Іноді нема часу читати купу листів, що надходять на пошту Gmail, тому створив для Python Gmail-reader, який дивиться всі листи і шукає потрібні речі – посилання, найбільш уживані слова або ж розпізнає і візуалізує вміст:
Позначка: python

Python PDF-and-URL-parser
Python PDF-and-URL-parser
Назбирав на комп’ютері уже кілька тисяч PDF файлів – статті та книги з програмування. Так само зібрав тисячі посилань на сайти. Тому вирішив об’єднати все в одну таблицю csv і написав для цього такий код – https://github.com/skupriienko/PDF-and-URL-parser
Мені б раніше таку штуку, коли ще писав дисертацію… 🙂

Create my Awesome Python Learning list
Create my Awesome Python Learning list in a table view (by Airtable) with 1070 links – https://airtable.com/shrNtoOfPJVDcO3fG/tblAYr9pYzqpWhYJ0(mostly in English, Russian and Ukrainian languages):
– Articles about Software Engineering
– Books
– Developer’s Tools
– Games for Education
– Jobs
– Math
– MOOC and courses
– Project examples for Junior
– Roadmaps
– Textbooks
– Training
– Video
A month when I learned 44 Python’s online courses
The most training month when I learned 44 Python’s online courses (in DataCamp and LinkedIn Learning. Here is the list of completed courses:
1. Building Chatbots in Python(DataCamp)
2. Building RESTful APIs with Flask(LinkedIn Learning)
3. Building RESTful Web APIs with Django(LinkedIn Learning)
4. Building a Paid Membership Site with Django(LinkedIn Learning)
5. Case Study: School Budgeting with Machine Learning in Python(DataCamp)
6. Data Science for Everyone Track(DataCamp)
7. Data Scientist with Python Track(DataCamp)
8. Dealing with Missing Data in Python(DataCamp)
9. Docker for Data Scientists(LinkedIn Learning)
10. Flask Essential Training(LinkedIn Learning)
11. Full Stack Web Development with Flask(LinkedIn Learning)
12. Functional Programming with Python(LinkedIn Learning)
13. Intermediate Data Visualization with Seaborn(Datacamp)
14. Introducing Jupyter(LinkedIn Learning)
15. Introduction to Bash Scripting(DataCamp)
16. Introduction to Deep Learning in Python(DataCamp)
17. Introduction to Deep Learning with OpenCV(LinkedIn Learning)
18. Introduction to Git(DataCamp)
19. Introduction to Natural Language Processing in Python(DataCamp)
20. Introduction to Network Analysis in Python(DataCamp)
21. Learning Django(LinkedIn Learning)
22. Linear Classiers in Python(DataCamp)
23. Machine Learning Fundamentals with Python Track(DataCamp)
24. Machine Learning with Tree-Based Models in Python(DataCamp)
25. Nail Your Python Interview(LinkedIn Learning)
26. Neural Networks and Convolutional Neural Networks Essential Training(LinkedIn Learning)
27. Next Step Python: Decorators(LinkedIn Learning)
28. Processing Text with Python Essential Training(LinkedIn Learning)
29. Python Code Challenges(LinkedIn Learning)
30. Python Data Structures: Dictionaries(LinkedIn Learning)
31. Python Essential Libraries(LinkedIn Learning)
32. Python Toolbox Track(DataCamp)
33. Python for Data Science Tips, Tricks, & Techniques(LinkedIn Learning)
34. Python for Data Visualization(LinkedIn Learning)
35. Python: Data Analysis (2015)(LinkedIn Learning)
36. Python: XML, JSON, and the Web(LinkedIn Learning)
37. Secure Coding in Python(LinkedIn Learning)
38. Sentiment Analysis in Python(DataCamp)
39. Statistical Thinking in Python (Part 2)(DataCamp)
40. Text Analytics and Predictions with Python Essential Training(LinkedIn Learning)
41. Unsupervised Learning in Python(DataCamp)
42. Using Python for Automation(LinkedIn Learning)
43. Using Python with Excel(LinkedIn Learning)
44. pandas Essential Training(LinkedIn Learning)

Awesome Python Learning
# Awesome-Python-Learning
Python Learning Library
## Contents
Jobs
Programming (learning)
Roadmaps
MOOC and courses
Video
Textbooks
Books
Games for Education
Online education (others)
IT-events
Training
Project examples for Junior
Puzzles
Developer’s Tools
Articles about Software Engineering
Jobs
- [15 App Ideas to Build and Level Up your Coding Skills]
- [15 вопросов по Python: как джуниору пройти собеседование]
- [15 задач на собеседовании для программиста]
- [16-річний програміст із Черкащини — про те, як 11-класником влаштувався на роботу зі зарплатнею майже $1000 | DOU]
- [5 советов по созданию вашего резюме]
- [50+ Data Structure and Algorithms Problems from Coding Interviews – DEV Community 👩💻👨💻]
- [53 Python Interview Questions and Answers – Towards Data Science]
- [hh.ua]
- [How to write a killer Software Engineering résumé – freeCodeCamp.org – Medium]
- [Job search, venture investing & new tech products | AngelList]
- [Python програмісти – Джин]
- [Top 100 Data Structure and Algorithm Interview Questions for Java Programmers | Java67]
- [Top 75 Programming Interview Questions Answers to Crack Any Coding Job Interview | Java67]
- [What I want (and don’t want) to see on your software engineering resume]
- [Вакансії | DOU]
- [Вастрик.Инсайд #39: Войти в айти. Нужен ли диплом? Как учиться новому? Как оставаться востребованным? Есть ли жизнь после 30?]
- [Вастрик.Инсайд #46: Краткий гайд о том, как нанимать нормальных людей]
- [Де, як і скільки: аналізуємо найм джуніорів у 2019 році | DOU]
- [Как должно выглядеть резюме ИТ-специалиста: типичные ошибки глазами HR]
- [Как успешно пройти любое техническое собеседование]
- [Работа]
Programming (learning)
Roadmaps
- [My Data Science & Machine Learning, Beginner’s Learning Path | LinkedIn]
- [AI & ML дайджест #17: курсы по ML & DL, обзор популярных GAN архитектур, AI бот для ребенка | DOU]
- [Data Science Career Guide — Dataquest]
- [Data Science Career Tips Archives — Dataquest]
- [Full-Stack JavaScript in Six Weeks: A Curriculum Guide]
- [Grow]
- [Grow]
- [How to become a data scientist? – Towards Data Science]
- [How we built our first full-stack JavaScript web app in three weeks]
- [If I had to start learning Data Science again, how would I do it?]
- [omreps/programmer-competency-matrix: ENG -> RU: Матрица компетентности программиста, мой перевод]
- [Pandas Урок — чтение файлов csv, создание dataframe и фильтрация данных]
- [Programmer Competency Matrix — Sijin Joseph]
- [programmer-competency-matrix/partII.md at master · omreps/programmer-competency-matrix]
- [Python Developers Survey 2019 Results | JetBrains: Developer Tools for Professionals and Teams]
- [Quiz: Data Engineer, Data Analyst, Data Scientist — Which Role Fits You?]
- [Resources I Wish I Knew When I Started Out With Data Science]
- [Roadmap • mlcourse.ai]
- [Top 10 In-Demand programming languages to learn in 2020]
- [Warning: Your programming career – SoloLearn – Medium]
- [Дайджест материалов по трудоустройству в сфере IT]
- [Детальный план самообразования в Computer Science за 1.5 года]
- [Мапа розвитку в Data Science, або Як стати дослідником даних | DOU]
- [Программирование на Python: от новичка до профессионала]
- [Путь Python Junior-а в 2017]
- [Развивать себя]
- [Советы сеньоров: как прокачать знания junior Front-end/JavaScript | DOU]
- [Хочу стать веб-разработчиком: подробный план по изучению JavaScript]
MOOC and courses
- [[UNИX][Python-Dev] Лекция 1. Разработка ПО. Индивидуальное использование GIT – YouTube]
- [11.1 – Regular Expressions – Мичиганский университет | Coursera]
- [200+ SQL Interview Questions and Answers for Developers | Udemy]
- [6.006: Introduction to Algorithms – Massachusetts Institute of Technology]
- [Advanced Operating Systems]
- [AI For Everyone — главная | Coursera]
- [Algorithmic Toolbox | Coursera]
- [Amazon Web Services Sign-In]
- [An Introduction to Interactive Programming in Python (Part 1) – Rice University | Coursera]
- [An Introduction to Interactive Programming in Python (Part 1) — главная | Coursera]
- [AP®︎ Computer Science Principles (AP®︎ CSP) | Khan Academy]
- [App Maker Academy | LEARN]
- [Applied Machine Learning in Python — главная | Coursera]
- [Applied Machine Learning in Python | Coursera]
- [Applied Plotting, Charting & Data Representation in Python | Coursera]
- [Applied Plotting, Charting & Data Representation in Python | Coursera]
- [Applied Social Network Analysis in Python | Coursera]
- [Applied Text Mining in Python | Coursera]
- [Applied Text Mining in Python | Coursera]
- [Artificial Intelligence]
- [Artificial Intelligence for Robotics | Udacity]
- [Basics of Software Architecture & Design Patterns in Java | Udemy]
- [Become a Python Developer]
- [Become a Solution Architect: Architecture Course | Udemy]
- [Big Data Analytics in Healthcare]
- [Bootcamp – Scrimba Tutorial]
- [Bootstrap 4 Tutorial – Learn Bootstrap For Free | Scrimba]
- [Break Away: Programming And Coding Interviews | Udemy]
- [Caesar – CS50x]
- [Chat with React – Scrimba Tutorial]
- [Clean Code | LEARN]
- [Client-Server Communication]
- [Code Basics: основы программирования]
- [Codecademy]
- [CodeSkulptor]
- [Coding for Kids | Tynker]
- [Coding Interview Bootcamp Algorithms, Data Structures Course | Udemy]
- [Command Line Essentials: Git Bash for Windows | Udemy]
- [Computability, Complexity & Algorithms]
- [Computability, Complexity & Algorithms – Udacity]
- [Computer programming | Computing | Khan Academy]
- [Computer science | Computing | Khan Academy]
- [Continuous Integration and Continuous Delivery using Interactive Browser-Based Labs | Katacoda]
- [Continuous Integration with Jenkins | LEARN]
- [Convolutional Neural Networks | Coursera]
- [Course | 15.071x | edX]
- [Course | CS1301xII | edX]
- [Course Introduction: Neural Networks in JavaScript – Scrimba Tutorial]
- [Course overview]
- [Course Overview – Scrimba Tutorial]
- [Courses | edX]
- [Courses | LEARN]
- [Crash Course on Python — главная | Coursera]
- [CS 436: Distributed Computer Systems – Lecture 1 – YouTube]
- [CSS – Scrimba Tutorial]
- [Dashboard | Khan Academy]
- [Data Analysis and Visualization]
- [Data Analysis Learning Path | Springboard]
- [Data Science A-Z™: Real-Life Data Science Exercises Included | Udemy]
- [Data Science Dream Job – YouTube]
- [Data Science Interview Prep]
- [Data Science Office Hours – YouTube]
- [Data Science with R | Pluralsight]
- [Data Scientist Path: Interactive Python, SQL | Dataquest]
- [Data Structure – Part I | Udemy]
- [Data Structures and Performance | Coursera]
- [Data Structures Fundamentals]
- [Data Visualization in Python — DataCamp]
- [Data Wrangling with MongoDB]
- [Database Systems Concepts & Design]
- [DataCamp]
- [Datatypes & Typecasting – Scrimba Tutorial]
- [DBA1 : Компания Postgres Professional]
- [DBA2 : Компания Postgres Professional]
- [Deep learning на пальцах!]
- [Design of Computer Programs]
- [Design of Computer Programs – Udacity]
- [Designing RESTful APIs]
- [Developing AI Applications on Azure — главная | Coursera]
- [Differential Equations in Action]
- [Divide and Conquer, Sorting and Searching, and Randomized Algorithms | Coursera]
- [DJANGO CHANNELS 2 Tutorial (V2) – Real Time – WebSockets – Async – YouTube]
- [Docker Swarm Mode Playground | Katacoda]
- [DZone: Programming & DevOps news, tutorials & tools]
- [Easy to Advanced Data Structures | Udemy]
- [Easy to Advanced Data Structures | Udemy]
- [Exercise files]
- [Exercises on the Python Track | Exercism]
- [Explore – LeetCode]
- [Free Clean Architecture Course: Patterns, Practices, and Principles for Beginners | Pluralsight]
- [Free Software Architect Course: Developer to Architect | Pluralsight]
- [Free SOLID Course: Principles of Object Oriented Design | Pluralsight]
- [Front Matter — Alembic 1.4.2 documentation]
- [Front-End Web UI Frameworks and Tools: Bootstrap 4 — главная | Coursera]
- [Full Stack Foundations]
- [Git Playground | Katacoda]
- [Git Started with GitHub | Udemy]
- [Graph Search, Shortest Paths, and Data Structures — главная | Coursera]
- [Graph Search, Shortest Paths, and Data Structures | Coursera]
- [Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming | Coursera]
- [Grok Learning]
- [Grokking the System Design Interview – Learn Interactively]
- [GT – Refresher – Advanced OS]
- [Harvard CS109 Data Science Course, Resources Free and Online]
- [High Performance Computer Architecture]
- [High Performance Computing]
- [HTTP & Web Servers]
- [HTTP & Web Servers – Udacity]
- [https://scratch.mit.edu/projects/374672500/editor]
- [Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization | Coursera]
- [Inferential Statistical Analysis with Python — главная | Coursera]
- [Input and output — Intro to Interviewing — Grasshopper]
- [Intel® Edge AI Fundamentals with OpenVINO™]
- [Intro to Algorithms – Udacity]
- [Intro to Algorithms | Udacity]
- [Intro to Artificial Intelligence – Udacity]
- [Intro to Backend – Udacity]
- [Intro to Data Analysis | Udacity]
- [Intro to Data Science]
- [Intro to Data Science]
- [Intro to Data Structures and Algorithms]
- [Intro to Deep Learning with PyTorch]
- [Intro to Descriptive Statistics]
- [Intro to DevOps]
- [Intro To Dynamic Programming – Coding Interview Preparation | Udemy]
- [Intro To Dynamic Programming – Coding Interview Preparation | Udemy]
- [Intro to Flask Series – YouTube]
- [Intro to Hadoop and MapReduce]
- [Intro to Inferential Statistics]
- [Intro to Progressive Web Apps]
- [Intro to Relational Databases]
- [Intro to the Design of Everyday Things]
- [Intro to Theoretical Computer Science]
- [Introduction – Scrimba Tutorial]
- [Introduction to Computational Thinking and Data Science | edX]
- [Introduction to Computer Vision]
- [Introduction to D3 – Scrimba Tutorial]
- [Introduction to Data Science in Python | Coursera]
- [Introduction to Data Science in Python | Coursera]
- [Introduction to Dynamical Systems and Chaos]
- [Introduction to Graduate Algorithms]
- [Introduction to GraphQL | GraphQL]
- [Introduction to JavaScript | Codecademy]
- [Introduction to Machine Learning – Online Course | DataCamp]
- [Introduction to Machine Learning Course | Udacity]
- [Introduction to Operating Systems]
- [Introduction to Operating Systems – Udacity]
- [Introduction to Python Programming – Udacity]
- [Introduction to Python Programming | Udacity]
- [Introduction To Python Programming | Udemy]
- [Introduction to Scripting in Python | Coursera]
- [IT Курсы программирования онлайн – обучение программированию, видео уроки | ITVDN]
- [JavaScript ES6 Intro – Scrimba Tutorial]
- [Kaggle Mercedes и кросс-валидация / Блог компании Open Data Science / Хабр]
- [Katacoda – Interactive Learning Platform for Software Engineers]
- [Katacoda – Interactive Learning Platform for Software Engineers]
- [Khan Academy | Free Online Courses, Lessons & Practice]
- [Knowledge-Based AI: Cognitive Systems]
- [Learn | freeCodeCamp.org]
- [Learn CI/CD with Jenkins using Interactive Browser-Based Labs | Katacoda]
- [Learn CSS Animations]
- [Learn Data Analysis using Pandas and Python (Module 2/3) | Udemy]
- [Learn Data Structures and Algorithms: Ace the Coding Interview | Udemy]
- [Learn Data Visualization Tutorials | Kaggle]
- [Learn Git Version Control using Interactive Browser-Based Labs | Katacoda]
- [Learn How to Code | Codecademy]
- [Learn Intermediate Machine Learning Tutorials | Kaggle]
- [Learn Intro to Machine Learning Tutorials | Kaggle]
- [Learn Kubernetes using Interactive Browser-Based Labs | Katacoda]
- [Learn Machine Learning using Interactive Browser-Based Labs | Katacoda]
- [Learn Pandas Tutorials | Kaggle]
- [Learn Python – Full Course for Beginners [Tutorial] – YouTube]
- [Learn Python 3.6 for Total Beginners | Udemy]
- [Learn Python for Data Science, Structures, Algorithms, Interviews | Udemy]
- [Learn Python for Data Structures, Algorithms & Interviews | Udemy]
- [Learn Python: Build a Virtual Assistant | Udemy]
- [Learn Serverless and Functions/FaaS Technologies using Interactive Browser-Based Labs | Katacoda]
- [Learn SQL | Codecademy]
- [Learn to Code with Interactive Tutorials | Scrimba]
- [Learn to Program: Crafting Quality Code — главная | Coursera]
- [Learn to Program: The Fundamentals — главная | Coursera]
- [Lecture 1: Administrivia; Introduction; Analysis of Algorithms, Insertion Sort, Mergesort | Video Lectures | Introduction to Algorithms (SMA 5503) | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Linear Algebra Refresher Course]
- [Livestreams | Codecademy]
- [Machine Learning]
- [Machine Learning A-Z (Python & R in Data Science Course) | Udemy]
- [Machine Learning Course Outline | Course Outline | CSMM.102x Courseware | edX]
- [Machine Learning Foundations: A Case Study Approach | Coursera]
- [Machine Learning in Python (Data Science and Deep Learning) | Udemy]
- [Machine Learning Interview Preparation]
- [Machine Learning with TensorFlow on Google Cloud Platform | Coursera]
- [Machine Learning: Unsupervised Learning]
- [Master Object Oriented Programming Concepts | Udemy]
- [Master Python for Data Science]
- [Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Microsoft: Our new free Python programming language courses are for novice AI developers | ZDNet]
- [MIT 6.042J Mathematics for Computer Science]
- [Neural Networks and Deep Learning — главная | Coursera]
- [Node.js Playground | Katacoda]
- [Nonlinear Dynamics: Mathematical and Computational Approaches]
- [Open Data Science (ODS.ai)]
- [Open Data Science (ODS.ai)]
- [Open Machine Learning Course mlcourse.ai • mlcourse.ai]
- [ossu/computer-science: Path to a free self-taught education in Computer Science!]
- [Practical Deep Learning for Coders, v3 | fast.ai course v3]
- [Probabilistic Graphical Models 1: Representation | Coursera]
- [Programming Languages]
- [PY4E – Python for Everybody]
- [Python – OOP | Udemy]
- [Python – YouTube]
- [Python | CoderNet]
- [Python 3, BBC Microbit, and MicroPython Bootcamp | Udemy]
- [Python 3.4 Programming Tutorials – YouTube]
- [Python Basics — главная | Coursera]
- [Python for Big Data Analytics – Edureka]
- [Python for Data Science | edX]
- [Python for Data Science | edX]
- [Python OOP : Four Pillars of OOP in Python 3 for Beginners | Udemy]
- [Python OOP : Four Pillars of OOP in Python 3 for Beginners | Udemy]
- [Python Playground | Katacoda]
- [Python Programming – Build a Reconnaissance Scanner | Udemy]
- [Python Programming – YouTube]
- [Python Programming for Beginners – Learn in 100 Easy Steps | Udemy]
- [Python Programming: A Concise Introduction — главная | Coursera]
- [Python Track | Exercism]
- [Python Tutorials – YouTube]
- [Python Variables]
- [Python: Object Oriented Programming | Udemy]
- [python: Online Courses, Training and Tutorials on LinkedIn Learning]
- [Quickstart for Cloud SQL for PostgreSQL | Google Cloud]
- [R Language Playground | Katacoda]
- [React – Scrimba Tutorial]
- [React & Django TUTORIAL Integration // REACTify Django – YouTube]
- [React Tutorial: Learn React JS For Free | Scrimba]
- [Reading: Welcome | Welcome | ALGS201x Courseware | edX]
- [Real-Time Analytics with Apache Storm]
- [Regular Expressions Intro – Scrimba Tutorial]
- [Responsive Images]
- [Rock Paper Scissors – Python Tutorial | Udemy]
- [RPA: Automation Anywhere: Example: Ticket Processing – YouTube]
- [Scalable Microservices with Kubernetes]
- [Scipy Lecture Notes — Scipy lecture notes]
- [Self-Driving Fundamentals: Featuring Apollo]
- [Sequence Models | Coursera]
- [Shortest Paths Revisited, NP-Complete Problems and What To Do About Them | Coursera]
- [Software Architecture & Design]
- [Software Development Methodologies | LEARN]
- [Software Development Processes and Methodologies | Coursera]
- [Software Testing Introduction (RUS) | LEARN]
- [Spark]
- [SQL for Data Analysis | Udacity]
- [Stanford Engineering Everywhere | CS229 – Machine Learning]
- [Story by Data – YouTube]
- [Structuring Machine Learning Projects | Coursera]
- [TensorFlow Getting Started using Interactive Browser-Based Labs | Katacoda]
- [Textbook | Calculus Online Textbook | MIT OpenCourseWare]
- [The Bits and Bytes of Computer Networking | Coursera]
- [The Ultimate GIT 5-day Challenge | Udemy]
- [Tick Tock, Tick Tock — Етап 9 — Stepik]
- [Top Coding Interview Questions (Essential to Getting Hired) | Udemy]
- [Try Django 1.11 // Python Web Development | Udemy]
- [Try DJANGO Tutorial Series – YouTube]
- [Try DJANGO TUTORIAL Series (v2.2) // PYTHON Web Development with Django version 2.2 – YouTube]
- [TypeScript: Introduction – Scrimba Tutorial]
- [Ubuntu Playground | Katacoda]
- [UI design – Scrimba Tutorial]
- [Using Databases with Python | Coursera]
- [Version Control with Git]
- [Video | Version control with Git | VCG Courseware | LEARN]
- [Video Lectures | Introduction to Algorithms (SMA 5503) | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Video Lectures | Introduction to Computer Science and Programming | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Video Lectures | Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Visual Studio Code Playground | vscode | Katacoda]
- [Web Application & Software Architecture 101 – Learn Interactively]
- [Web Design, Business, Technology Classes and Immersives | General Assembly]
- [Web Tooling & Automation]
- [WebDriver | LEARN]
- [Web-Services Introduction | LEARN]
- [Website Performance Optimization]
- [Week 2 | Week 2 | CS50 Courseware | edX]
- [Welcome 👋 to Vue.js! – Scrimba Tutorial]
- [Алгоритмы | Coursera]
- [Алгоритмы на Python 3. Лекция №1 – YouTube]
- [Алгоритмы, часть I | Coursera]
- [Алгоритмы, часть I | Coursera]
- [Алгоритмы, часть II | Coursera]
- [Алгоритмы, часть II | Coursera]
- [Алексей Савватеев ” Математический анализ. Анонс” – YouTube]
- [Аналіз даних та статистичне виведення на мові R | Prometheus]
- [Бесплатное учебное руководство по теме “NumPy” — Deep Learning Prerequisites: The Numpy Stack in Python | Udemy]
- [Бесплатное учебное руководство по теме “Python” — Learn Python 3.6 for Total Beginners | Udemy]
- [Введение в математическое мышление | Coursera]
- [Введение в математическое мышление | Coursera]
- [Введение в науку о данных | Coursera]
- [Введение в программирование с MATLAB | Coursera]
- [Візуалізація даних | Prometheus]
- [Высшая математика для заочников и не только]
- [Глубокое обучение | Coursera]
- [Глубокое обучение | Coursera]
- [Интерактивные курсы — HTML Academy]
- [Інформація про курс CS50 | Prometheus]
- [Ключевые аспекты разработки на Python – Курсы по программированию]
- [Корисні ресурси для програміста (оновив 11 травня 2020) | DOU]
- [Курсы по программированию]
- [Машинне навчання | Prometheus]
- [Машинное обучение | Coursera]
- [Машинное обучение | Coursera]
- [Машинное обучение | Coursera]
- [Машинное обучение для людей :: Разбираемся простыми словами :: Блог Вастрик.ру]
- [Начало]
- [Нейронные сети и глубокое обучение | Coursera]
- [Онлайн-курсы — когда угодно, где угодно | Udemy]
- [Онлайн-курсы Computer Science Center]
- [Основи програмування CS50 2019 | Prometheus]
- [Основы React.js]
- [Основы компьютерных вычислений | Coursera]
- [Открытый курс машинного обучения. Тема 1. Первичный анализ данных с Pandas / Блог компании Open Data Science / Хабр]
- [Открытый курс машинного обучения. Тема 2: Визуализация данных c Python / Блог компании Open Data Science / Хабр]
- [Открытый курс машинного обучения. Тема 3. Классификация, деревья решений и метод ближайших соседей / Open Data Science corporate blog / Habr]
- [Открытый курс машинного обучения. Тема 3. Классификация, деревья решений и метод ближайших соседей / Блог компании Open Data Science / Хабр]
- [Панель курсів | Prometheus]
- [Практическое компьютерное обучение | Coursera]
- [Прикладная наука о данных с Python | Coursera]
- [Программирование мобильных приложений для портативных систем на базе Android: Часть 1 | Coursera]
- [Программирование мобильных приложений для портативных систем на базе Android: Часть 2 | Coursera]
- [Программирование на Python | Coursera]
- [Профессиональная сертификация ‘Google IT Automation with Python’ | Coursera]
- [Разведочный анализ данных | Coursera]
- [Разработка и проектирование адаптивных веб-сайтов | Coursera]
- [Розробка та аналіз алгоритмів. Частина 1 | Prometheus]
- [Скринкаст по Angular]
- [Скринкаст по Gulp]
- [Скринкаст по Node.JS]
- [Скринкаст по Webpack]
- [Современный учебник JavaScript]
- [Структуры данных в Python | Coursera]
- [Структуры и алгоритмы данных | Coursera]
- [Теория вероятностей для начинающих | Coursera]
- [Теория игр | Coursera]
- [Уроки по Python для начинающих и программистов ~ PythonRu]
- [Учимся программировать: основы | Coursera]
- [Функции – Московский физико-технический институт, Mail.Ru Group & ФРОО | Coursera]
- [Язык программирования JavaScript]
- [🤖 Интерактивные эксперименты с машинным обучением на TensorFlow | DOU]
Video
- [6.824 Lecture 1 – YouTube]
- [62 лучших видео для тех, кто хочет углубить знания в JavaScript]
- [AlSweigart – Twitch]
- [Berkeley AI Materials]
- [Build a Data Analysis Library from Scratch in Python – YouTube]
- [Building a keylogger using Python + Pynput – YouTube]
- [Compilers with Alex Aiken – YouTube]
- [Computer Science 162 (Fall 2010) – Lecture 1 – YouTube]
- [Computer Science 61A, 001 – Spring 2011 : Free Movies : Free Download, Borrow and Streaming : Internet Archive]
- [CS144 Fall 2013, Video 4-0: Congestion Control – YouTube]
- [Essence of linear algebra – YouTube]
- [Git – Lecture 0 – CS50’s Web Programming with Python and JavaScript – YouTube]
- [Golovach Courses – YouTube]
- [L01 Functional Programming | UC Berkeley CS 61A, Spring 2010 – YouTube]
- [Steven Skiena – Algorithms]
- [Tech Debates Webinar | Ruby vs Python – Zoom]
- [UC Berkeley CS professor Brian Harvey]
- [UCBerkeley Course Computer Science 186 : Free Download, Borrow, and Streaming : Internet Archive]
- [Video Lectures | Structure and Interpretation of Computer Programs | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Изучение программирования. SQL – YouTube]
- [Лучшие Youtube-каналы для Frontend-разработчика]
- [Лучший видеокурс по сетевым технологиям]
- [Огромный видеокурс по основам JavaScript от freeCodeCamp]
Textbooks
- [100 days of algorithms — Medium]
- [30 Helpful Python Snippets That You Can Learn in 30 Seconds or Less]
- [97-things-every-programmer-should-know/ru/thing_01 at master · 97-things/97-things-every-programmer-should-know]
- [All the basics of Python classes – Level Up Coding]
- [BeginnersGuide/Programmers – Python Wiki]
- [Calculating Streaks in Pandas]
- [Cheat Sheet – Google Таблиці]
- [Cheat Sheet of Machine Learning and Python (and Math) Cheat Sheets]
- [Deep Learning]
- [DevDocs API Documentation]
- [DZone Big Data]
- [Front-end Developer Handbook 2019 – Learn the entire JavaScript, CSS and HTML development practice!]
- [Google’s Python Class | Python Education | Google Developers]
- [Learn DS & Algorithms | Programiz]
- [List of Keywords in Python Programming]
- [Manning | Catalog]
- [Manning | Deep Learning with Python, Second Edition]
- [Manning | Get Programming]
- [Manning | liveBook]
- [Manning | Making Sense of Edge Computing]
- [Manning | The Quick Python Book, Third Edition]
- [MLOps: Continuous delivery and automation pipelines in machine learning]
- [NumPy Tutorial: Data Analysis with Python — Dataquest]
- [Python – Все для студента]
- [Python | CoderNet]
- [Python 3 для начинающих и чайников – уроки программирования]
- [Python Pandas Tutorial – Tutorialspoint]
- [Python Tricks 101🐍 – HackerNoon.com – Medium]
- [Python Tutorial | Learn Python For Data Science]
- [Python Tutorial for Beginners: Learn Python Programming in 7 Days]
- [Python на Хабре / Хабр]
- [Python/Учебник Python 3.1 — Викиучебник]
- [Scipy Tutorial: Vectors and Arrays (Linear Algebra) – DataCamp]
- [skromnitsky/awesome: 😎 Awesome lists about all kinds of interesting topics]
- [Stencil Computations with Numba — Dask Examples documentation]
- [The Ultimate Guide to Python: How to Go From Beginner to Pro]
- [Tutorials – Online Data Analysis & Interpretation | DataCamp]
- [www.ПЕРВЫЕ ШАГИ.ru :: Шаг 38 – PL/SQL – вводный курс]
- [Вычислительная Фотография :: Будущее фотографии — это код :: Блог Вастрик.ру]
- [Добавляем параллельные вычисления в Pandas / Хабр]
- [Инструменты Python: лучшая шпаргалка для начинающих]
- [Нескучный туториал по NumPy / Хабр]
- [Оглавление — Problem Solving with Algorithms and Data Structures]
- [Основы языка программирования Python за 10 минут / Хабр]
- [Программирование на языке PL/SQL под базы данных Oracle]
- [Руководство Oracle PL/SQL]
- [Содержание E:\DEV\Programming\]
- [Сохраните в закладках эту статью, если вы новичок в Python (особенно если изучаете Python сами) / Хабр]
Books
- [10 лучших книг по программированию по мнению Reddit]
- [15 лучших книг по программированию на Python – Kompot Journal]
- [3 лучших книги по объектно-ориентированному программированию]
- [3 лучших книги по объектно-ориентированному программированию]
- [5 отличных англоязычных книг по теоретическому Computer Science]
- [6 бесплатных книг по алгоритмам в программировании]
- [6.042J Complete course notes]
- [8 книг по компьютерным сетям]
- [Architectural Styles and the Design of Network-based Software Architectures]
- [Build your first app | Android Developers]
- [Building Blocks for Theoretical Computer Science]
- [Computer Networking: a Top Down Approach]
- [Data-Oriented Design]
- [Distributed Systems: Principles and Paradigms]
- [Dive Into Python 3]
- [dmitryrubtsov/Python-for-Data-Science: Education]
- [Domain Driven Design Quickly]
- [Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.]
- [Eloquent JavaScript]
- [holoviz/hvplot: A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews]
- [How to Design Programs]
- [How to not get caught while web scraping? – Data Driven Investor – Medium]
- [HTML5 и CSS3. Веб-разработка по стандартам нового поколения – Хоган Брайан – Google Книги]
- [Introduction – Выразительный Javascript]
- [Introduction to Computing: Explorations in Language, Logic, and Machines]
- [Introduction to Linear Algebra, 5th Edition]
- [Introduction to Programming in Java · Computer Science]
- [JQuery]
- [Learn Python – Free Interactive Python Tutorial]
- [Learn Python in Y Minutes]
- [Learn Python the Hard Way]
- [Python Documentation contents — Python 3.8.2 documentation]
- [R Tutorial for Beginners: Learning R Programming]
- [Springer has released 65 Machine Learning and Data books for free]
- [Teach Yourself Computer Science]
- [The Functional Art: An Introduction to Information Graphics and Visualization: The Functional Art]
- [The HoTT Book | Homotopy Type Theory]
- [The Python Standard Library — Python 3.8.2 documentation]
- [TheoryOfComputation.dvi]
- [Think Python]
- [tr22.pdf]
- [Tutorial – Learn Python in 10 minutes – Stavros’ Stuff]
- [Tutorials — pandas 1.0.3 documentation]
- [unmaintainable code : Java Glossary]
- [You-Dont-Know-JS/README.md at 2nd-ed · getify/You-Dont-Know-JS]
- [You-Dont-Know-JS/README.md at 2nd-ed · getify/You-Dont-Know-JS]
- [Большая книга веб-дизайна – Терри Фельке-Моррис – Google книги]
- [Каталог книг | VK]
- [Категория:Программирование — Википедия]
- [Книга «Python для сложных задач: наука о данных и машинное обучение» / Блог компании Издательский дом «Питер» / Хабр]
- [Лучший самоучитель по Java для начинающих и продвинутых]
- [Математические основы анализа данных: подборка материалов по вузовской математике]
- [Обложка — A Byte Of Python — русский перевод]
- [Оглавление — Problem Solving with Algorithms and Data Structures]
- [Перевод документации Python 3.x]
- [Помнить все: делимся лучшей шпаргалкой по Python]
- [Топ 10 самых популярных книг по программированию]
- [Учебник по NumPy – Визуализация примеров для быстрого изучения]
Games for Education
- [10 мобильных приложений, которые научат вас программировать]
- [12 бесплатных ресурсов для обучения программированию в игровой форме]
- [House Prices: Advanced Regression Techniques | Kaggle]
- [Learn Git Branching]
- [Play CodeCombat Levels – Learn Python, JavaScript, and HTML | CodeCombat]
- [The Python Challenge]
- [Titanic: Machine Learning from Disaster | Kaggle]
Online education (others)
- [arXiv.org e-Print archive]
- [Code Basics: основы программирования на Javascript]
- [CoderNet Портал для помощи программистам | CoderNet]
- [cs184/284a]
- [CS61C Spring 2015: Great Ideas in Computer Architecture (Machine Structures)]
- [Free JavaScript Course: Code School JavaScript Road Trip Part 1 | Pluralsight]
- [kanaka/mal: mal – Make a Lisp]
- [Learn Basic JavaScript: Declare JavaScript Variables | freeCodeCamp.org]
- [Machine Learning is Fun! – Adam Geitgey – Medium]
- [Machine Learning Mastery]
- [new fast.ai course: A Code-First Introduction to Natural Language Processing · fast.ai]
- [OOP Concept Tutorial in Java – Object Oriented Programming | Java67]
- [Operating Systems: Three Easy Pieces]
- [Programming — Towards Data Science]
- [PyVideo.org]
- [Skiena’s Audio Lectures]
- [Solve Easy Unpack – Py.CheckiO]
- [Web | Google Developers]
- [Why every Data Scientist should use Dask? – Towards Data Science]
- [Открытый курс машинного обучения. Тема 1. Первичный анализ данных с Pandas / Хабр]
- [Упражнения по SQL]
IT-events
Training
- [Day 0: Hello, World. | HackerRank]
- [Problems – LeetCode]
- [Skill Assessment]
- [Solve Python | HackerRank]
- [Solve Python | HackerRank]
Project examples for Junior
- [(1) Python]
- [10 Data Science Projects — Dataquest]
- [10 Great Programming Projects to Improve Your Resume and Learn to Program]
- [13 Project Ideas for Intermediate Python Developers — Real Python]
- [5 Cool Python Project Ideas For Inspiration | Hacker Noon]
- [6 Python Projects For Beginners | Codementor]
- [Building a Simple Chatbot from Scratch in Python (using NLTK)]
- [CodeProject – For those who code]
- [karan/Projects: A list of practical projects that anyone can solve in any programming language.]
- [latest Python project topics and ideas with source code for final year projects – kashipara]
- [Machine Learning Projects | Data Science Projects with Example]
- [Martyr2’s Mega Project Ideas List! – Share Your Project | Dream.In.Code]
- [Neural Network Embedding Recommendation System | Kaggle]
- [Python Project Ideas for Final Year, Python Project Help]
- [Top Python Projects | Easy, Intermediate And Advanced Python Projects | Edureka]
- [Tutorial 2 – Making it interesting — BeeWare 0.3.0 documentation]
Puzzles
- [About – Project Euler]
- [CodeKata]
- [Coderbyte | Code Screening, Challenges, & Interview Prep]
- [Problem set @ Timus Online Judge]
- [Programming Praxis | A collection of etudes, updated weekly, for the education and enjoyment of the savvy programmer]
- [The Daily WTF: Curious Perversions in Information Technology]
- [Задачи для программистов, ответы на задания различной сложности]
- [Мозговой фитнес. Актуальные задачи для прокачки программистских скиллов]
- [Решаем задачи на одномерные и двумерные массивы]
Developer’s Tools
- [(Tutorial) Web Scraping With Python: Beautiful Soup – DataCamp]
- [| fastai]
- [10 Best CSS Frameworks For Frontend Developers in 2020 – GeeksforGeeks]
- [10 лучших материалов для изучения Django]
- [20 short tutorials all data scientists should read (and practice) – Data Science Central]
- [7 Steps to Mastering Machine Learning With Python]
- [A Beginner’s Introduction to Python Web Frameworks : Python]
- [A successful Git branching model » nvie.com]
- [ageitgey/face_recognition: The world’s simplest facial recognition api for Python and the command line]
- [Algorithms – Algorithmia]
- [All Tools — PyViz 0.0.1 documentation]
- [An Intro to Git and GitHub for Beginners (Tutorial)]
- [Apache против Nginx: практические соображения]
- [ARCore – Google Developers]
- [Are you still using Pandas for big data? – Towards Data Science]
- [ArtVk & Bugtrack: Задачи по базам данных. Решение задач по SQL [1]]
- [Awesome Python | LibHunt]
- [awesome-vscode | 🎨 A curated list of delightful VS Code packages and resources.]
- [Azure Machine Learning SDK for Python – Azure Machine Learning Python | Microsoft Docs]
- [Batch convert images to PDF with Python by using Pillow or img2pdf | Solarian Programmer]
- [benfred/py-spy: Sampling profiler for Python programs]
- [Better Code Hub]
- [Big data sets available for free – Data Science Central]
- [Build and deploy your first machine learning web app]
- [Build and run a Python app in a container]
- [Building A Blog Application With Django | Django Central]
- [Building a Microservice in Python – Sonu Sharma – Medium]
- [Caffe | Installation]
- [CAL board – Agile board – Jira]
- [Catalog of Patterns of Enterprise Application Architecture]
- [Chapter 1. Getting to know Redis – Redis in Action]
- [Choosing the right estimator — scikit-learn 0.22.2 documentation]
- [CLI Setup – NativeScript Docs]
- [Cloud Shell]
- [Codacy Onboarding]
- [Codecov]
- [CodePen: Build, Test, and Discover Front-end Code.]
- [colorama · PyPI]
- [Conda Cheat Sheet – Kapeli]
- [Control Room | Home | Automation Anywhere]
- [Coveralls – Test Coverage History & Statistics]
- [CRAN – Package rattle]
- [create-graphql-server — instantly scaffold a GraphQL server]
- [Dash Bootstrap Components]
- [Dash for Beginners – DataCamp]
- [Dashboard : skromnitsky : PythonAnywhere]
- [Dashboard · WakaTime]
- [Dask + Numba for Efficient In-Memory Model Scoring – Capital One Tech – Medium]
- [Data Science with Python: Intro to Data Visualization with Matplotlib]
- [Data: Querying, Analyzing and Downloading: The GDELT Project]
- [Dataset Search]
- [Datasets for Data Mining and Data Science]
- [Django ORM. Добавим сахарку / Хабр]
- [Django в примерах · GitBook (Legacy)]
- [Django на русском]
- [Django Руководство часть 11: Разворачивание сайта на сервере – Изучение веб-разработки | MDN]
- [Download · Bootstrap]
- [Download All Free Textbooks from Springer using Python]
- [Download jQuery | jQuery]
- [Download RequireJS]
- [ekzhu/datasketch: MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble]
- [emmetio/emmet-atom: Emmet support for Atom]
- [Erotemic/ubelt: A Python utility belt containing simple tools, a stdlib like feel, and extra batteries. Hashing, Caching, Timing, Progress, and more made easy!]
- [Exploring your data with just 1 line of Python – Towards Data Science]
- [eyaltrabelsi/pandas-log: The goal of pandas-log is to provide feedback about basic pandas operations. It provides simple wrapper functions for the most common functions that add additional logs]
- [facebook/create-react-app: Set up a modern web app by running one command.]
- [facebookresearch/detectron2: Detectron2 is FAIR’s next-generation platform for object detection and segmentation.]
- [facebookresearch/DrQA: Reading Wikipedia to Answer Open-Domain Questions]
- [facebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors.]
- [facebookresearch/fastMRI: A large-scale dataset of both raw MRI measurements and clinical MRI images]
- [facebookresearch/habitat-api: A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.]
- [facebookresearch/LAMA: LAnguage Model Analysis]
- [facebookresearch/nevergrad: A Python toolbox for performing gradient-free optimization]
- [facebookresearch/pytext: A natural language modeling framework based on PyTorch]
- [facebookresearch/pytorch_GAN_zoo: A mix of GAN implementations including progressive growing]
- [facebookresearch/VideoPose3D: Efficient 3D human pose estimation in video using 2D keypoint trajectories]
- [facebookresearch/visdom: A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.]
- [facebookresearch/vizseq: An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.)]
- [Getting started — Flexx 1.0 documentation]
- [Getting started — HiPlot 0.1.9.post2 documentation]
- [Getting started — pandas 1.0.3 documentation]
- [Getting started — SciPy.org]
- [Getting started with Django | Django]
- [Getting started with PyMC3 — PyMC3 3.8 documentation]
- [github/hub: A command-line tool that makes git easier to use with GitHub.]
- [Graphene-Python]
- [great-expectations/great_expectations: Always know what to expect from your data.]
- [gto76/python-cheatsheet: Comprehensive Python Cheatsheet]
- [GUI (графический интерфейс пользователя) | Python 3 для начинающих и чайников]
- [GuiProgramming – Python Wiki]
- [Hello, App Center]
- [How to deploy ML models using Flask + Gunicorn + Nginx + Docker]
- [How to Get a Job with Python – Towards Data Science]
- [How to Install and Run Hadoop on Windows for Beginners – Data Science Central]
- [How to Update All Python Packages | ActiveState]
- [Installation — Kivy 1.11.1 documentation]
- [Installation — pyglet v1.5.0]
- [Integrating Summernote WYSIWYG Editor in Django | Django Central]
- [interpretml/interpret: Fit interpretable machine learning models. Explain blackbox machine learning.]
- [Introducing Bamboolib — a GUI for Pandas – Towards Data Science]
- [Introducing GitFlow]
- [ipinfo.io/json]
- [ironmussa/Optimus at develop-3.0]
- [japronto/1_hello.md at master · squeaky-pl/japronto]
- [jaybaird/python-bloomfilter: Scalable Bloom Filter implemented in Python]
- [jazzband/pip-tools: A set of tools to keep your pinned Python dependencies fresh.]
- [Jetware – aise / tensorflow18_keras21_python36_cpu_notebook – 180509 appliance]
- [jiffyclub/snakeviz: An in-browser Python profile viewer]
- [JS Bin – Collaborative JavaScript Debugging]
- [Keras Cheat Sheet: Neural Networks in Python – DataCamp]
- [keyboard-shortcuts-windows.pdf]
- [knockknock/README.md at master · huggingface/knockknock]
- [Laravel Nova – Beautifully-designed administration panel for Laravel]
- [localhost:54321/callback?code=b7e3a07c1695c5b58b6d]
- [Machine Learning]
- [main]
- [marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier]
- [MIT App Inventor 2]
- [More Itertools — more-itertools 8.2.0 documentation]
- [mouradmourafiq/pandas-summary: An extension to pandas dataframes describe function.]
- [Native mobile apps with Angular, Vue.js, TypeScript, JavaScript – NativeScript]
- [nicolaskruchten/pivottable: Open-source Javascript Pivot Table (aka Pivot Grid, Pivot Chart, Cross-Tab) implementation with drag’n’drop.]
- [NLTK Data]
- [NoSQL Databases List by Hosting Data – Updated 2020]
- [Numba: A High Performance Python Compiler]
- [Numpy and Scipy Documentation — Numpy and Scipy documentation]
- [NumPy в Python. Часть 1 / Хабр]
- [Optimus/README.md at master · ironmussa/Optimus]
- [Over 150 of the Best Machine Learning, NLP, and Python Tutorials I’ve Found]
- [Overview — Matplotlib 3.2.1 documentation]
- [Overview — NumPy v1.19.dev0 Manual]
- [PageSpeed Insights]
- [pallets/werkzeug: The comprehensive WSGI web application library.]
- [Pivot Demo From Local CSV]
- [PivotTable.js]
- [Plotting Google Sheets data in Python with Folium – Towards Data Science]
- [Plugin Status · WakaTime]
- [Polymer Project]
- [Popper – Tooltip & Popover Positioning Engine]
- [PostgreSQL : Документация : Компания Postgres Professional]
- [Prisma – Database tools for modern application development]
- [Projects – Home]
- [pydqc/README.md at master · SauceCat/pydqc]
- [PyQt5 book with a foreword by the creator of PyQt]
- [Pythia’s Documentation — Pythia 0.3 documentation]
- [Python 3.8 documentation — DevDocs]
- [Python Extension Packages for Windows – Christoph Gohlke]
- [Python Frameworks Comparison: How to Choose the Best for Web Development]
- [Python в три ручья: работаем с потоками (часть 1) | GeekBrains – образовательный портал]
- [pytorch3d/INSTALL.md at master · facebookresearch/pytorch3d]
- [Qt Designer Download for Windows and Mac]
- [Quick Start | GatsbyJS]
- [Quick Start · gulp.js]
- [Quickstart for Python/WSGI applications — uWSGI 2.0 documentation]
- [Quickstart tutorial — NumPy v1.19.dev0 Manual]
- [R Packages – RStudio]
- [RaRe-Technologies/bounter: Efficient Counter that uses a limited (bounded) amount of memory regardless of data size.]
- [React — JavaScript-бібліотека для створення користувацьких інтерфейсів]
- [Roundup of Python NLP Libraries – NLP-FOR-HACKERS]
- [samuelhwilliams/Eel: A little Python library for making simple Electron-like HTML/JS GUI apps]
- [SciPy — SciPy v1.4.1 Reference Guide]
- [SciPy.org — SciPy.org]
- [Settings | Account · WakaTime]
- [shaypal5/cachier: Persistent, stale-free, local and cross-machine caching for Python functions.]
- [sindresorhus/awesome: 😎 Awesome lists about all kinds of interesting topics]
- [skromnitsky/My_Projects]
- [Speech Recognition – Speech to Text in Python using Google API, Wit.AI, IBM, CMUSphinx]
- [Speed Up your Algorithms Part 2— Numba – Towards Data Science]
- [Speeding up your Algorithms Part 4— Dask – Towards Data Science]
- [Stop Worrying and Create your Deep Learning Server in 30 minutes]
- [streamlit/streamlit: Streamlit — The fastest way to build custom ML tools]
- [Superbird11/ranges: Continuous Range, RangeSet, and RangeDict data structures for Python]
- [The 30 Best Python Libraries and Packages for Beginners]
- [The Basics of Data Visualisation with Python – Towards Data Science]
- [The Big Bad NLP Database: Access Nearly 300 Datasets]
- [The Coolest Data Science And Machine Learning Tool Companies Of The 2020 Big Data 100]
- [The Most Underrated Python Packages – Towards Data Science]
- [The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks]
- [Tkinter. Программирование GUI на Python. Курс]
- [Top Python Libraries Used In Data Science – Towards Data Science]
- [tqdm/tqdm: A Fast, Extensible Progress Bar for Python and CLI]
- [Travis CI]
- [Travis CI – Test and Deploy with Confidence]
- [Turn Python Scripts into Beautiful ML Tools – Towards Data Science]
- [Tutorial — ZODB documentation]
- [Tutorial: Web Scraping in R with rvest — Dataquest]
- [ucg8j/awesome-dash: A curated list of awesome Dash (plotly) resources]
- [umdjs/umd: UMD (Universal Module Definition) patterns for JavaScript modules that work everywhere.]
- [Understanding the GitHub flow · GitHub Guides]
- [Untitled Diagram – diagrams.net]
- [Untitled Document – Creately]
- [Usage · s0md3v/XSStrike Wiki]
- [User’s Guide — Matplotlib 3.2.1 documentation]
- [vaexio/vaex: Out-of-Core DataFrames for Python, ML, visualize and explore big tabular data at a billion rows per second 🚀]
- [vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources]
- [vstinner/pyperf: Toolkit to run Python benchmarks]
- [vue.js]
- [vue.min.js]
- [W3Schools Online Web Tutorials]
- [WAVE Report of Мої книги | KUPRIENKO]
- [Web technology for developers | MDN]
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