to understand the expected output. I assume that you have a beginner-level knowledge of Python and have it installed in your system. I have designed the book so that each chapter corresponds to a specific concept so that even an absolute beginners can follow. By the end of the book, you will have a proper understanding of how to create dynamic applications which are frequently used in the data science industry and confidently use the new skill in your day-to-day coding activities. Topics Covered: Chapter 1: Introduction to Streamlit Chapter 2: Installing and Setting Up Streamlit Chapter 3: Coding our first application in Streamlit Chapter 4: Displaying Text in Streamlit Chapter 5: Displaying Data in Streamlit Chapter 6: Displaying Plots in Streamlit Chapter 7: Accepting User Inputs in Streamlit Applications Chapter 8: Displaying Media in Streamlit Chapter 9: Arranging the Layout in Streamlit Chapter 10: Displaying Status Animations in Streamlit

Snowflake The Definitive Guide

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Author : Joyce Kay Avila
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-08-11

Snowflake The Definitive Guide written by Joyce Kay Avila and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-11 with Computers categories.

Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. Whether you're an IT professional working in data warehousing or data science, a business analyst or technical manager, or an aspiring data professional wanting to get more hands-on experience with the Snowflake platform, this book is for you. You'll learn how Snowflake users can build modern integrated data applications and develop new revenue streams based on data. Using hands-on SQL examples, you'll also discover how the Snowflake Data Cloud helps you accelerate data science by avoiding replatforming or migrating data unnecessarily. You'll be able to: Efficiently capture, store, and process large amounts of data at an amazing speed Ingest and transform real-time data feeds in both structured and semistructured formats and deliver meaningful data insights within minutes Use Snowflake Time Travel and zero-copy cloning to produce a sensible data recovery strategy that balances system resilience with ongoing storage costs Securely share data and reduce or eliminate data integration costs by accessing ready-to-query datasets available in the Snowflake Marketplace

Deploy Machine Learning Models To Production

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Author : Pramod Singh
language : en
Publisher: Apress
Release Date : 2020-12-15

Deploy Machine Learning Models To Production written by Pramod Singh and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-15 with Computers categories.

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

Data Storytelling With Altair And Ai

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Author : Angelica Lo Duca
language : en
Publisher: Simon and Schuster
Release Date : 2024-09-24

Data Storytelling With Altair And Ai written by Angelica Lo Duca and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-24 with Computers categories.

Great data presentations tell a story. Learn how to organize, visualize, and present data using Python, generative AI, and the cutting-edge Altair data visualization toolkit. Take the fast track to amazing data presentations! Data Storytelling with Altair and AI introduces a stack of useful tools and tried-and-tested methodologies that will rapidly increase your productivity, streamline the visualization process, and leave your audience inspired. In Data Storytelling with Altair and AI you’ll discover: • Using Python Altair for data visualization • Using Generative AI tools for data storytelling • The main concepts of data storytelling • Building data stories with the DIKW pyramid approach • Transforming raw data into a data story Data Storytelling with Altair and AI teaches you how to turn raw data into effective, insightful data stories. You’ll learn exactly what goes into an effective data story, then combine your Python data skills with the Altair library and AI tools to rapidly create amazing visualizations. Your bosses and decision-makers will love your new presentations—and you’ll love how quick Generative AI makes the whole process! About the technology Every dataset tells a story. After you’ve cleaned, crunched, and organized the raw data, it’s your job to share its story in a way that connects with your audience. Python’s Altair data visualization library, combined with generative AI tools like Copilot and ChatGPT, provide an amazing toolbox for transforming numbers, code, text, and graphics into intuitive data presentations. About the book Data Storytelling with Altair and AI teaches you how to build enhanced data visualizations using these tools. The book uses hands-on examples to build powerful narratives that can inform, inspire, and motivate. It covers the Altair data visualization library, along with AI techniques like generating text with ChatGPT, creating images with DALL-E, and Python coding with Copilot. You’ll learn by practicing with each interesting data story, from tourist arrivals in Portugal to population growth in the USA to fake news, salmon aquaculture, and more. What's inside • The Data-Information-Knowledge-Wisdom (DIKW) pyramid • Publish data stories using Streamlit, Tableau, and Comet • Vega and Vega-Lite visualization grammar About the reader For data analysts and data scientists experienced with Python. No previous knowledge of Altair or Generative AI required. About the author Angelica Lo Duca is a researcher at the Institute of Informatics and Telematics of the National Research Council, Italy. The technical editor on this book was Ninoslav Cerkez. Table of Contents PART 1 1 Introducing data storytelling 2 Running your first data story in Altair and GitHub Copilot 3 Reviewing the basic concepts of Altair 4 Generative AI tools for data storytelling PART 2 5 Crafting a data story using the DIKW pyramid 6 From data to information: Extracting insights 7 From information to knowledge: Building textual context 8 From information to knowledge: Building the visual context 9 From knowledge to wisdom: Adding next steps PART 3 10 Common issues while using generative AI 11 Publishing the data story A Technical requirements B Python pandas DataFrameC Other chart types

Operating Systems And Infrastructure In Data Science

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Author : Josef Spillner
language : en
Publisher: vdf Hochschulverlag AG
Release Date : 2023-09-22

Operating Systems And Infrastructure In Data Science written by Josef Spillner and has been published by vdf Hochschulverlag AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-22 with categories.

Programming, DataOps, Data Concepts, Applications, Workflows, Tools, Middleware, Collaborative Platforms, Cloud Facilities Modern data scientists work with a number of tools and operating system facilities in addition to online platforms. Mastering these in combination to manage their data and to deploy software, models and data as ready-to-use online services as well as to perform data science and analysis tasks is in the focus of Operating Systems and Infrastructure in Data Science. Readers will come to understand the fundamental concepts of operating systems and to explore plenty of tools in hands-on tasks and thus gradually develop the skills necessary to compose them for programming in the large, an essential capability in their later career. The book guides students through semester studies, acts as reference knowledge base and aids in acquiring the necessary knowledge, skills and competences especially in self-study settings. A unique feature of the book is the associated access to Edushell, a live environment to practice operating systems and infrastructure tasks.

Hands On Data Analysis With Pandas

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Author : Stefanie Molin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-04-29

Hands On Data Analysis With Pandas written by Stefanie Molin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Computers categories.

Get to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasks Key Features Perform efficient data analysis and manipulation tasks using pandas 1.x Apply pandas to different real-world domains with the help of step-by-step examples Make the most of pandas as an effective data exploration tool Book DescriptionExtracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.What you will learn Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Solve common data representation and analysis problems using pandas Build Python scripts, modules, and packages for reusable analysis code Who this book is for This book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress. You’ll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher.