In the simplest terms, event-driven architectures are like onions; they are manageable as a single layer (like a monolith) but when you get into them, they begin to cascade apart and you quickly realize that there are many complex layers (distributed microservices architecture). And that’s when the tears begin.This prescriptive guide takes you through the steps of moving a platform with millions o...
Machine Learning (ML) Английский PDFIn 2019, I published a PyTorch tutorial on Towards Data Science and I was amazed by the reaction from the readers! Their feedback motivated me to write this book to help beginners start their journey into Deep Learning and PyTorch. I hope you enjoy reading this book as much as I enjoy writing it.UPDATE (July, 19th, 2022): The Spanish version of Part I, Fundamentals, was published today:https://lea...
Python Английский PDFUp-to-date strategies for thwarting the latest, most insidious network attacksThis fully updated, industry-standard security resource shows, step by step, how to fortify computer networks by learning and applying effective ethical hacking techniques. Based on curricula developed by the authors at major security conferences and colleges, the book features actionable planning and analysis methods as...
Hacking and Security Английский PDFLearn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library.Use coroutines and tasks alongside async/await syntax to run code concurrentlyBuild web APIs and make concurrency web requests with aiohttpRun thousands of SQL queries concurrentlyCreate a map-reduce job that can process gigabytes of data concurrentlyUse threading with asyncio to mix blocking co...
Python Английский PDFIn Data Analysis with Python and PySpark you will learn how to:Manage your data as it scales across multiple machinesScale up your data programs with full confidenceRead and write data to and from a variety of sources and formatsDeal with messy data with PySpark’s data manipulation functionalityDiscover new data sets and perform exploratory data analysisBuild automated data pipelines tha...
Big Data/DataScience Python Английский PDFData engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.Author...
Big Data/DataScience Английский PDFComputers store and process data with an extra ordinary speed and accuracy. So, it is highly essential that the data is stored efficiently and can be accessed fast. Also, the processing of data should happen in the smallest possible time, but without losing the accuracy.Data structures deal with how the data is organised and held in the memory, when a program processes it. It is important to note...
Big Data/DataScience Python Английский PDFWhat will you learn from this book?Head First Java is a complete learning experience in Java and object-oriented programming. With this book, you'll learn the Java language with a unique method that goes beyond how-to manuals and helps you become a great programmer. Through puzzles, mysteries, and soul-searching interviews with famous Java objects, you'll quickly get up to speed on Java's fun...
Java Английский PDFFinancial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to r...
Machine Learning (ML) Python Английский PDFPython definitely tops the charts when it comes to ease of use and beginner-friendly learning curve in the world of programming languages. At the same time, Python is essential when it comes to writing system scripts, processing big data, performing mathematical computations, creating web applications, and rapid prototyping.With this Mastering edition, we have focused especially on the u...
Python Английский PDFMachine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments...
Machine Learning (ML) Английский PDFPractical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. Anthony DeBarros, a journalist and data analyst, focuses on using SQL to find the story within your data. The examples and code use the open-source database PostgreSQL and its companion pgAdmin interfa...
DataBase (SQL) Английский PDFGet the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.Written by Wes McKinney...
Big Data/DataScience Python Английский PDFObject-Oriented Python is an intuitive and thorough guide to mastering object-oriented programming from the ground up. You’ll cover the basics of building classes and creating objects, and put theory into practice using the pygame package with clear examples that help visualize the object-oriented style. You’ll explore the key concepts of object-oriented programming — encapsulation, polymorph...
Python Английский PDFMaster the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those...
Big Data/DataScience Английский PDF