Evaluating and cleaning data

Contents

• Introduction Introduction

  • Evaluating LLMs: Introduction

    1m 53s
• 1. Foundations of LLM Evaluation 1. Foundations of LLM Evaluation

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    Topics

    34s
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    Introduction to evaluation: Why it matters

    13m 24s
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    Generative versus understanding tasks

    11m 3s
  • Key metrics for common tasks

    19m 15s
• 2. Evaluating Generative Tasks 2. Evaluating Generative Tasks

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    Topics

    35s
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    Evaluating multiple-choice tasks

    13m 16s
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    Evaluating free text response tasks, part 1

    23m 43s
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    Evaluating free text response tasks, part 2

    26m 54s
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    AIs supervising AIs: LLM as a judge

    12m 29s
• 3. Evaluating Understanding Tasks 3. Evaluating Understanding Tasks

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    Topics

    47s
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    Evaluating embedding tasks

    15m 55s
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    Evaluating classification tasks

    21m 46s
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    Building an LLM classifier with BERT and GPT

    24m 2s
• 4. Using Benchmarks Effectively 4. Using Benchmarks Effectively

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    Topics

    45s
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    The role of benchmarks

    7m 45s
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    Interrogating common benchmarks

    20m 36s
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    Evaluating LLMs with benchmarks

    23m 30s
• 5. Probing LLMs for a World Model 5. Probing LLMs for a World Model

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    Topics

    37s
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    Probing LLMs for knowledge

    18m 47s
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    Probing LLMs to play games

    27m 20s
• 6. Evaluating LLM Fine-Tuning 6. Evaluating LLM Fine-Tuning

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    Topics

    36s
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    Fine-tuning objectives

    9m 57s
  • Metrics for fine-tuning success

    11m 42s
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    Practical demonstration: Evaluating fine-tuning

    25m 54s
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    Evaluating and cleaning data

    32m 30s
• 7. Case Studies 7. Case Studies

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    Topics

    43s
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    Evaluating AI agents: Task automation and tool integration

    18m 41s
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    Measuring retrieval-augmented generation (RAG) systems

    11m 58s
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    Building and evaluating a recommendation engine using LLMs

    19m 13s
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    Using evaluation to combat AI drift

    22m 1s
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    Time-series regression

    19m 35s
• 8. Summary of Evaluation and Looking Ahead 8. Summary of Evaluation and Looking Ahead

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    Topics

    40s
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    When and how to evaluate

    10m 37s
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    Looking ahead: Trends in LLM evaluation

    6m 35s
• Conclusion Conclusion

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    Evaluating LLMs: Summary

    54s