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Head first Python : A learner's guide to the fundamentals of python programming / Paul Barry.
California : A Brain-friendly guide, 2023
[200] p. : ill. ; 29 cm.

What will you learn from this book? Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you'll quickly grasp Python's fundamentals by working with built-in data structures and functions. You'll build your very own web app, which--once it's ready for prime time--runs in the cloud. You'll learn how to wrangle data with Python, scrape data from the web, feed data to pandas, and interact with databases. This third edition is a complete learning experience that will help you become a bona fide Python programmer in no time. What's so special about this book? If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. With this book, you'll learn Python through a multisensory experience that engages your mind--rather than a text-heavy approach that puts you to sleep


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Nghiên cứu và thử nghiệm thuật toán phân cụm K-means / Đỗ Thùy Dương. // Kỷ yếu hội thảo khoa học giáo viên Khoa Công nghệ thông tin 5/2020
Hà Nội : Đại học Hà Nội, 2020
tr. 36-41

Bài báo cáo này đưa ra các bước xây dựng thuật toán phân cụm K-means và sử dụng thư viện có sẵn scikit-learn để chạy thử nghiệm thuật toán, đưa ra các hạn chế và ưu điểm của thuật toán này.

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Python for Everybody : Exploring Data in Python 3 / Charles Severance
Michigan : Ann Arbor, [2013]
[200] p. : ill. ; 29 cm.

I never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning.The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning. Chapters 2-10 are similar to the Think Python book, but there have been major changes. Number-oriented examples and exercises have been replaced with data- oriented exercises. Topics are presented in the order needed to build increasingly sophisticated data analysis solutions. Some topics like try and except are pulled forward and presented as part of the chapter on conditionals. Functions are given very light treatment until they are needed to handle program complexity rather than introduced as an early lesson in abstraction. Nearly all user-defined functions have been removed from the example code and exercises outside of Chapter 4. The word "recursion"1 does not appear in the book at all. In chapters 1 and 11-16, all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming, using web services, parsing XML and JSON data, creating and using databases using Structured Query Language, and visualizing data. The ultimate goal of all of these changes is a shift from a Computer Science to an Informatics focus is to only include topics into a first technology class that can be useful even if one chooses not to become a professional programmer


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Python for kids for dummies / Brendan Scott.
Hoboken, NJ : John Wiley & Sons, Inc., 2015
315 p. ; : color ill. ; 23 cm.

Coding experts point to Python as one of the best languages to start with when you're learning coding. It's been a popular choice for schools and code camps who want to introduce coding to a younger audience. Python For Kids For Dummies helps teach the basics of coding and Python to kids who don't have the opportunity to take coding classes at school or in camp as well as those who simply prefer to learn on their own.

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Ứng dụng học máy xây dựng module giải bài toán dự đoán giá bất động sản / Đỗ Thùy Dương. // Kỷ yếu hội thảo khoa học giáo viên Khoa Công nghệ thông tin 5/2020
Hà Nội : Đại học Hà Nội, 2020
tr. 28-35

Bài báo cáo này đưa ra phương pháp tiếp cận bài toán dự đoán giá bất động sản, thông qua học máy, xây dựng mô đun tính toán, cực tiểu hàm lỗi.