No Code Data Science
DOWNLOAD
Download No Code Data Science PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get No Code Data Science book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
No Code Data Science
DOWNLOAD
Author : David Patrishkoff
language : en
Publisher:
Release Date : 2023-10-16
No Code Data Science written by David Patrishkoff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-16 with Computers categories.
No-Code Data Science is a revolutionary book that democratizes the application of predictive analytics for organizations of all sizes. This first-of-its-kind textbook book is designed to empower readers with the ability to leverage advanced analytics, machine learning, and AI without using a programming language, such as Python or R.It's a comprehensive guide to no-code data science (NCDS) that applies free, no-code, and open-source software with Orange visual programming software, JASP, and BlueSky Statistics. A no-shortcuts approach to ML and AI is applied to maximize the accuracy and application potential of predictive models. The NCDS approach is akin to constructing predictive models with pre-made LEGO bricks (visual programming) versus tediously molding shapes from clay (manual coding). A practical how-to approach to predictive modeling is offered while insisting on the rigor of our disciplined NCDS process. Hands-on data exercises are included in the first eleven chapters. QR code links to educational videos are included in most chapters.Data science background is first explored, discussing basic definitions and data scientist skill sets. This is followed by chapters on data preparation, wrangling, and data visualization. Predictive analytics is covered in chapters on machine learning models and model evaluation. Both supervised and unsupervised learning are included in the discourse. Time series forecasting, survival analysis, and geolocation are covered in separate chapters. Artificial intelligence is featured in chapters on image analysis and text mining. Lastly, the potential impact of machine learning and artificial intelligence on Industry 4.0 is covered in the last chapter. We also offer a pathway for statisticians, Lean Six Sigma practitioners, and other professionals to learn predictive modeling techniques to enable organizations to successfully pursue Industry 4.0 goals.
No Code Data Science
DOWNLOAD
Author : David Patrishkoff
language : en
Publisher:
Release Date : 2023-10-16
No Code Data Science written by David Patrishkoff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-16 with Computers categories.
No Code Data Science is a revolutionary book that democratizes the application of predictive analytics for organizations of all sizes. This first-of-its-kind textbook book is designed to empower readers with the ability to leverage advanced analytics, machine learning, and AI without using a programming language, such as Python or R.It's a comprehensive guide to no-code data science (NCDS) that applies free, no-code, and open-source software with Orange visual programming software, JASP, and BlueSky Statistics. A no-shortcuts approach to ML and AI is applied to maximize the accuracy and application potential of predictive models. The NCDS approach is akin to constructing predictive models with pre-made LEGO bricks (visual programming) versus tediously molding shapes from clay (manual coding). A practical how-to approach to predictive modeling is offered while insisting on the rigor of our disciplined NCDS process. Hands-on data exercises are included in the first eleven chapters. QR code links to educational videos are included in most chapters.Data science background is first explored, discussing basic definitions and data scientist skill sets. This is followed by chapters on data preparation, wrangling, and data visualization. Predictive analytics is covered in chapters on machine learning models and model evaluation. Both supervised and unsupervised learning are included in the discourse. Time series forecasting, survival analysis, and geolocation are covered in separate chapters. Artificial intelligence is featured in chapters on image analysis and text mining. Lastly, the potential impact of machine learning and artificial intelligence on Industry 4.0 is covered in the last chapter. A pathway for statisticians, Lean Six Sigma practitioners, and other professionals is offered to learn predictive modeling techniques to enable organizations to successfully pursue Industry 4.0 goals.
Empowering The Citizen Data Scientist In Everyone
DOWNLOAD
Author : David Guggenheim
language : en
Publisher: CitizenAnalytics LLC
Release Date : 2023-10-26
Empowering The Citizen Data Scientist In Everyone written by David Guggenheim and has been published by CitizenAnalytics LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-26 with Computers categories.
This book contains our citizen data science philosophy, theories of machine learning explained in plain English, practical applications for many types of predictive and interpretable models, and the software and datasets required for doing real data science without becoming a data scientist. The data mining process flows, hosted in Jupyter notebooks along with the datasets in the cloud, are complete, and templates are fully populated for all main types of models. In fact, this book is where template-driven data analytics gets its start, but you will decide where it ends as it can be applied to limitless situations. While the backend technology is very advanced, you can use a Chromebook to build, run, and analyze professional-grade machine learning models using this guide.
Data Analytics Made Easy
DOWNLOAD
Author : Andrea De Mauro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-08-30
Data Analytics Made Easy written by Andrea De Mauro 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 2021-08-30 with Business & Economics categories.
Learn how to gain insights from your data as well as machine learning and become a presentation pro who can create interactive dashboards Key FeaturesEnhance your presentation skills by implementing engaging data storytelling and visualization techniquesLearn the basics of machine learning and easily apply machine learning models to your dataImprove productivity by automating your data processesBook Description Data Analytics Made Easy is an accessible beginner's guide for anyone working with data. The book interweaves four key elements: Data visualizations and storytelling – Tired of people not listening to you and ignoring your results? Don't worry; chapters 7 and 8 show you how to enhance your presentations and engage with your managers and co-workers. Learn to create focused content with a well-structured story behind it to captivate your audience. Automating your data workflows – Improve your productivity by automating your data analysis. This book introduces you to the open-source platform, KNIME Analytics Platform. You'll see how to use this no-code and free-to-use software to create a KNIME workflow of your data processes just by clicking and dragging components. Machine learning – Data Analytics Made Easy describes popular machine learning approaches in a simplified and visual way before implementing these machine learning models using KNIME. You'll not only be able to understand data scientists' machine learning models; you'll be able to challenge them and build your own. Creating interactive dashboards – Follow the book's simple methodology to create professional-looking dashboards using Microsoft Power BI, giving users the capability to slice and dice data and drill down into the results. What you will learnUnderstand the potential of data and its impact on your businessImport, clean, transform, combine data feeds, and automate your processesInfluence business decisions by learning to create engaging presentationsBuild real-world models to improve profitability, create customer segmentation, automate and improve data reporting, and moreCreate professional-looking and business-centric visuals and dashboardsOpen the lid on the black box of AI and learn about and implement supervised and unsupervised machine learning modelsWho this book is for This book is for beginners who work with data and those who need to know how to interpret their business/customer data. The book also covers the high-level concepts of data workflows, machine learning, data storytelling, and visualizations, which are useful for managers. No previous math, statistics, or computer science knowledge is required.
Learn Python By Building Data Science Applications
DOWNLOAD
Author : Philipp Kats
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-08-30
Learn Python By Building Data Science Applications written by Philipp Kats 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 2019-08-30 with Computers categories.
Understand the constructs of the Python programming language and use them to build data science projects Key FeaturesLearn the basics of developing applications with Python and deploy your first data applicationTake your first steps in Python programming by understanding and using data structures, variables, and loopsDelve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in PythonBook Description Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards. What you will learnCode in Python using Jupyter and VS CodeExplore the basics of coding – loops, variables, functions, and classesDeploy continuous integration with Git, Bash, and DVCGet to grips with Pandas, NumPy, and scikit-learnPerform data visualization with Matplotlib, Altair, and DatashaderCreate a package out of your code using poetry and test it with PyTestMake your machine learning model accessible to anyone with the web APIWho this book is for If you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.
No Code Data Science And Statistics
DOWNLOAD
Author : Abhinandan H. Patil
language : en
Publisher:
Release Date : 2022-08-10
No Code Data Science And Statistics written by Abhinandan H. Patil and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-10 with Education categories.
This Book is for someone who wants to get hold of Statistics and Data Science in experimentation way. The hands-on learners. Since the learning is top-down approach in this Book the learning curve should be steep. We will not be covering the basics/definitions of Statistics or Data Science in this Book rather we will be taking direct dive to solve the problems. This Book is for intermediate learners of Statistics and Data Science. This Book does give pointers to some great Books. This Book is more of LAB session with mainly very capable tool JASP. To make maximum out of this Book repeat the experiments in this Book as we progress. Author is not sharing the JASP files intentionally in the GIT Hub.
Encyclopedia Of Data Science And Machine Learning
DOWNLOAD
Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2023-01-20
Encyclopedia Of Data Science And Machine Learning written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Computers categories.
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Data Science From Scratch
DOWNLOAD
Author : Steven Cooper
language : en
Publisher: Roland Bind
Release Date : 2018-08-10
Data Science From Scratch written by Steven Cooper and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-10 with Computers categories.
★☆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!
A Beginners Guide To Data Science
DOWNLOAD
Author : Enamul Haque
language : en
Publisher:
Release Date : 2021-03-31
A Beginners Guide To Data Science written by Enamul Haque and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-31 with categories.
Calling all the Aspiring Data Scientists! This book is your "one-stop-shop" to kick start your data science career without knowing how to code! In fact, data science doesn't have to be complicated! With this book, you will grow an understanding of the foundations of data science and its applications. To master this book, you don't need technical abilities. This book is recommended for beginners and anybody who want to understand data science conveniently. You don't need a big textbook to master data science today. A straightforward language has been used to ensure ease of understanding, especially for beginners. Key features include: Introduction to data scienceHistory of data scienceData science life-cycleData science tools and technologiesData science methodologyData science modelsDeveloping data science business strategyManaging data science projectsBecoming a data scientist, data engineers etc.Doing data science without codingBig dataData MiningArtificial intelligenceMachine learningDeep learningNeural networksMathematical analysisStatistical modellingUnderstanding the fundamentals of Python and RDatabase structures and principlesRobotic Process AutomationData science acronyms you need to knowOnline free data science learning resources And a lot more
Data Science On The Google Cloud Platform
DOWNLOAD
Author : Valliappa Lakshmanan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-03-29
Data Science On The Google Cloud Platform written by Valliappa Lakshmanan 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 2022-03-29 with Computers categories.
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines