📓 Python Concurrency with asyncio.

• Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python’s performance by applying a variety of concurrency techniques. You’ll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio’s APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading.

• Use coroutines and tasks alongside async/await syntax to run code concurrently;
• Build web APIs and make concurrency web requests with aiohttp;
• Run thousands of SQL queries concurrently;
• Create a map-reduce job that can process gigabytes of data concurrently;
• Use threading with asyncio to mix blocking code with asyncio code.

#Eng

Python Concurrency with asyncio.
2022 #Eng || Бесплатный софт для чтения книг.

📓 Data Analysis with Python and PySpark.

• When it comes to data analytics, it pays to think big. PySpark blends the powerful Spark big data processing engine with the Python programming language to provide a data analysis platform that can scale up for nearly any task. Data Analysis with Python and PySpark is your guide to delivering successful Python-driven data projects.

• Data Analysis with Python and PySpark is a carefully engineered tutorial that helps you use PySpark to deliver your data-driven applications at any scale. This clear and hands-on guide shows you how to enlarge your processing capabilities across multiple machines with data from any source, ranging from Hadoop-based clusters to Excel worksheets. You’ll learn how to break down big analysis tasks into manageable chunks and how to choose and use the best PySpark data abstraction for your unique needs.

#Eng #PySpark

Data Analysis with Python and PySpark.
2022 #Eng #PySpark || Бесплатный софт для чтения книг.

📓 Python: Machine Learning Projects.

• This book will set you up with a Python programming environment if you don’t have one already, then provide you with a conceptual understanding of machine learning in the chapter “An Introduction to Machine Learning.” What follows next are three Python machine learning projects. They will help you create a machine learning classifier, build a neural network to recognize handwritten digits, and give you a background in deep reinforcement learning through building a bot for Atari.

#Eng

Python: Machine Learning Projects.
2022 #ENG || Бесплатный софт для чтения книг.

📓 Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch. 2022.

• The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoretical and practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch.

#ENG #PyTorch

Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch.
2022 #ENG #PyTorch || Бесплатный софт для чтения книг.

📓 Python for MATLAB Development: Extend MATLAB with 300,000+ Modules from the Python Package Index. 2022.

This book shows how to call Python functions to enhance MATLAB’s capabilities. Specifically, you’ll see how Python helps MATLAB:

• Run faster with numba;
• Distribute work to a compute cluster with dask;
• Find symbolic solutions to integrals, derivatives, and series summations with SymPy;
• Overlay data on maps with Cartopy;
• Solve mixed-integer linear programming problems with PuLP;
• Interact with Redis via pyredis, PostgreSQL via psycopg2, and MongoDB via pymongo;
• Read and write file formats that are not natively understood by MATLAB, such as SQLite, YAML, and ini.

#ENG #MATLAB #MongoDB #SQL #Redis #SymPy #Cartopy #YAML

Python for MATLAB Development: Extend MATLAB with 300,000+ Modules from the Python Package Index.
2022 #ENG #MATLAB #MongoDB #SQL #Redis #SymPy #Cartopy #YAML || Бесплатный софт для чтения книг.

🐍 Python Learning Courses provided by Microsoft.

📌 Beginner:
1. What is Python?
2. Introduction to Python
3. Take your first steps with Python
4. Set up your Python beginner development environment with Visual Studio Code
5. Branch code execution with the if...elif...else statement in Python
6. Manipulate and format string data for display in Python
7. Perform mathematical operations on numeric data in Python
8. Iterate through code blocks by using the while statement
9. Import standard library modules to add features to Python programs
10. Create reusable functionality with functions in Python
11. Manage a sequence of data by using Python lists
12. Write basic Python in Notebooks
13. Count the number of Moon rocks by type using Python
14. Code control statements in Python
15. Introduction to Python for space exploration
16. Install coding tools for Python development
17. Discover the role of Python in space exploration
18. Crack the code and reveal a secret with Python and Visual Studio Code
19. Introduction to object-oriented programming with Python
20. Use Python basics to solve mysteries and find answers
21. Predict meteor showers by using Python and Visual Studio Code
22. Plan a Moon mission by using Python pandas

📌 Intermediate:
1. Create machine learning models
2. Explore and analyze data with Python
3. Build an AI web app by using Python and Flask
4. Get started with Django
5. Architect full-stack applications and automate deployments with GitHub

#Курс #Python #Eng

🐍 Python Learning Courses provided by Microsoft.

📌 Beginner:
1. What is Python?
2. Introduction to Python
3. Take your first steps with Python
4. Set up your Python beginner development environment with Visual Studio Code
5. Branch code execution with the if...elif...else statement in Python
6. Manipulate and format string data for display in Python
7. Perform mathematical operations on numeric data in Python
8. Iterate through code blocks by using the while statement
9. Import standard library modules to add features to Python programs
10. Create reusable functionality with functions in Python
11. Manage a sequence of data by using Python lists
12. Write basic Python in Notebooks
13. Count the number of Moon rocks by type using Python
14. Code control statements in Python
15. Introduction to Python for space exploration
16. Install coding tools for Python development
17. Discover the role of Python in space exploration
18. Crack the code and reveal a secret with Python and Visual Studio Code
19. Introduction to object-oriented programming with Python
20. Use Python basics to solve mysteries and find answers
21. Predict meteor showers by using Python and Visual Studio Code
22. Plan a Moon mission by using Python pandas

📌 Intermediate:
1. Create machine learning models
2. Explore and analyze data with Python
3. Build an AI web app by using Python and Flask
4. Get started with Django
5. Architect full-stack applications and automate deployments with GitHub

#Курс #Python #Eng