Python For Data Science From Novice To Expert
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Python For Data Science From Novice To Expert
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Author : F.G. Cardin
language : en
Publisher:
Release Date :
Python For Data Science From Novice To Expert written by F.G. Cardin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Want to learn data science but don't know where to start? "Python for Data Science" provides a clear and accessible path. This book guides you through the essential Python libraries and techniques, empowering you to analyze data and build machine learning models.
Python Journey From Novice To Expert
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Author : Fabrizio Romano
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-08-31
Python Journey From Novice To Expert written by Fabrizio Romano 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 2016-08-31 with Computers categories.
Learn core concepts of Python and unleash its power to script highest quality Python programs About This Book Develop a strong set of programming skills with Pyhton that you will be able to express in any situation, on every platform, thanks to Python's portability Stop writing scripts and start architecting programs by applying object-oriented programming techniques in Python Learn the trickier aspects of Python and put it in a structured context for deeper understanding of the language Who This Book Is For This course is meant for programmers who wants to learn Python programming from a basic to an expert level. The course is mostly self-contained and introduces Python programming to a new reader and can help him become an expert in this trade. What You Will Learn Get Python up and running on Windows, Mac, and Linux in no time Grasp the fundamental concepts of coding, along with the basics of data structures and control flow Understand when to use the functional or the object-oriented programming approach Extend class functionality using inheritance Exploit object-oriented programming in key Python technologies, such as Kivy and Django Understand how and when to use the functional programming paradigm Use the multiprocessing library, not just locally but also across multiple machines In Detail Python is a dynamic and powerful programming language, having its application in a wide range of domains. It has an easy-to-use, simple syntax, and a powerful library, which includes hundreds of modules to provide routines for a wide range of applications, thus making it a popular language among programing enthusiasts.This course will take you on a journey from basic programming practices to high-end tools and techniques giving you an edge over your peers. It follows an interesting learning path, divided into three modules. As you complete each one, you'll have gained key skills and get ready for the material in the next module.The first module will begin with exploring all the essentials of Python programming in an easy-to-understand way. This will lay a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring topics, like GUIs, web apps, and data science.In the second module you will learn about object oriented programming techniques in Python. Starting with a detailed analysis of object-oriented technique and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This module fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software.With a good foundation of Python you will move onto the third module which is a comprehensive tutorial covering advanced features of the Python language. Start by creating a project-specific environment using venv. This will introduce you to various Pythonic syntax and common pitfalls before moving onto functional features and advanced concepts, thereby gaining an expert level knowledge in programming and teaching how to script highest quality Python programs. Style and approach This course follows a theory-cum-practical approach having all the ingredients that will help you jump into the field of Python programming as a novice and grow-up as an expert. The aim is to create a smooth learning path that will teach you how to get started with Python and carry out expert-level programming techniques at the end of course.
Beginning Python
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Author : Magnus Lie Hetland
language : en
Publisher: Apress
Release Date : 2006-11-07
Beginning Python written by Magnus Lie Hetland and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-07 with Computers categories.
Beginning Python: From Novice to Professional is the most comprehensive book on the Python ever written. Based on Practical Python, this newly-revised book is both an introduction and practical reference for a swath of Python-related programming topics, including addressing language internals, database integration, network programming, and web services. Advanced topics, such as extending Python and packaging/distributing Python applications, are also covered. Ten different projects illustrate the concepts introduced in the book. You will learn how to create a P2P file-sharing application and a web-based bulletin board, and how to remotely edit web-based documents and create games. Author Magnus Lie Hetland is an authority on Python and previously authored Practical Python. He also authored the popular online guide, Instant Python Hacking, on which both books are based.
Data Science With Python
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Author : Rohan Chopra
language : en
Publisher:
Release Date : 2019-07-09
Data Science With Python written by Rohan Chopra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-09 with Computers categories.
A Hands On Introduction To Data Science
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Author : Chirag Shah
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-02
A Hands On Introduction To Data Science written by Chirag Shah and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Business & Economics categories.
An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.
The Hitchhiker S Guide To Python
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Author : Kenneth Reitz
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-08-30
The Hitchhiker S Guide To Python written by Kenneth Reitz 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 2016-08-30 with Computers categories.
The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversityâ??and possibly dilution. This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhikerâ??s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.
Data Science For Marketing Analytics
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Author : Tommy Blanchard
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-03-30
Data Science For Marketing Analytics written by Tommy Blanchard 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 2019-03-30 with Computers categories.
Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learnAnalyze and visualize data in Python using pandas and MatplotlibStudy clustering techniques, such as hierarchical and k-means clusteringCreate customer segments based on manipulated data Predict customer lifetime value using linear regressionUse classification algorithms to understand customer choiceOptimize classification algorithms to extract maximal informationWho this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.
Learn Python By Building Data Science Applications
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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.
Python For Mechanical And Aerospace Engineering
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Author : Alex Kenan
language : en
Publisher: Alex Kenan
Release Date : 2021-01-01
Python For Mechanical And Aerospace Engineering written by Alex Kenan and has been published by Alex Kenan this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-01 with Computers categories.
The traditional computer science courses for engineering focus on the fundamentals of programming without demonstrating the wide array of practical applications for fields outside of computer science. Thus, the mindset of “Java/Python is for computer science people or programmers, and MATLAB is for engineering” develops. MATLAB tends to dominate the engineering space because it is viewed as a batteries-included software kit that is focused on functional programming. Everything in MATLAB is some sort of array, and it lends itself to engineering integration with its toolkits like Simulink and other add-ins. The downside of MATLAB is that it is proprietary software, the license is expensive to purchase, and it is more limited than Python for doing tasks besides calculating or data capturing. This book is about the Python programming language. Specifically, it is about Python in the context of mechanical and aerospace engineering. Did you know that Python can be used to model a satellite orbiting the Earth? You can find the completed programs and a very helpful 595 page NSA Python tutorial at the book’s GitHub page at https://www.github.com/alexkenan/pymae. Read more about the book, including a sample part of Chapter 5, at https://pymae.github.io
A Smarter Way To Learn Python
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Author : Mark Myers
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-08-09
A Smarter Way To Learn Python written by Mark Myers and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-09 with Python (Computer program language) categories.
I designed a learning system for myself that quadrupled my aptitude for learning computer languages. It worked so well for me that I've used it to teach coding to grandmothers, cab drivers, musicians, and 50,000 other newbies. Washington University research shows that a key teaching method I use--interactive recall practice--improves learning performance 400 percent. Computer languages are not inherently hard to understand, even for non-techies. Remembering is the problem. Research shows that you will remember everything if you're repeatedly asked to recall it. That's the beauty of flash cards. But technology offers an even better way to make information stick. With my book you get almost a thousand interactive exercises--they're free online--that embed the whole book in your memory. Algorithms check your work to make sure you know what you think you know. When you stumble, you do the exercise again. You keep trying until you know the chapter cold. The exercises keep you engaged, give you extra practice where you're shaky, and prepare you for each next step. Every lesson is built on top of a solid foundation that you and I have carefully constructed. Each individual step is small. But all the little steps add up to real knowledge--knowledge that you retain. You don't need to be a computer genius to learn Python. You just need to be smart about how you learn it.--Amazon.com description.