Создание Telegram Бота с Webhook'ом на Python 3. Создание тестового приложения на Flask и его загрузка на хостинг PythonAnyWhere. Решение проблемы с использованием SSL-сертификатов.
https://youtu.be/QmGYc7aWpd4
https://youtu.be/QmGYc7aWpd4
YouTube
1. Создание Telegram бота с Webhook'ом на Python. Подготовка.
Мои курсы:
Boosty:
https://boosty.to/omolchanov/posts/995a18dd-487b-4000-9b3f-0aafa5e060cd
Patreon:
https://www.patreon.com/posts/karty-vsekh-41011404
Создание Telegram Бота с Webhook'ом на Python 3. Создание тестового приложения на Flask и его загрузка…
Boosty:
https://boosty.to/omolchanov/posts/995a18dd-487b-4000-9b3f-0aafa5e060cd
Patreon:
https://www.patreon.com/posts/karty-vsekh-41011404
Создание Telegram Бота с Webhook'ом на Python 3. Создание тестового приложения на Flask и его загрузка…
Деплой Telegram Python бота на Heroku.
Пример как выложить созданного телеграм бота на сервер.
https://youtu.be/B72-sZyiW10
Пример как выложить созданного телеграм бота на сервер.
https://youtu.be/B72-sZyiW10
YouTube
ДЕПЛОЙ БОТА ► Деплой Telegram Python бота на Heroku
Thinking_in_Pandas_How_to_Use_the_Python_Data_Analysis_Library_the.pdf
2.3 MB
Thinking in Pandas How to Use the Python Data Analysis Library the Right Way by Hannah Stepanek 2020.pdf
What You Will Learn
📌 Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances
📌 Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance
📌 Choose the right DataFrame so that the data analysis is simple and efficient.
📌 Improve performance of pandas operations with other Python libraries
What You Will Learn
📌 Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances
📌 Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance
📌 Choose the right DataFrame so that the data analysis is simple and efficient.
📌 Improve performance of pandas operations with other Python libraries
Full Stack Python is an open source book that explains technical concepts in plain language. Read everything online for free
https://www.fullstackpython.com/
https://www.fullstackpython.com/
Fullstackpython
Full Stack Python
Full Stack Python explains programming concepts in plain language and provides links to the best tutorials for those topics.
Hands_On_Data_Science_with_Anaconda_by_Yuxing_Yan,_James_Yan.epub
13.3 MB
Hands-On Data Science with Anaconda. Yuxing Yan, James Yan. 2018 EPUB
Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world.
The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod.
Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world.
The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod.
Pro_Power_Bi_Desktop_Self_service_Analytics_and_Data_Visualization.pdf
28.7 MB
Pro Power Bi Desktop: Self-service Analytics and Data Visualization for the Power User. Adam Aspin. 2020
What You Will Learn
🏷 Deliver attention-grabbing information, turning data into insight
🏷 Find new insights as you chop and tweak your data as never before
🏷 Build a data narrative through interactive reports with drill-through and cross-page slicing
🏷 Mash up data from multiple sources into a cleansed and coherent data model
🏷 Build interdependent charts, maps, and tables to deliver visually stunning information
🏷 Create dashboards that help in monitoring key performance indicators of your business
🏷 Adapt delivery to mobile devices such as phones and tablets
What You Will Learn
🏷 Deliver attention-grabbing information, turning data into insight
🏷 Find new insights as you chop and tweak your data as never before
🏷 Build a data narrative through interactive reports with drill-through and cross-page slicing
🏷 Mash up data from multiple sources into a cleansed and coherent data model
🏷 Build interdependent charts, maps, and tables to deliver visually stunning information
🏷 Create dashboards that help in monitoring key performance indicators of your business
🏷 Adapt delivery to mobile devices such as phones and tablets
Clark_Dan_Beginning_Microsoft_Power_BI_A_Practical_Guide_to_Self.pdf
22.5 MB
Clark Dan. Beginning Microsoft Power BI: A Practical Guide to Self-Service Data Analytics.pdf
What You Will Learn:
🏷 Simplify data discovery, association, and cleansing
🏷 Build solid analytical data models
🏷 Create robust interactive data presentations
🏷 Combine analytical and geographic data in map-based visualizations
🏷 Publish and share dashboards and reports
What You Will Learn:
🏷 Simplify data discovery, association, and cleansing
🏷 Build solid analytical data models
🏷 Create robust interactive data presentations
🏷 Combine analytical and geographic data in map-based visualizations
🏷 Publish and share dashboards and reports
Horne I. Hands-On Business Intelligence with DAX.pdf
10.7 MB
Horne I. Hands-On Business Intelligence with DAX.pdf
🏷 Understand DAX, from the basics through to advanced topics, and learn to build effective data models
🏷 Write and use DAX functions and expressions with the help of hands-on examples
🏷 Discover how to handle errors in your DAX code, and avoid unwanted results
🏷 Load data into a data model using Power BI, Excel Power Pivot, and SSAS Tabular
🏷 Cover DAX functions such as date, time, and time intelligence using code examples
🏷 Gain insights into data by using DAX to create new information
🏷 Understand the DAX VertiPaq engine and how it can help you optimize data models
🏷 Understand DAX, from the basics through to advanced topics, and learn to build effective data models
🏷 Write and use DAX functions and expressions with the help of hands-on examples
🏷 Discover how to handle errors in your DAX code, and avoid unwanted results
🏷 Load data into a data model using Power BI, Excel Power Pivot, and SSAS Tabular
🏷 Cover DAX functions such as date, time, and time intelligence using code examples
🏷 Gain insights into data by using DAX to create new information
🏷 Understand the DAX VertiPaq engine and how it can help you optimize data models
Practical_Data_Analysis_Using_Jupyter_Notebook_Learn_how_to_speak.pdf
7.7 MB
Practical Data Analysis Using Jupyter Notebook: Learn how to speak the language of data by extracting insights with Python.pdf
🏷 Understand the importance of data literacy and how to communicate effectively using data
🏷 Find out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysis
🏷 Wrangle data and create DataFrames using pandas
Produce charts and data visualizations using time-series datasets
🏷 Discover relationships and how to join data together using SQL
🏷 Use NLP techniques to work with unstructured data to create sentiment analysis models
🏷 Discover patterns in real-world datasets that provide accurate insights
🏷 Understand the importance of data literacy and how to communicate effectively using data
🏷 Find out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysis
🏷 Wrangle data and create DataFrames using pandas
Produce charts and data visualizations using time-series datasets
🏷 Discover relationships and how to join data together using SQL
🏷 Use NLP techniques to work with unstructured data to create sentiment analysis models
🏷 Discover patterns in real-world datasets that provide accurate insights
Lewinson E. Python for Finance Cookbook.pdf
32.8 MB
Lewinson E. Python for Finance Cookbook.pdf
Use powerful Python libraries such as pandas, NumPy, and SciPy
In this book, you’ll cover different ways of downloading financial data and preparing it for modeling. You’ll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, and RSI, and backtest automatic trading strategies. Next, you’ll cover time series analysis and models such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and Fama-French's Three-Factor Model. You’ll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you’ll work through an entire data science project in the finance domain. You’ll also learn how to solve credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models.
Use powerful Python libraries such as pandas, NumPy, and SciPy
In this book, you’ll cover different ways of downloading financial data and preparing it for modeling. You’ll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, and RSI, and backtest automatic trading strategies. Next, you’ll cover time series analysis and models such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and Fama-French's Three-Factor Model. You’ll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you’ll work through an entire data science project in the finance domain. You’ll also learn how to solve credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models.
Lerner R.M. Python Workout. 50 Essential Exercises.pdf
8.2 MB
Lerner R.M. Python Workout. 50 Essential Exercises.pdf
This book isn’t meant to teach you Python. Rather, it’s meant to give you the practice you need to achieve greater fluency. After going through the exercises in this book—not just skimming through the questions and peeking at the answers—you will write more readable, more idiomatic, and more maintainable Python code.
Python Workout is the result of conversations with students in my corporate Python training classes. Once the course was over, they often asked where they could get additional practice, to continue improving their skills. This book draws upon the hands-on labs that I give my students, as well as discussions that I have had with them during and after class.
This book isn’t meant to teach you Python. Rather, it’s meant to give you the practice you need to achieve greater fluency. After going through the exercises in this book—not just skimming through the questions and peeking at the answers—you will write more readable, more idiomatic, and more maintainable Python code.
Python Workout is the result of conversations with students in my corporate Python training classes. Once the course was over, they often asked where they could get additional practice, to continue improving their skills. This book draws upon the hands-on labs that I give my students, as well as discussions that I have had with them during and after class.
How_Matt_The_Modern_Data_Warehouse_in_Azure_Building_with_Speed.pdf
9.6 MB
How Matt. The Modern Data Warehouse in Azure: Building with Speed and Agility on Microsoft’s Cloud Platform.pdf
What You Will Learn
🏷 Choose the appropriate Azure SQL engine for implementing a given data warehouse
🏷 Develop smart, reusable ETL/ELT processes that are resilient and easily maintained
🏷 Automate mundane development tasks through tools such as PowerShell
🏷 Ensure consistency of data by creating and enforcing data contracts
🏷 Explore streaming and event-driven architectures for data ingestion
🏷 Create advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse
What You Will Learn
🏷 Choose the appropriate Azure SQL engine for implementing a given data warehouse
🏷 Develop smart, reusable ETL/ELT processes that are resilient and easily maintained
🏷 Automate mundane development tasks through tools such as PowerShell
🏷 Ensure consistency of data by creating and enforcing data contracts
🏷 Explore streaming and event-driven architectures for data ingestion
🏷 Create advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse
Всё для изучения Python: 181 бесплатный материал + бонус
https://tproger.ru/digest/data-science-python/
https://tproger.ru/digest/data-science-python/
Tproger
Всё для изучения Python: 181 бесплатный материал + бонус
Статья на Tproger — Всё для изучения Python: 181 бесплатный материал + бонус