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Designing Data-Intensive Applications by Martin Kleppmann

  • Comprehensive guide for data-intensive application design.
  • Navigate scalability, consistency, and reliability challenges.
  • Explore pros and cons of data storage technologies.
  • Understand trade-offs in fault tolerance and complexity.
  • Learn from architectures of major online services.
  • Apply fundamental principles to modern software engineering.
  • Make informed decisions on technology choices.

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Best Alternatives and Similar Products for Designing Data-Intensive Applications by Martin Kleppmann

The best Databases & Big Data includes Build a Language Model from Scratch: A Complete Guide, Designing Data-Intensive Applications Book, Code: The Hidden Language of Computing and many others as mentioned below.

1

Build a Language Model from Scratch: A Complete Guide

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    2

    Designing Data-Intensive Applications Book

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  • Comprehensive guide to data-intensive application design.
  • Explore scalability, consistency, and reliability challenges.
  • Examine pros and cons of various technologies.
  • Understand trade-offs in architecture decisions.
  • Learn from major online service architectures.
  • Navigate tools like NoSQL and relational databases.
  • Make informed decisions for modern applications.
  • Price Range: $26.33

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    3

    Code: The Hidden Language of Computing

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  • Illuminates how computers and software truly function.
  • Engaging storytelling builds understanding layer by layer.
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  • Companion website enhances learning with animated graphics.
  • Teaches computing concepts through relatable analogies.
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    Data Science Interview Questions: 201 Essential Tips

  • 201 real interview questions from top tech companies
  • Step-by-step solutions for better understanding
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  • Tips for resume crafting and networking
  • Case study practice from renowned companies
  • Insights from Ex-Facebook data professionals
  • Avoid counterfeit books; buy new only
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    Python and SQL: Ultimate 5-in-1 Coding Guide

  • Comprehensive guide from beginner to advanced level.
  • Master Python and SQL with practical examples.
  • Hands-on exercises for real-world applications.
  • Boost your confidence tackling coding challenges.
  • Five books in one for complete learning.
  • Learn advanced topics to enhance your skills.
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    Generative AI System Design Interview Guide

  • Structured approach for generative AI design interviews.
  • Practical framework simplifies complex concepts.
  • Real-world examples enhance understanding and application.
  • Insider insights on interviewer expectations.
  • Seven-step framework for tackling design questions.
  • In-depth solutions for ten example questions.
  • Over 280 diagrams to clarify system architecture.
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    R for Data Science: A Comprehensive Guide

  • Learn data science using R and RStudio.
  • Master tidyverse for efficient data analysis.
  • Import, transform, and visualize your data effectively.
  • Communicate results clearly with integrated prose.
  • Practice with exercises to reinforce learning.
  • Updated for latest tidyverse features and best practices.
  • Gain a comprehensive understanding of data science cycle.
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    SQL QuickStart Guide: Beginner's Data Management

  • Comprehensive SQL guide for beginners.
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    Python Data Analysis: Pandas, NumPy, Jupyter

  • Comprehensive guide for data manipulation in Python.
  • Updated for Python 3.10 and pandas 1.4.
  • Practical case studies for effective data analysis.
  • Learn pandas, NumPy, and Jupyter essentials.
  • Ideal for Python programmers and data analysts.
  • Access data files and materials on GitHub.
  • Create informative visualizations with matplotlib.
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    Fundamentals of Data Engineering Guide

  • Comprehensive overview of data engineering landscape.
  • Learn to plan and build robust data systems.
  • Evaluate technologies through the data engineering lifecycle.
  • Understand data generation, ingestion, and orchestration concepts.
  • Design architecture using best practices and frameworks.
  • Incorporate governance and security in data processes.
  • Cut through marketing hype for better technology choices.
  • Price Range: $43.99

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    Understanding Large Language Models: Hands-On Guide

  • Learn practical tools for language AI applications.
  • Understand Transformer architecture for text generation.
  • Create advanced pipelines for document clustering.
  • Build semantic search engines beyond keyword matching.
  • Explore generative models and prompt engineering techniques.
  • Train and optimize LLMs for specific tasks.
  • Utilize pretrained models for text classification tasks.
  • Price Range: $55.98

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    12

    Practical SQL: Beginner's Guide to Data Storytelling

  • Learn SQL through real-world data examples.
  • Beginner-friendly guide to SQL and databases.
  • Analyze data using PostgreSQL and pgAdmin tools.
  • Hands-on exercises for practical skill-building.
  • Create and manage databases efficiently.
  • Updated content with advanced SQL techniques.
  • Two new chapters on system setup and JSON.
  • Price Range: $27.41

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    13

    Fundamentals of Data Engineering Book

  • Comprehensive overview of data engineering practices.
  • Learn to build robust data systems.
  • Evaluate technologies through a data lifecycle framework.
  • Understand key concepts: ingestion, transformation, storage.
  • Assess data problems with best practices.
  • Incorporate governance and security in engineering.
  • Available PDF included with your purchase.
  • Price Range: $21.43

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    14

    Build a Language Model from Scratch: A Guide

  • Step-by-step guide to building LLMs.
  • Clear explanations with diagrams and examples.
  • Code a GPT-style language model from scratch.
  • Fine-tune LLMs for specific tasks and data.
  • Prepare datasets suitable for effective training.
  • Develop your own personal assistant LLM.
  • Requires intermediate Python and machine learning knowledge.
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    The Data Warehouse Toolkit: Dimensional Modeling Guide

  • Comprehensive guide to dimensional modeling techniques.
  • Updated third edition with new ETL techniques.
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  • Authored by renowned experts Ralph Kimball and Margy Ross.
  • Focus on real-world business applications and scenarios.
  • Designed for fast query response and ease of understanding.
  • Essential resource for data warehousing and business intelligence.
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