Data Preprocessing With Python For Absolute Beginners

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Data Preprocessing With Python For Absolute Beginners

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Author : AI. Publishing
language : en
Publisher:
Release Date : 2020

Data Preprocessing With Python For Absolute Beginners written by AI. Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

Data Preprocessing With Python For Absolute Beginners

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Author : Ai Publishing
language : en
Publisher:
Release Date : 2020-03-21

Data Preprocessing With Python For Absolute Beginners written by Ai Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-21 with categories.

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.

Data Preprocessing With Python For Absolute Beginners

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Author : A. I. Sciences OU
language : en
Publisher:
Release Date : 2021-03-25

Data Preprocessing With Python For Absolute Beginners written by A. I. Sciences OU and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-25 with categories.

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.

Machine Learning For Absolute Beginners

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Author : Jonathan K. Hari
language : en
Publisher: epubli
Release Date : 2025-06-23

Machine Learning For Absolute Beginners written by Jonathan K. Hari and has been published by epubli this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-23 with Computers categories.

Machine Learning for Absolute Beginners In a world where artificial intelligence is shaping the future, understanding machine learning is no longer optional—it's essential. This book takes you on a journey through the fundamentals of AI and data science, breaking down complex concepts into simple, beginner-friendly language. Whether you're a tech enthusiast, an aspiring data scientist, or just curious about the power of AI, this step-by-step guide will help you grasp the essentials without needing any prior coding experience. Inside This Book, You'll Discover: The difference between AI, machine learning, and deep learning Types of machine learning: Supervised, unsupervised, and reinforcement learning Key concepts like data, features, labels, and models Understanding algorithms, from linear regression to neural networks How to prepare and clean data for machine learning An introduction to Python and popular ML libraries like Scikit-Learn, TensorFlow, and PyTorch Real-world applications and ethical considerations in AI This book is designed for absolute beginners, ensuring you build a strong foundation in machine learning without the need for complex mathematics or programming skills. If you've ever wanted to explore AI but didn't know where to start—this is your gateway into the exciting world of machine learning! Scroll Up and Grab Your Copy Today!

Machine Learning With Python

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Author : Mark Coding
language : en
Publisher: Charlie Creative Lab
Release Date : 2020-10-25

Machine Learning With Python written by Mark Coding and has been published by Charlie Creative Lab this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-25 with categories.

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.

Learn Python From An Expert The Complete Guide With Artificial Intelligence

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Author : Edson L P Camacho
language : en
Publisher:
Release Date : 2023-06-08

Learn Python From An Expert The Complete Guide With Artificial Intelligence written by Edson L P Camacho and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-08 with Computers categories.

The Ultimate Guide to Advanced Python and Artificial Intelligence: Unleash the Power of Code! Are you ready to take your Python programming skills to the next level and dive into the exciting world of artificial intelligence? Look no further! We proudly present the comprehensive book written by renowned author Edson L P Camacho: "Advanced Python: Mastering AI." In today's rapidly evolving technological landscape, the demand for AI professionals is soaring. Python, with its simplicity and versatility, has become the go-to language for AI development. Whether you are a seasoned Pythonista or a beginner eager to learn, this book is your gateway to mastering AI concepts and enhancing your programming expertise. What sets "Advanced Python: Mastering AI" apart from other books is its unparalleled combination of in-depth theory and hands-on practicality. Edson L P Camacho, a leading expert in the field, guides you through every step, from laying the foundation of Python fundamentals to implementing cutting-edge AI algorithms. Here's a glimpse of what you'll find within the pages of this comprehensive guide: 1. Python Fundamentals: Review and reinforce your knowledge of Python basics, including data types, control flow, functions, and object-oriented programming. Build a solid foundation to tackle complex AI concepts. 2. Data Manipulation and Visualization: Learn powerful libraries such as NumPy, Pandas, and Matplotlib to handle and analyze data. Understand how to preprocess and visualize data effectively for AI applications. 3. Machine Learning Essentials: Dive into the world of machine learning and explore popular algorithms like linear regression, decision trees, support vector machines, and neural networks. Discover how to train, evaluate, and optimize models for various tasks. 4. Deep Learning and Neural Networks: Delve deeper into neural networks, the backbone of modern AI. Gain insights into deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Implement advanced techniques like transfer learning and generative models. 5. Natural Language Processing (NLP): Explore the fascinating field of NLP and learn how to process and analyze textual data using Python. Discover techniques like sentiment analysis, named entity recognition, and text generation. 6. Computer Vision: Unleash the power of Python for image and video analysis. Build computer vision applications using popular libraries like OpenCV and TensorFlow. Understand concepts like object detection, image segmentation, and image captioning. 7. Reinforcement Learning: Embark on the exciting journey of reinforcement learning. Master the fundamentals of Q-learning, policy gradients, and deep Q-networks. Create intelligent agents that can learn and make decisions in dynamic environments. "Advanced Python: Mastering AI" not only equips you with the theoretical knowledge but also provides numerous real-world examples and projects to reinforce your understanding. Each chapter is accompanied by practical exercises and coding challenges to sharpen your skills and boost your confidence. Don't miss the opportunity to stay ahead in this AI-driven era. Order your copy of "Advanced Python: Mastering AI" today and unlock the full potential of Python programming with artificial intelligence. Take your career to new heights and become a proficient AI developer. Get ready to write the code that shapes the future!

Data Science With Python

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Author : Henry George
language : en
Publisher:
Release Date : 2020-01-24

Data Science With Python written by Henry George and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-24 with categories.

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.

Systems Engineering Neural Networks

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Author : Alessandro Migliaccio
language : en
Publisher: John Wiley & Sons
Release Date : 2023-02-07

Systems Engineering Neural Networks written by Alessandro Migliaccio and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-07 with Technology & Engineering categories.

SYSTEMS ENGINEERING NEURAL NETWORKS A complete and authoritative discussion of systems engineering and neural networks In Systems Engineering Neural Networks, a team of distinguished researchers deliver a thorough exploration of the fundamental concepts underpinning the creation and improvement of neural networks with a systems engineering mindset. In the book, you’ll find a general theoretical discussion of both systems engineering and neural networks accompanied by coverage of relevant and specific topics, from deep learning fundamentals to sport business applications. Readers will discover in-depth examples derived from many years of engineering experience, a comprehensive glossary with links to further reading, and supplementary online content. The authors have also included a variety of applications programmed in both Python 3 and Microsoft Excel. The book provides: A thorough introduction to neural networks, introduced as key element of complex systems Practical discussions of systems engineering and forecasting, complexity theory and optimization and how these techniques can be used to support applications outside of the traditional AI domains Comprehensive explorations of input and output, hidden layers, and bias in neural networks, as well as activation functions, cost functions, and back-propagation Guidelines for software development incorporating neural networks with a systems engineering methodology Perfect for students and professionals eager to incorporate machine learning techniques into their products and processes, Systems Engineering Neural Networks will also earn a place in the libraries of managers and researchers working in areas involving neural networks.

A Guide To Applied Machine Learning For Biologists

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Author : Mohammad "Sufian" Badar
language : en
Publisher: Springer Nature
Release Date : 2023-06-21

A Guide To Applied Machine Learning For Biologists written by Mohammad "Sufian" Badar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-21 with Science categories.

This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.

Transportation Big Data

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Author : Zhiyuan Liu
language : en
Publisher: Elsevier
Release Date : 2024-11-29

Transportation Big Data written by Zhiyuan Liu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Transportation categories.

Transportation Big Data: Theory and Methods is centered on the big data theory and methods. Big data is now a key topic in transportation, simply because the volume of data has increased exponentially due to the growth in the amount of traffic (all modes) and detectors. This book provides a structured analysis of the commonly used methods for handling transportation big data; it is supported by a wealth of transportation engineering examples, together with codes. It offers a concise, yet comprehensive, description of the key techniques and important tools in transportation big data analysis. - Covers big data applications in transportation engineering in real-world scenarios - Shows how to select different machine learning algorithms for processing, analyzing, and modeling transportation data - Provides an overview of the fundamental concepts of machine learning and how classical algorithms can be applied to transportation-related problems - Provides an overview of Python's basic syntax and commonly used modules, enabling practical data analysis and modeling tasks using Python