Getting Started With Streamlit For Data Science

Author : Tyler Richards
Publisher : Packt Publishing Ltd
Page : 282 pages
File Size : 42,8 Mb
Release : 2021-08-20
Category : Computers
ISBN : 9781800563209

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Getting Started with Streamlit for Data Science by Tyler Richards Pdf

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.

Author : Tyler Richards
Publisher : Packt Publishing Ltd
Page : 301 pages
File Size : 44,8 Mb
Release : 2023-09-29
Category : Computers
ISBN : 9781803232959

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Streamlit for Data Science by Tyler Richards Pdf

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.

Author : Ayodele Odubela
Publisher : fullyConnected Inc.
Page : 117 pages
File Size : 49,9 Mb
Release : 2020-12-01
Category : Technology & Engineering
ISBN : 9780578806044

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Getting Started in Data Science by Ayodele Odubela Pdf

Data Science is one of the "sexiest jobs of the 21st Century", but few resources are geared towards learners with no prior experience. Getting Started in Data Science simplifies the core of the concepts of Data Science and Machine Learning. This book includes perspectives of a Data Science from someone with a non-traditional route to a Data Science career. Getting Started in Data Science creatively weaves in ethical questions and asks readers to question the harm models can cause as they learn new concepts. Unlike many other books for beginners, this book covers bias and accountability in detail as well as career insight that informs readers of what expectations are in industry Data Science.

Author : Murtaza Haider
Publisher : IBM Press
Page : 941 pages
File Size : 41,7 Mb
Release : 2015-12-14
Category : Business & Economics
ISBN : 9780133991239

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Getting Started with Data Science by Murtaza Haider Pdf

Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

Author : Svetlana Karslioglu
Publisher : Packt Publishing Ltd
Page : 365 pages
File Size : 48,6 Mb
Release : 2022-03-18
Category : Computers
ISBN : 9781801079075

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Reproducible Data Science with Pachyderm by Svetlana Karslioglu Pdf

Create scalable and reliable data pipelines easily with Pachyderm Key FeaturesLearn how to build an enterprise-level reproducible data science platform with PachydermDeploy Pachyderm on cloud platforms such as AWS EKS, Google Kubernetes Engine, and Microsoft Azure Kubernetes ServiceIntegrate Pachyderm with other data science tools, such as Pachyderm NotebooksBook Description Pachyderm is an open source project that enables data scientists to run reproducible data pipelines and scale them to an enterprise level. This book will teach you how to implement Pachyderm to create collaborative data science workflows and reproduce your ML experiments at scale. You'll begin your journey by exploring the importance of data reproducibility and comparing different data science platforms. Next, you'll explore how Pachyderm fits into the picture and its significance, followed by learning how to install Pachyderm locally on your computer or a cloud platform of your choice. You'll then discover the architectural components and Pachyderm's main pipeline principles and concepts. The book demonstrates how to use Pachyderm components to create your first data pipeline and advances to cover common operations involving data, such as uploading data to and from Pachyderm to create more complex pipelines. Based on what you've learned, you'll develop an end-to-end ML workflow, before trying out the hyperparameter tuning technique and the different supported Pachyderm language clients. Finally, you'll learn how to use a SaaS version of Pachyderm with Pachyderm Notebooks. By the end of this book, you will learn all aspects of running your data pipelines in Pachyderm and manage them on a day-to-day basis. What you will learnUnderstand the importance of reproducible data science for enterpriseExplore the basics of Pachyderm, such as commits and branchesUpload data to and from PachydermImplement common pipeline operations in PachydermCreate a real-life example of hyperparameter tuning in PachydermCombine Pachyderm with Pachyderm language clients in Python and GoWho this book is for This book is for new as well as experienced data scientists and machine learning engineers who want to build scalable infrastructures for their data science projects. Basic knowledge of Python programming and Kubernetes will be beneficial. Familiarity with Golang will be helpful.

Author : John Paul Mueller,Luca Massaron
Publisher : John Wiley & Sons
Page : 471 pages
File Size : 48,6 Mb
Release : 2023-11-07
Category : Computers
ISBN : 9781394213146

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Python for Data Science For Dummies by John Paul Mueller,Luca Massaron Pdf

Let Python do the heavy lifting for you as you analyze large datasets Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner’s guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples. Get a firm background in the basics of Python coding for data analysis Learn about data science careers you can pursue with Python coding skills Integrate data analysis with multimedia and graphics Manage and organize data with cloud-based relational databases Python careers are on the rise. Grab this user-friendly Dummies guide and gain the programming skills you need to become a data pro.

Author : Prateek Gupta
Publisher : BPB Publications
Page : 437 pages
File Size : 41,7 Mb
Release : 2021-03-01
Category : Computers
ISBN : 9789389898064

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Practical Data Science with Jupyter by Prateek Gupta Pdf

Solve business problems with data-driven techniques and easy-to-follow Python examples Ê KEY FEATURESÊÊ _ Essential coverage on statistics and data science techniques. _ Exposure to Jupyter, PyCharm, and use of GitHub. _ Real use-cases, best practices, and smart techniques on the use of data science for data applications. DESCRIPTIONÊÊ This book begins with an introduction to Data Science followed by the Python concepts. The readers will understand how to interact with various database and Statistics concepts with their Python implementations. You will learn how to import various types of data in Python, which is the first step of the data analysis process. Once you become comfortable with data importing, you willÊ clean the dataset and after that will gain an understanding about various visualization charts. This book focuses on how to apply feature engineering techniques to make your data more valuable to an algorithm. The readers will get to know various Machine Learning Algorithms, concepts, Time Series data, and a few real-world case studies. This book also presents some best practices that will help you to be industry-ready. This book focuses on how to practice data science techniques while learning their concepts using Python and Jupyter. This book is a complete answer to the most common question that how can you get started with Data Science instead of explaining Mathematics and Statistics behind the Machine Learning Algorithms. WHAT YOU WILL LEARN _ Rapid understanding of Python concepts for data science applications. _ Understand and practice how to run data analysis with data science techniques and algorithms. _ Learn feature engineering, dealing with different datasets, and most trending machine learning algorithms. _ Become self-sufficient to perform data science tasks with the best tools and techniques. Ê WHO THIS BOOK IS FORÊÊ This book is for a beginner or an experienced professional who is thinking about a career or a career switch to Data Science. Each chapter contains easy-to-follow Python examples. Ê TABLE OF CONTENTS 1. Data Science Fundamentals 2. Installing Software and System Setup 3. Lists and Dictionaries 4. Package, Function, and Loop 5. NumPy Foundation 6. Pandas and DataFrame 7. Interacting with Databases 8. Thinking Statistically in Data Science 9. How to Import Data in Python? 10. Cleaning of Imported Data 11. Data Visualization 12. Data Pre-processing 13. Supervised Machine Learning 14. Unsupervised Machine Learning 15. Handling Time-Series Data 16. Time-Series Methods 17. Case Study-1 18. Case Study-2 19. Case Study-3 20. Case Study-4 21. Python Virtual Environment 22. Introduction to An Advanced Algorithm - CatBoost 23. Revision of All ChaptersÕ Learning

Author : Murtaza Haider
Publisher : Unknown
Page : 128 pages
File Size : 54,9 Mb
Release : 2016
Category : Business enterprises
ISBN : 0133991245

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Getting Started with Data Science by Murtaza Haider Pdf

Author : William Gray
Publisher : Unknown
Page : 162 pages
File Size : 48,9 Mb
Release : 2019-08-20
Category : Electronic
ISBN : 1687276099

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Data Science from Scratch by William Gray Pdf

You Are About To Build Your Knowledge Of Data Science To Perhaps Build A Career Out Of It Even If You Are A Complete Beginner! The most valuable resource is no longer oil and gold; data reigns supreme these days! And if data is the most valuable resource, perhaps the field of data science is the most critical of them all! It is so lucrative that the median entry level starting salary of a data scientist is $98,000! If you think I'm making this up, just think of the Cambridge Analytica story of how it was used in the 2016 Presidential elections in the US to influence people's voting decisions! I'm not being political here; whether true or not, data was used and it, to some extent, was seen to be effective in influencing people! All that is the realm of data science! And it is not just Cambridge Analytica that uses data on a massive scale. Data is used to tell which ad suggestions show up when you are browsing on your favorite website, the kind of videos you see on YouTube for instance, the friend suggestions we see on Facebook, the stuff you see on your newsfeed, the emails that land in your spam folder, our credit rating, how much we pay for insurance, the products/movies that Amazon, Netflix and other online stores display to you and much more! For all these things to be possible, lots of data (an estimated 2.5 exabytes were being generated every single day in 2012, according to IBM) has to be collected, analyzed, interpreted and manipulated to serve a given purpose! Does all this sound like music to your ears? Would you want to understand the inner workings of key concepts of data science, including high performance computing, big data analysis, data infrastructure issues, machine learning, data mining, deep learning and more? This book has a comprehensive introduction to the field of data science to help you to have an above average understanding of data science to get you started. In it, you will learn: What data science is all about, including how it works, how it is used in everyday life and more The fundamentals of computer science and the place of data science in today's highly interconnected society Fundamentals of machine learning, including the intricacies of machine learning in data science and its application in everyday life Natural language processing, automation and artificial intelligence with respect to big data and data science The role of python programming language in modern day data science Data modeling, including the place of data modelers in data science Voice recognition as an important area of data science The concept of distributed systems and big data and their place in data science The concept of data visualization as part of data science The impact of smart technology on data entry processes And much more! The book uses beginner friendly, easy to follow, language that will ultimately help you to start seeing how to apply machine learning and big data analysis in solving everyday problems in the world! If you've ever wanted to dip your feet into the murky and interestingly mysterious world of data science, now is the time to get in! What are you waiting for? Click Buy Now In 1-Click or Buy Now at the top of this page to get started!

Author : Steven Cooper
Publisher : Roland Bind
Page : 156 pages
File Size : 50,8 Mb
Release : 2018-08-10
Category : Computers
ISBN : PKEY:6610000095711

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Data Science from Scratch by Steven Cooper Pdf

★☆If you are looking to start a new career that is in high demand, then you need to continue reading!★☆​​​​​​​ Data scientists are changing the way big data is used in different institutions. Big data is everywhere, but without the right person to interpret it, it means nothing. So where do business find these people to help change their business? You could be that person! It has become a universal truth that businesses are full of data. With the use of big data, the US healthcare could reduce their health-care spending by $300 billion to $450 billion. It can easily be seen that the value of big data lies in the analysis and processing of that data, and that's where data science comes in. ★★ Grab your copy today and learn ★★ ♦ In depth information about what data science is and why it is important. ♦ The prerequisites you will need to get started in data science. ♦ What it means to be a data scientist. ♦ The roles that hacking and coding play in data science. ♦ The different coding languages that can be used in data science. ♦ Why python is so important. ♦ How to use linear algebra and statistics. ♦ The different applications for data science. ♦ How to work with the data through munging and cleaning ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. As businesses and the internet change, so will data science. This means it's important to be flexible. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started in a new, ever growing, career, don't wait any longer. Scroll up and click the buy now button to get this book today!

Author : Joel Grus
Publisher : "O'Reilly Media, Inc."
Page : 330 pages
File Size : 42,7 Mb
Release : 2015-04-14
Category : Computers
ISBN : 9781491904404

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Data Science from Scratch by Joel Grus Pdf

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

Author : Daniel O'Reilly
Publisher : Unknown
Page : 112 pages
File Size : 53,6 Mb
Release : 2020-11-23
Category : Electronic
ISBN : 9798570409385

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Python for Data Science by Daniel O'Reilly Pdf

Here's the Perfect Solution if You Want to Become the Master of Data Science and Learn Phyton Step-by-Step Would you like to: Learn a super competitive skill? Become irreplaceable in the future job market? Upgrade yourself to the ultimate data whizz? If so, then keep reading! Data science is one of the emerging technologies that is set to radically transform the job market. With applications in almost every industry, data science experts will have no shortage of great job offers. But, the whole field may seem a little intimidating if your background is not specific to data science. This book is here to guide you through the field of data science from the very beginning. You will learn the fundamental skills and tools to support your learning process. If you're a beginner, this is the book to help you easily understand the basics of data science. To understand data science, you also need a good understanding of how Python helps you design and implement these projects. This guidebook is going to explain how we can get all of this done. Here just a little preview of what you'll find inside this book: A thorough and simple explanation of data science and the way it works Basics of data science and fundamental skills you need to get started Data science libraries you need to learn to become a data whizz A blueprint for the most used frameworks for Python data science How to process and understand the data and design your own projects AND SO MUCH MORE! Even if you're an absolute beginner with little programming experience, you will find this book easy to follow and implement. This guide is your first step towards a successful data science career, so don't hesitate! Scroll Up, Click the "Buy Now with 1-Click", and Get Your Copy!

Author : Stephen Klosterman
Publisher : Packt Publishing Ltd
Page : 433 pages
File Size : 48,8 Mb
Release : 2021-07-29
Category : Computers
ISBN : 9781800569447

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Data Science Projects with Python by Stephen Klosterman Pdf

Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoost Key FeaturesThink critically about data and use it to form and test a hypothesisChoose an appropriate machine learning model and train it on your dataCommunicate data-driven insights with confidence and clarityBook Description If data is the new oil, then machine learning is the drill. As companies gain access to ever-increasing quantities of raw data, the ability to deliver state-of-the-art predictive models that support business decision-making becomes more and more valuable. In this book, you'll work on an end-to-end project based around a realistic data set and split up into bite-sized practical exercises. This creates a case-study approach that simulates the working conditions you'll experience in real-world data science projects. You'll learn how to use key Python packages, including pandas, Matplotlib, and scikit-learn, and master the process of data exploration and data processing, before moving on to fitting, evaluating, and tuning algorithms such as regularized logistic regression and random forest. Now in its second edition, this book will take you through the end-to-end process of exploring data and delivering machine learning models. Updated for 2021, this edition includes brand new content on XGBoost, SHAP values, algorithmic fairness, and the ethical concerns of deploying a model in the real world. By the end of this data science book, you'll have the skills, understanding, and confidence to build your own machine learning models and gain insights from real data. What you will learnLoad, explore, and process data using the pandas Python packageUse Matplotlib to create compelling data visualizationsImplement predictive machine learning models with scikit-learnUse lasso and ridge regression to reduce model overfittingEvaluate random forest and logistic regression model performanceDeliver business insights by presenting clear, convincing conclusionsWho this book is for Data Science Projects with Python – Second Edition is for anyone who wants to get started with data science and machine learning. If you're keen to advance your career by using data analysis and predictive modeling to generate business insights, then this book is the perfect place to begin. To quickly grasp the concepts covered, it is recommended that you have basic experience of programming with Python or another similar language, and a general interest in statistics.

Author : Christoph Molnar
Publisher : Lulu.com
Page : 320 pages
File Size : 41,8 Mb
Release : 2020
Category : Artificial intelligence
ISBN : 9780244768522

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Interpretable Machine Learning by Christoph Molnar Pdf

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Author : Craig Berg
Publisher : Unknown
Page : 138 pages
File Size : 50,8 Mb
Release : 2020-06-17
Category : Electronic
ISBN : 9798654741257

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Data Science with Python by Craig Berg Pdf

You Are About To Venture Into The World Of Data Science With Confidence By Learning The Ins And Outs Of Data Science With Python! Are you a practicing or aspiring data scientist who's been wondering; What's the best language for a data scientist's rigorous work? Is there one that is also easy to understand and learn, and easy to use for the less technically-inclined person? ...and one that also builds better analytics tools? If you've been having those questions, you've clearly been looking for Python. Individual data scientists and data science consulting companies are increasingly adopting Python as a programming language of choice, as they realize its amazing features like large sets of libraries and unique capabilities in handling big data. The fact that it' also a language that you can easily integrate with other programming languages, and it's easily scalable and future-oriented makes it particularly valuable and practical for data science. As a new data scientist, you'd find it easy to use it because of its simple syntax, excellent readability and its increased availability of mining tools that make it easy to handle data. But how would you get started with it? How do you work with it? How do you set it up? If you still have such questions, then this book is all you need. It gives you the ins and outs of python as a data science solution, including how you can set it up, use it and what you need to get started. Here's a bit of what you can expect to learn from it: What data science is and why we need to learn and apply it in daily life The different types of data scientists we have The requirement and tools for data science The difference between data science and business intelligence The lifecycle of data science The components of data science How data science is being used today How to set up the Python environment in Linux, Mac and Windows How the Anaconda environment looks and works Basic Python concepts to refresh your mind How to work with Python for data analysis How to work out data visualization with Matplotlib and Seaborn ...And much more! Are you ready to enjoy data science more by achieving better insight, understanding patterns and correlating data from big datasets? Do you want to be able to develop machine learning models, web services, data mining, classification and so much more, while solving problems end to end effortlessly and within an incredibly short duration? If you do, then this simple, straightforward and comprehensive beginners' book will help you get there in just a few hours! Even if the concept of data science seems too complex and out there right now, this book will break the topic using simple, straightforward language that you can start using right away to your advantage! Scroll up and click Buy Now With 1-Click or Buy Now to get started!