Python Data Analysis For Beginners 2021
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Python Data Analysis For Beginners 2021
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Author : Steven Williams
language : en
Publisher:
Release Date : 2020-11-27
Python Data Analysis For Beginners 2021 written by Steven Williams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-27 with Computers categories.
Master the Python Programming Language and Data Analysis With This Comprehensive Guide! If you want to learn more about Data Analysis or how to master it with the Python Programming Language, then keep reading. This book will teach you how to achieve all that with the help of data analysis and data science. Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations. The goal of this book is not only to learn about data analysis but to go from this theoretical to practical knowledge and application. In other words, you'll be able to complete your own analysis, implement its methods in your business, and master the Python Programming Language! Here's what you'll learn with this book -The importance of data analysis and why every successful business and industry are using it -How to process data with tools and techniques used by data scientists -The concepts behind Python programming -How to use the "data munging" process -How to use Python libraries such as Pandas and NumPy for data analysis -The importance of data visualization -How to create the right analytical algorithm for predicting the market trends -How to write codes, and create programs and databases -And much more! Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, and the most important real-world applications. If you want to modernize your company and your skills, make the most of your data and become a competitive force on the market, Scroll up, click on "Buy Now with 1-Click", and Get Your Copy Now!
Python Data Science For Beginners 2021
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Author : Steven Williams
language : en
Publisher:
Release Date : 2020-11-27
Python Data Science For Beginners 2021 written by Steven Williams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-27 with Computers categories.
If you want to learn more about Data Science or how to master it with the Python Programming Language Step-by-Step, then keep reading. Data Science is one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?" Data Science includes all the different steps that you take with the data: collecting and cleaning them if they come from more than one source, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations. You will learn about the main steps that are needed to correctly implement Data Science techniques and the algorithms to help you sort through the data and see some amazing results. Some of the topics that we will discuss inside include -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 -A blueprint for the most used frameworks for Python data science -How to process and understand the data and design your own projects -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 -What is the intersection between Machine Learning and Data Science and how to combine them -Functions and Modules in Python -Data Aggregation and Group Operations -Interaction with databases and data in the cloud -And Much More! Even if you have never implemented Data Science techniques, learning them is easier than it looks. You just need the right guidance. And Python Data Science provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn, the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications. Would You Like To Know More? Scroll up and click on the BUY NOW button to get your copy now!
Hacker S Guide To Machine Learning Concepts
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Author : Trilokesh Khatri
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Hacker S Guide To Machine Learning Concepts written by Trilokesh Khatri and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Hacker’s Guide to Machine Learning Concepts is crafted for those eager to dive into the world of ethical hacking. This book demonstrates how ethical hacking can help companies identify and fix vulnerabilities efficiently. With the rise of data and the evolving IT industry, the scope of ethical hacking continues to expand. We cover various hacking techniques, identifying weak points in programs, and how to address them. The book is accessible even to beginners, offering chapters on machine learning and programming in Python. Written in an easy-to-understand manner, it allows learners to practice hacking steps independently on Linux or Windows systems using tools like Netsparker. This book equips you with fundamental and intermediate knowledge about hacking, making it an invaluable resource for learners.
Applied Machine Learning For Data Science Practitioners
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Author : Vidya Subramanian
language : en
Publisher: John Wiley & Sons
Release Date : 2025-04-29
Applied Machine Learning For Data Science Practitioners written by Vidya Subramanian 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 2025-04-29 with Mathematics categories.
A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML. Data Preparation covers the process of framing ML problems and preparing data and features for modeling. ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection. Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model. ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics. Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.
Data Science And Applications
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Author : Satyasai Jagannath Nanda
language : en
Publisher: Springer Nature
Release Date : 2026-01-01
Data Science And Applications written by Satyasai Jagannath Nanda and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Computers categories.
This book gathers outstanding papers presented at the 6th International Conference on Data Science and Applications (ICDSA 2025), organized by Soft Computing Research Society (SCRS) and Malaviya National Institute of Technology Jaipur, India, from 16 to 18 July 2025. The book is divided into eight volumes, and it covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.
Artificial Intelligence And Computational Dynamics For Biomedical Research
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Author : Ankur Saxena
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-11-07
Artificial Intelligence And Computational Dynamics For Biomedical Research written by Ankur Saxena and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-07 with Computers categories.
This work presents the latest development in the field of computational intelligence to advance Big Data and Cloud Computing concerning applications in medical diagnosis. As forum for academia and professionals it covers state-of-the-art research challenges and issues in the digital information & knowledge management and the concerns along with the solutions adopted in these fields.
Data Mining And Exploration
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Author : Chong Ho Alex Yu
language : en
Publisher: CRC Press
Release Date : 2022-10-27
Data Mining And Exploration written by Chong Ho Alex Yu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Business & Economics categories.
This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. First, most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between traditional statistics and modern data science; as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a “black box”, without a comprehensive view of the foundational differences between traditional and modern methods (e.g., dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation etc.). This book delineates the transition between classical methods and data science (e.g. from p value to Log Worth, from resampling to ensemble methods, from content analysis to text mining etc.). Second, this book aims to widen the learner's horizon by covering a plethora of software tools. When a technician has a hammer, every problem seems to be a nail. By the same token, many textbooks focus on a single software package only, and consequently the learner tends to fit the problem with the tool, but not the other way around. To rectify the situation, a competent analyst should be equipped with a tool set, rather than a single tool. For example, when the analyst works with crucial data in a highly regulated industry, such as pharmaceutical and banking, commercial software modules (e.g., SAS) are indispensable. For a mid-size and small company, open-source packages such as Python would come in handy. If the research goal is to create an executive summary quickly, the logical choice is rapid model comparison. If the analyst would like to explore the data by asking what-if questions, then dynamic graphing in JMP Pro is a better option. This book uses concrete examples to explain the pros and cons of various software applications.
Python For Beginners 2021
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Author : James Hevans
language : en
Publisher: James Hevans
Release Date : 2021-04-19
Python For Beginners 2021 written by James Hevans and has been published by James Hevans this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-19 with categories.
**55% OFF for Bookstores!! LAST DAYS*** PYTHON FOR BEGINNERS 2021 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!
Python For Beginners 2021 Ultimate Step By Step Guide To Machine Learning Using Python
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Author : Leo Sgarbi
language : en
Publisher:
Release Date : 2021-10-23
Python For Beginners 2021 Ultimate Step By Step Guide To Machine Learning Using Python written by Leo Sgarbi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-23 with Computers categories.
Python was developed in 1980s by Guido Van Rossum of Netherlands. Python was developed as an object-oriented language with an emphasis on simplicity, extensibility and flexibility. Python also comes with a large library of pre-built functionality for data science, statistical analysis and data visualizations which make this language very easy to learn and use. In this book we will focus on data science applications of Python with hands on examples that allow you to go from novice to expert in a short period of time! We will start with getting you set up with Python, introducing you to its data structures and libraries and then finally getting into the data science applications of this beautiful language. What you will find different about this book is the visual and hands on approach it takes to teaching Python. Since this book is directed at beginners, we will not drone on and on about complex concepts or make this book text heavy. Instead, we will take inspiration from the Zen of Python by Tim Peters.
Python For Data Analysis
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Author : Andrew Park
language : en
Publisher: Andrew Park
Release Date : 2021-02-13
Python For Data Analysis written by Andrew Park and has been published by Andrew Park this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-13 with categories.
★ 55% OFF for Bookstores! NOW at $33,97 instead of $43,97!Do you want to learn more about Data Analysis and how to master it with Python?Your Customers Will Love This Amazing Guide! Everyone talks about data today. You have probably come across the term "data" more times than you can remember in one day. Data as a concept is so wide. One thing that is true about data is that it can be used to tell a story. The story could be anything from explaining an event to predicting the future. Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations. With Python for Data Analysis you will learn about the main steps that are needed to correctly implement Data Analysis and the procedures to help you extract the right insights from the right data. Some of the topics that we will discuss inside include: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis Pandas, Jupyter and PyTorch The 7 Python libraries that make Python one of the best choices for Data Analysis Neural Network 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! While most books focus on how to implement advanced predictive models, this book takes the time to explain the basic concepts and all the necessary steps to correctly implement Data Analysis, including Data Visualization and providing practical examples and simple coding scripts. Don't miss the opportunity to learn more about these topics. Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, and the most important real-world applications. Would You Like To Know More? Buy it NOW and Let Your Customers Get Addicted to This Amazing Book!