Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pipelines and Cloud Platforms - Image 1

£39.85

Apress Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pipelines and Cloud Platforms

Name: Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pipelines and Cloud Platforms
Brand: Apress
Price: 39.85 GBP
Availability: InStock

Higher Education

Pricier than usual. £12 more than the 30-day average — we'd wait.

£40 today · 30-day average £28 · all-time low £12

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 89 days • 89 data points

Historical

Generating forecast...

Price Distribution

Price distribution over 89 days • 6 price levels

Days at Price

Current Price

Price Analysis

Most common price: £12 (47 days, 52.8%)

Price range: £12 - £41

Price levels: 6 different prices over 89 days

Description

This book covers modern data engineering functions and important Python libraries, to help you develop state-of-the-art ML pipelines and integration code. The book begins by explaining data analytics and transformation, delving into the Pandas library, its capabilities, and nuances. It then explores emerging libraries such as Polars and CuDF, providing insights into GPU-based computing and cutting-edge data manipulation techniques. The text discusses the importance of data validation in engineering processes, introducing tools such as Great Expectations and Pandera to ensure data quality and reliability. The book delves into API design and development, with a specific focus on leveraging the power of FastAPI. It covers authentication, authorization, and real-world applications, enabling you to construct efficient and secure APIs using FastAPI. Also explored is concurrency in data engineering, examining Dask's capabilities from basic setup to crafting advanced machine learning pipelines. The book includes development and delivery of data engineering pipelines using leading cloud platforms such as AWS, Google Cloud, and Microsoft Azure. The concluding chapters concentrate on real-time and streaming data engineering pipelines, emphasizing Apache Kafka and workflow orchestration in data engineering. Workflow tools such as Airflow and Prefect are introduced to seamlessly manage and automate complex data workflows. What sets this book apart is its blend of theoretical knowledge and practical application, a structured path from basic to advanced concepts, and insights into using state-of-the-art tools. With this book, you gain access to cutting-edge techniques and insights that are reshaping the industry. This book is not just an educational tool. It is a career catalyst, and an investment in your future as a data engineering expert, poised to meet the challenges of today's data-driven world. What You Will Learn Elevate your data wrangling jobs by utilizing the power of both CPU and GPU computing, and learn to process data using Pandas 2.0, Polars, and CuDF at unprecedented speeds Design data validation pipelines, construct efficient data service APIs, develop real-time streaming pipelines and master the art of workflow orchestration to streamline your engineering projects Leverage concurrent programming to develop machine learning pipelines and get hands-on experience in development and deployment of machine learning pipelines across AWS, GCP, and Azure Who This Book Is For Data analysts, data engineers, data scientists, machine learning engineers, and MLOps specialists

Product Specifications

Brand: Apress
Format: paperback
ASIN: B0D8XR4NJJ
Category: Books > Subjects > Science, Nature & Maths > Engineering & Technology > Education > Higher Education
Domain: Amazon UK
Release Date: 28 September 2024
Listed Since: 06 July 2024

Barcode

No barcode data available

Apress Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pipelines and Cloud Platforms

Pricier than usual. £12 more than the 30-day average — we'd wait.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Data Engineering with Google Cloud Platform: A practical guide to operationalizing scalable data analytics systems on GCP

Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples

Azure Data Engineering Cookbook: Get well versed in various data engineering techniques in Azure using this recipe-based guide, 2nd Edition

Data Engineeringon Azure

Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle

Building Data Science Applications with FastAPI: Develop, manage, and deploy efficient machine learning applications with Python

Production-Ready Applied Deep Learning: Learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks

Journey to Become a Google Cloud Machine Learning Engineer: Build the mind and hand of a Google Certified ML professional

A Python Data Analyst’s Toolkit: Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

The Pandas Workshop: A comprehensive guide to using Python for data analysis with real-world case studies

Docker on Windows: From 101 to production with Docker on Windows, 2nd Edition

Azure Data Engineer Associate Certification Guide: A hands-on reference guide to developing your data engineering skills and preparing for the DP-203 exam

Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R

Data Mesh Design: A Practical Pipeline Design Guide for Analytics, Data Science and Machine Learning

The Python Workshop: Learn to code in Python and kickstart your career in software development or data science

Python Machine Learning By Example: The easiest way to get into machine learning

Python: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents using Python

Digital Customer Experience Engineering: Strategies for Creating Effective Digital Experiences

Python for Data Engineering Build Scalable Data Pipelines, Analytics, and Automation (Data Engineering Domain For professional)

Modern Time Series Forecasting with Python: Explore industry-ready time series forecasting using modern machine learning and deep learning

Deep Dive into the Power Platform in the Age of Generative AI: Architectural Insights and Best Practices for Intelligent Business Solutions

Critical Approaches to Data Engineering Systems and Analysis

Microsoft Copilot for Power Apps: Transforming App Development with AI Assistance (Inside Copilot)

Cracking AI Engineering Interviews: A Practical Field Guide to Coding, Systems, ML, and Engineering Judgment