Streamlit For Data Science
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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.
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.
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
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.
To succeed in AI and data science, you must first master APIs. API skills are essential for AI and data science success. 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. Part 1 takes you step-by-step through coding projects to build APIs using Python and FastAPI and deploy them in the cloud. Part 2 teaches you to consume APIs in a data science project using industry-standard tools. And in Part 3, you'll use ChatGPT, the LangChain framework, and other tools to access your APIs with generative AI and large language models (LLMs). As you complete the chapters in the book, you'll be creating a professional online portfolio demonstrating your new skill with APIs, AI, and data science. You'll learn 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 Author Ryan Day is a data scientist in the financial services industry and an open source developer.
Interactive Dashboards And Data Apps With Plotly And Dash
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Author : Elias Dabbas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-05-21
Interactive Dashboards And Data Apps With Plotly And Dash written by Elias Dabbas 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 2021-05-21 with Computers categories.
Build web-based, mobile-friendly analytic apps and interactive dashboards with Python Key Features Develop data apps and dashboards without any knowledge of JavaScript Map different types of data such as integers, floats, and dates to bar charts, scatter plots, and more Create controls and visual elements with multiple inputs and outputs and add functionality to the app as per your requirements Book DescriptionPlotly's Dash framework is a life-saver for Python developers who want to develop complete data apps and interactive dashboards without JavaScript, but you'll need to have the right guide to make sure you’re getting the most of it. With the help of this book, you'll be able to explore the functionalities of Dash for visualizing data in different ways. Interactive Dashboards and Data Apps with Plotly and Dash will first give you an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it. Next, you’ll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them. By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.What you will learn Find out how to run a fully interactive and easy-to-use app Convert your charts to various formats including images and HTML files Use Plotly Express and the grammar of graphics for easily mapping data to various visual attributes Create different chart types, such as bar charts, scatter plots, histograms, maps, and more Expand your app by creating dynamic pages that generate content based on URLs Implement new callbacks to manage charts based on URLs and vice versa Who this book is for This Plotly Dash book is for data professionals and data analysts who want to gain a better understanding of their data with the help of different visualizations and dashboards – and without having to use JS. Basic knowledge of the Python programming language and HTML will help you to grasp the concepts covered in this book more effectively, but it’s not a prerequisite.
Libgdx Game Development By Example
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Author : James Cook
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-08-26
Libgdx Game Development By Example written by James Cook 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 2015-08-26 with Computers categories.
Learn how to create your very own game using the libGDX cross-platform framework About This Book Learn the core features of libGDX to develop your own exciting games Explore game development concepts through example projects Target games for major app stores quickly and easily with libGDX's cross-platform functionality Who This Book Is For This book is intended for those who wish to learn the concepts of game development using libGDX. An understanding of Java and other programming languages would definitely be helpful, although it is not a must. What You Will Learn Create and configure a libGDX project to get started with making games Get to grips with a simple game loop that will drive your games Manage game assets to reduce code duplication and speed up development Pack game assets together into single assets to increase your game's performance Display textures on the screen and manipulate them with play input Play various types of sounds that a game can generate Design and modify a game user interface with libGDX's built-in tools Develop a game that will run across various platforms In Detail LibGDX is a cross-platform game development framework in Java that makes game programming easier and fun to do. It currently supports Windows, Linux, Mac OS X, Android, and HTML5. With a vast feature set on offer, there isn't a game that can't be made using libGDX. It allows you to write your code once and deploy it to multiple platforms without modification. With cross-platform delivery at its heart, a game can be made to target the major markets quickly and cost effectively. This book starts with a simple game through which the game update cycle is explained, including loading textures onto your screen, moving them around, and responding to input. From there you'll move on to more advanced concepts such as creating a formal game structure with a menu screen, adding a game screen and loading screen, sprite sheets, and animations. You'll explore how to introduce a font to optimize text, and with the help of a game that you'll create, you'll familiarise yourself with the 2D tile map API to create worlds that scroll as the characters move. In the final sample game of the book, you'll implement a basic version of an Angry Birds clone, which will allow you to use the physic library box2D that libGDX provides access to. An overview of exporting games to different platforms is then provided. Finally, you will discover how to integrate third-party services into games and take a sneak peak at the Social Media API to get a basic understanding of how it fits into the libGDX ecosystem. Style and approach With this book you'll learn game development with libGDX through example game projects. You'll finish the book with a thorough understanding of libGDX game development, along with completed games that you'll have built yourself.
Beginning Game Programming With Pygame Zero
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Author : Stewart Watkiss
language : en
Publisher: Apress
Release Date : 2020-02-04
Beginning Game Programming With Pygame Zero written by Stewart Watkiss and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-04 with Computers categories.
Make fun games while learning to code. Focused on making games rather than teaching programming theory, in this book you're more likely to see code on how gravity affects a missiles trajectory instead of the most efficient way to search through data. Even then the code is kept simple as games should be about playability rather than complex physics. There are links to the official documentation when you need to lookup information that isn't included in the book. Start with a simple text based game to grasp the basics of programming in Python. Then moves on to creating simple graphical games in Pygame Zero. Not only will you learn object oriented programming to make it easier to make more complex games, you'll also work to create your own graphics and sounds. 3D graphics are a little complex. So we focus on 2D games, including spins on some classic boardgames and arcade games. All the games are designed to run on a Raspberry Pi. They will work on any Raspberry Pi, butwill also work on any other computer that supports Python 3 along with Pygame Zero. The games you make will be playable and hopefully fun to play. And by the end of the book, you can step beyond the provided source code to develop your own unique games and programs. What You'll Learn Code in Python Generate sounds and graphics for 2D games Grasp object oriented programming with Pygame Zero Who This Book Is ForBeginning game developers interested in working with low-cost and easy-to-learn solutions like Pygame Zero and the Raspberry Pi.
Applied Natural Language Processing In The Enterprise
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Author : Ankur A. Patel
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-12
Applied Natural Language Processing In The Enterprise written by Ankur A. Patel 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 2021-05-12 with Computers categories.
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
Practical Machine Learning For Data Analysis Using Python
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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2020-06-07
Practical Machine Learning For Data Analysis Using Python written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-07 with Computers categories.
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.
Implementing A Digital Asset Management System
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Author : Jens Jacobsen
language : en
Publisher: CRC Press
Release Date : 2012-08-21
Implementing A Digital Asset Management System written by Jens Jacobsen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-21 with Business & Economics categories.
Learn how the top CG film, computer game and web development companies have saved significant time and money on their projects by optimizing digital asset management systems and streamlining production processes. Also included is a product overview with 28 detailed descriptions of software solutions, including screenshots and prices, as well as a practical assessment of their suitability for different industries & project sizes.