Download or read book Data Preprocessing with Python for Absolute Beginners written by Ai Publishing and published by . This book was released on 2020-03-21 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you looking for a hands-on approach to learn Data Preprocessing techniques fast? Do you need to start learning Python for Data Preparation from Scratch? This book is for you.This book is dedicated to data preparation and explains how to perform different data preparation techniques on a variety of datasets using various data preparation libraries written in the Python programming language. It is suggested that you use this book for data preparation purposes only and not for data science or machine learning. For the application of data preparation in data science and machine learning, read this book in conjunction with dedicated books on machine learning and data science. This book explains the process of data preparation using various libraries from scratch. All the codes and datasets have been provided. However, to download data preparation libraries, you will need the internet. In addition to beginners to data preparation with Python, this book can also be used as a reference manual by intermediate and experienced programmers as it contains data preparation code samples using multiple data visualization libraries. What this book offers... The book follows a very simple approach. It is divided into nine chapters. Chapter 1 introduces the basic concept of data preparation, along with the installation steps for the software that we will need to perform data preparation in this book. Chapter 1 also contains a crash course on Python. A brief overview of different data types is given in Chapter 2. Chapter 3 explains how to handle missing values in the data, while the categorical encoding of numeric data is explained in Chapter 4. Data discretization is presented in Chapter 5. Chapter 6 explains the process of handline outliers, while Chapter 7 explains how to scale features in the dataset. Handling of mixed and datetime data type is explained in Chapter 8, while data balancing and resampling has been explained in Chapter 9. A full data preparation final project is also available at the end of the book. In each chapter, different types of data preparation techniques have been explained theoretically, followed by practical examples. Each chapter also contains an exercise that students can use to evaluate their understanding of the concepts explained in the chapter.Clear and Easy to Understand SolutionsAll solutions in this book are extensively tested by a group of beta readers. The solutions provided are simplified as much as possible so that they can serve as examples for you to refer to when you are learning a new skill.Topics Covered: What Is Data Preparation Python Crash Course Different Libraries for Data Preparation Understanding Data Types Handling Missing Data Encoding Categorical Data Data Discretization Outlier Handling Feature Scaling Handling Mixed and DateTime Variables Handling Imbalanced Datasets A Complete Data Preparation Pipeline Project 1 - Data Preparation Project 2 - Classification Project Project 3 - Regression Project Click the BUY button and download the book now to start learning Data Preprocessing Using Python.

Download or read book Data Preprocessing with Python for Absolute Beginners written by A. I. Sciences OU and published by . This book was released on 2021-03-25 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to data preparation and explains how to perform different data preparation techniques on various datasets using different data preparation libraries written in the Python programming language.Key Features* A crash course in Python to fill any gaps in prerequisite knowledge and a solid foundation on which to build your new skills* A complete data preparation pipeline for your guided practice* Three real-world projects covering each major task to cement your learned skills in data preparation, classification, and regressionBook DescriptionThe book follows a straightforward approach. It is divided into nine chapters. Chapter 1 introduces the basic concept of data preparation and installation steps for the software that we will need to perform data preparation in this book. Chapter 1 also contains a crash course on Python, followed by a brief overview of different data types in Chapter 2. You will then learn how to handle missing values in the data, while the categorical encoding of numeric data is explained in Chapter 4.The second half of the course presents data discretization and describes the handling of outliers' process. Chapter 7 demonstrates how to scale features in the dataset. Subsequent chapters teach you to handle mixed and DateTime data type, balance data, and practice resampling. A full data preparation final project is also available at the end of the book.Different types of data preprocessing techniques have been explained theoretically, followed by practical examples in each chapter. Each chapter also contains an exercise that students can use to evaluate their understanding of the chapter's concepts. By the end of this course, you will have built a solid working knowledge in data preparation--the first steps to any data science or machine learning career and an essential skillset for any aspiring developer.The code bundle for this course is available at https://www.aispublishing.net/book-data-preprocessingWhat you will learn* Explore different libraries for data preparation* Understand data types* Handle missing data* Encode categorical data* Discretize data* Learn to handle outliers* Practice feature scaling* Handle mixed and DateTime variables and imbalanced datasets* Employ your new skills to complete projects in data preparation, classification, and regressionWho this book is forIn addition to beginners in data preparation with Python, this book can also be used as a reference manual by intermediate and experienced programmers. It contains data preprocessing code samples using multiple data visualization libraries.

Download or read book Data Preprocessing With Python for Absolute Beginners written by AI. Publishing and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Science With Python written by Henry George and published by . This book was released on 2020-01-24 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to learn what data science is all about? Familiar with Python and wonder how to use it to its fullest extent? Then this guide is for you.Learn how to set up your data science toolbox containing all the important tools you will need to complete a data science project. Python is the number one programming language for data science and this book will walk you through a project, allowing you to get familiar with the tools so you can move on to your own projects.Earn how to preprocess data, load it, transform it and fix it for the purpose of analysis. Learn how to explore data and how to process it before looking at the fundamental machine learning algorithms required for data science, at graph analysis and visualization tools. You will learn: -How to use Python to set up your data science toolbox-How to prepare data-How to solve data science problems-How to explore and manipulate data-All about the data science pipeline and how to set one up-How to choose the right algorithm for the right task-The visualization tools you need to present your resultsData science is here and it's here to stay so start your data science journey right now by clicking that Buy Now button.

Download or read book Machine Learning with Python written by Mark Coding and published by Charlie Creative Lab. This book was released on 2020-10-25 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you tired of taking risks, hoping things will pay off big but you are always worried about the risks? Have you been hearing about some of the buzzwords in the world of business like data science, data analysis, and machine learning, but worry they will be too hard for you to catch onto and learn more about? Are you looking for ways to know more about your industry, what products to release, and how to gain a competitive edge overall, without all of the risks? If this sounds like something you have dealt with, then machine learning for Python is the best option for you! This guidebook is going to dive into all of the parts of this that you need to know right now! Inside, we will explore what machine learning is all about, how to add it into Python, and so many of the algorithms and steps you need to really make all of this a reality for your needs. Inside this guidebook, be prepared to take some of the basics of Python and machine learning, and turn yourself into an expert, someone who knows with certainty that all of your decisions are the right ones, and who has data and information to back them all up. Some of the different topics we will discuss in this guidebook to help make this a reality, and to ensure we can learn and make good predictions, includes: -The basics of machine learning and artificial intelligence. -How to work with Python and machine learning to get started with all the options that work with this topic. -How to work with some of the different Python machine learning algorithms out there for you to choose from. -How to work with a model of machine learning and go through the process of having your computer learn on its own. -More examples of how to work with Python and machine learning together. -The importance of working with neural networks and what all of this can mean to your code. -A look at deep learning and data science that can take your machine learning to the next level. -The steps you need to know to get started with data Preprocessing. -A look at where machine learning and more will be able to help lead us to the future. Working with machine learning for Python is an important topic a lot of businesses are diving into now more than ever. They see the value of working with data science, and what this process can do for them in terms of their success and their sound business decisions. When you are ready to learn how to use machine learning for Python for some of your business and data science needs, make sure to take a look at this guidebook to get started.

Download or read book Hands On Data Preprocessing in Python written by Roy Jafari and published by Packt Publishing Ltd. This book was released on 2022-01-21 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get your raw data cleaned up and ready for processing to design better data analytic solutions Key FeaturesDevelop the skills to perform data cleaning, data integration, data reduction, and data transformationMake the most of your raw data with powerful data transformation and massaging techniquesPerform thorough data cleaning, including dealing with missing values and outliersBook Description Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who's developed college-level courses on data preprocessing and related subjects. With this book, you'll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you'll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data. By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools. What you will learnUse Python to perform analytics functions on your dataUnderstand the role of databases and how to effectively pull data from databasesPerform data preprocessing steps defined by your analytics goalsRecognize and resolve data integration challengesIdentify the need for data reduction and execute itDetect opportunities to improve analytics with data transformationWho this book is for This book is for junior and senior data analysts, business intelligence professionals, engineering undergraduates, and data enthusiasts looking to perform preprocessing and data cleaning on large amounts of data. You don't need any prior experience with data preprocessing to get started with this book. However, basic programming skills, such as working with variables, conditionals, and loops, along with beginner-level knowledge of Python and simple analytics experience, are a prerequisite.

Download or read book Python Programming for the Absolute Beginner written by Michael Dawson and published by Course Technology. This book was released on 2003 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are new to programming with Python and are looking for a solid introduction, this is the book for you. Developed by computer science instructors, books in the for the absolute beginner series teach the principles of programming through simple game creation. You will acquire the skills that you need for more practical Python programming applications and you will learn how these skills can be put to use in real- world scenarios. Best of all, by the time you finish this book you will be able to apply the basic principles youve learned to the next programming language you tackle.

Download or read book Python for Absolute Beginners written by Josh Davison and published by . This book was released on 2020-04-03 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you ready to start your path to becoming a Data Scientist! This comprehensive book will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms! Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This book is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Enroll Now

Download or read book Python for DATA SCIENCE written by Warren Overby and published by . This book was released on 2020-11-16 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you looking for a crash course about Python for Data Science? Do you also want to come up easily with your first project in no time? Are you constantly looking for information on social networks (like FB groups) and you don't know where to start with Python programming? If so, then keep on reading! Python is nowadays often used in data science because it is a mature programming language that has excellent properties for beginning programmers. Some of the most notable of these properties are the easy-to-read password, suppression of optional delimiters, dynamic writing, and use of dynamic memory. Data science uses science strategies to process data and separate information from it. It moves away from an idea similar to Big Data and Data Mining. It requires innovative equipment along with useful calculation and programming to deal with data problems or process data to gain substantial learning from them. The improvement and highly useful research in the world of Computing and Technology have increased the importance of its most basic and essential concepts in a thousand aspects. This notion of principle is what we continuously refer to as data, and that data is the only thing that "opens the way" for everything in the world. The world's largest organizations and companies have built their creation and their philosophies and determine a unique portion of their pay through data. The value and importance of data can be understood with the simple certainty that a legitimate data storage/distribution center is a million times more profitable than the pure gold mine in the advanced world. However, learning all the required skills to master data science and machine learning could certainly be challenging. BUT DON'T WORRY In this complete Guide we have condensed all the knowledge you need in a simple and practical way. Through his revolutionary and systematic approach, you will skyrocket your skills, regardless of your previous experience, with the best techniques to manipulate and process datasets, learn in deep the principles of Python programming, and their real-world applications. In this book you are ready to discover: How to move your first steps in the world of "Python". I will explain you, with easy to follow visuals, how to exactly install Python on the Mac OS X, Windows and Linux systems. How to easily setting up your first Data Science project from scratch with Python in less than 7 days. Practical codes and exercises to use Python. I will explain you the step-by-step process to create games like: "magic 8 ball" and "hangman game". How the regression algorithms (used in data science) work and what are the best tips and tricks to work with them. How Scikit-Learn library is used in the development of a machine learning algorithm. And much more! Even if you're still a beginner struggling on how to start projects with Python, this book will surely give you the right information to skyrocket your programming skills to the next level. ★ Keep in mind: "Real progress happens only when advantages of a new technology become available to everybody" (H. Ford). ★ Pick up your own copy today by clicking the BUY NOW button at the top of the page!

Download or read book Data Science for Beginners written by Andrew Park and published by Independently Published. This book was released on 2020-01-26 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the world of Python, Data Analysis, Machine Learning and Data Science with this comprehensive 4-in-1 bundle. Do you want to learn more about the amazing world of Data Science? Or are you interested in becoming a Python geek? Then keep reading. Created with the beginner in mind, this powerful bundle delves into the fundamentals behind Python and Data Science, from basic code and concepts to complex Neural Networks and data manipulation. Inside, you'll discover everything you need to know to get started with Python and Data Science, and begin your journey to success! In book one, PYTHON FOR BEGINNERS, you will learn: How to install Python What are the different Python Data Types, Variables and Basic Operators Data Structures, Functions and Files Conditional and Loops in Python Object-Oriented Programming (OOP), Inheritance and Polymorphism Essential Programming Tools and Exception Handling An application to Decision Trees And Much More! In book two, PYTHON FOR DATA ANALYSIS, you will learn: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis Neural Network The 7 Python libraries that make Python one of the best choices for Data Analysis How Data Visualization and Matplotlib can help you to understand the data you are working with. Some of the main industries that are using data to improve their business with 14 real-world applications And Much More! In book three, PYTHON MACHINE LEARNING, you will learn: What is Machine Learning and how it is applied in real-world situations Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence Machine learning training models, Regression techniques and Linear Regression in Python How to use Lists and Modules in Python The 12 essential libraries for Machine Learning in Python Artificial Neural Networks And Much More! And in book four, PYTHON DATA SCIENCE, you will learn: What Data Science is all about and why so many companies are using it to give them a competitive edge. Why Python and how to use it to implement Data Science The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with practical codes and exercises The 7 most important algorithms and models in Data Science Data Aggregation, Group Operations, Databases and Data in the Cloud 9 important Data Mining techniques in Data Science And So Much More! Whether you're a complete beginner or a programmer looking to improve his skillset, Data Science for Beginners is your all-in-one solution to mastering the world of Python and Data Science. Would you like to know more?Scroll Up and Click on the BUY NOW Button to Get Your Copy!

Download or read book Python for Data Science For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2019-02-27 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

Download or read book Machine Learning With Python written by Daniel Géron and published by . This book was released on 2021-02-19 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Machine Learning with Python written by Daniel Geron and published by . This book was released on 2019-07-19 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Buy the Paperback Version of this Book and get the Kindle Book Version for FREEDo want to learn how machine learning and neural networks work quickly and simply? Do you want to know how to build a machine learning model and you have no programming skill? Do you want to get started with learning data science? This book is going to guide you to the basics and the principles behind machine learning. Machine learning is an active research domain and includes several different approaches. This book is going to help you understand the different approaches of machine learning and neural networks. It will guide you through the steps you need to build a machine learning model. Machine learning implies programming. This book will teach you Python programming. This book does not require any pre-programming skills. It will help to get you started in Python programming, as well as how to use Python libraries to analyze data and apply machine learning. Overall, this book is a go-to guide for getting started in machine learning modeling using Python programming. Once you get through the book, you will be able to develop your own machine learning models using Python. Through this book, you will learn: - Principles of machine learning - Types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning - Advantages of each type of machine learning - Principle and types of neural networks - Steps to develop and fit artificial neural network model - Getting started and installing Python - Tools and platforms for Python programming - How to use pandas, NumPy and matplotlib Python libraries - How to develop a simple linear and logistic machine learning model - How to develop and train a multi-layer artificial neural network two ways: from scratch and using the Python libraries Even if you don't have any background in machine learning and Python programming, this book will give you the tools to develop machine learning models. Would you like to know more? Scroll to the top of the page and select the BUY NOW button.

Download or read book Python Data Science written by James Bolt and published by James Bolt. This book was released on 2021-04-19 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: **55% OFF for Bookstores!! LAST DAYS*** PYTHON DATA SCIENCE Your Customers Never Stop to Use this Awesome Book! Here's the Perfect Solution if You Want to Become the Master of Data Science and Learn Python 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! Buy it Now and let your customers get addicted to this amazing book!

Download or read book Python for Data Science written by Ethan Williams and published by . This book was released on 2019-08-18 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide for beginners to learn Python Programming, especially its application for Data Science. While the lessons in this book are targeted at the absolute beginner to programming, people at various levels of proficiency in Python, or any other programming languages can also learn some basics and concepts of data science. A few Python libraries are introduced, including NumPy, Pandas, Matplotlib, and Seaborn for data analysis and visualisation. To make the lessons more intuitive and relatable, practical examples and applications of each lesson are given. The reader is equally encouraged to practise the techniques via exercises, within and at the end of the relevant chapters. To help the reader get a full learning experience, there are references to relevant reading and practice materials, and the reader is encouraged to click these links and explore the possibilities they offer. It is expected that with consistency in learning and practicing the reader can master Python and the basics of its application in data science. The only limitation to the reader's progress, however, is themselves!

Download or read book Data Science Crash Course for Beginners with Python Fundamentals and Practices with Python written by Ai Publishing and published by AI Publishing LLC. This book was released on 2020-08-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science Crash Course for Beginners with Python Data Science is here to stay. The tremendous growth in the volume, velocity, and variety of data has a substantial impact on every aspect of a business. While data continues to grow exponentially, accuracy remains a problem. This is where data scientists play a decisive role. A data scientist analyzes data, discovers new insights, paints a picture, and creates a vision. And a competent data scientist will provide a business with the competitive edge it needs and address pressing business problems. Data Science Crash Course for Beginners with Python presents you with a hands-on approach to learn data science fast. How Is This Book Different? Every book by AI Publishing has been carefully crafted. This book lays equal emphasis on the theoretical sections as well as the practical aspects of data science. Each chapter provides the theoretical background behind the numerous data science techniques, and practical examples explain the working of these techniques. In the Further Reading section of each chapter, you will find the links to informative data science posts. This book presents you with the tools and packages you need to kick-start data science projects to resolve problems of practical nature. Special emphasis is laid on the main stages of a data science pipeline--data acquisition, data preparation, exploratory data analysis, data modeling and evaluation, and interpretation of the results. In the Data Science Resources section, links to data science resources, articles, interviews, and data science newsletters are provided. The author has also put together a list of contests and competitions that you can try on your own. Another added benefit of buying this book is you get instant access to all the learning material presented with this book-- PDFs, Python codes, exercises, and references--on the publisher's website. They will not cost you an extra cent. The datasets used in this book can be downloaded at runtime, or accessed via the Resources/Datasets folder. The author simplifies your learning by holding your hand through everything. The step by step description of the installation of the software you need for implementing the various data science techniques in this book is guaranteed to make your learning easier. So, right from the beginning, you can experiment with the practical aspects of data science. You'll also find the quick course on Python programming in the second and third chapters immensely helpful, especially if you are new to Python. This book gives you access to all the codes and datasets. So, access to a computer with the internet is sufficient to get started. The topics covered include: Introduction to Data Science and Decision Making Python Installation and Libraries for Data Science Review of Python for Data Science Data Acquisition Data Preparation (Preprocessing) Exploratory Data Analysis Data Modeling and Evaluation Using Machine Learning Interpretation and Reporting of Findings Data Science Projects Key Insights and Further Avenues Click the BUY button to start your Data Science journey.

Download or read book Data Science for Beginners written by Andrew Park and published by . This book was released on 2021-02-09 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ 55% OFF for Bookstores! Now at $49.95 instead of $59.95! ★ Your Customers Will Never Stop To Use This Complete Guide! Did you know that according to Harvard Business Review the Data Scientist is the sexiest job of the 21st century? And for a reason! If "sexy" means having rare qualities that are much in demand, data scientists are already there. They are expensive to hire and, given the very competitive market for their services, difficult to retain. There simply aren't a lot of people with their combination of scientific background and computational and analytical skills. Data Science is all about transforming data into business value using math and algorithms. And needless to say, Python is the must-know programming language of the 21st century. If you are interested in coding and Data Science, then you must know Python to succeed in these industries! Data Science for Beginners is the perfect place to start learning everything you need to succeed. Contained within these four essential books are the methods, concepts, and important practical examples to help build your foundation for excelling at the discipline that is shaping the modern word. This bundle is perfect for programmers, software engineers, project managers and those who just want to keep up with technology. With these books in your hands, you will: ● Learn Python from scratch including the basic operations, how to install it, data structures and functions, and conditional loops ● Build upon the fundamentals with advanced techniques like Object-Oriented Programming (OOP), Inheritance, and Polymorphism ● Discover the importance of Data Science and how to use it in real-world situations ● Learn the 5 steps of Data Analysis so you can comprehend and analyze data sitting right in front of you ● Increase your income by learning a new, valuable skill that only a select handful of people take the time to learn ● Discover how companies can improve their business through practical examples and explanations ● And Much More! This bundle is essential for anyone who wants to study Data Science and learn how the world is moving to an open-source platform. Whether you are a software engineer or a project manager, jump to the next level by developing a data-driven approach and learning how to define a data-driven vision of your business! Order Your Copy of the Bundle and Let Your Customers Start Their New Career Path Today!