THE APORIA ACADEMY

ML Observability Expert

Introduction >

1. Intro

2. ML evaluation metrics

3. Drift Metrics

4. Fairness metrics

5. Explainability

6. Production ML

7. LLM Observability

ML Observability Experts

Aporia Team
Aporia Team
2 min read May 22, 2023

Table of Contents

    Welcome to the Aporia ML Observability Expert Academy! This advanced program is designed to equip machine learning engineers, MLOps engineers, data scientists, and other experienced ML practitioners with an in-depth, expert-level understanding of observability, including LLM observability. By participating in this academy, you’ll gain insights into specialized areas such as ML Evaluation metrics, Drift Metrics, Fairness Metrics, Explainability, and more.

    Part 1: Model Evaluation, Drift, and Fairness Metrics

    In this first section, we will deep dive into the complex landscape of ML Evaluation metrics, uncovering how to measure model effectiveness accurately. We will explore Drift Metrics to understand how data can change over time and affect models, and Fairness Metrics to ensure that models are free from biases and treat all users equitably.

    Part 2: Explainability and LLM Observability

    The second part of the program will focus on Explainability in ML, providing tools and methodologies to interpret model decisions and build trust with stakeholders. Additionally, we will explore LLM (Large Language Models) Observability, addressing the unique challenges and solutions for observing and understanding these sophisticated models.

    Part 3: Advanced Monitoring Techniques

    The third part of the academy expands your knowledge on monitoring by drilling down into specific use cases, extending the concepts from basic to expert levels. Join us as we unlock the power of observability in ML and empower you to build trustworthy and high-performing machine learning systems.

    Don’t feel like you can finish all the lessons in one day? No problem, put us on your calendar for quick and easy reminders here.

    Prerequisites and Topics Learned in This Course

    You’ll need an intermediate to advanced understanding of the following:

    • Machine Learning
    • Python
    • MLOps
    • Model Evaluation Techniques

    Topics Covered:

    • ML Evaluation Metrics
    • Drift Metrics
    • Fairness Metrics
    • Explainability
    • LLM Observability

    Whether you’re looking to deepen your expertise or explore cutting-edge areas of ML observability, the Aporia ML Observability Expert Academy provides a comprehensive and challenging learning journey. Join us and elevate your skills to the expert level!

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    Aporia Team
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