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Fiddler Documentation
Product DocumentationRecipesAPI ReferenceRelease Notes
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Product DocumentationRecipesAPI ReferenceRelease Notes

Overview

  • Welcome to Fiddler's Documentation!
  • Product Tour

QuickStart Notebooks

  • Simple Monitoring
  • NLP Monitoring
  • CV Monitoring
  • Explainability with a Surrogate Model
  • Explainability with Model Artifact

Illustrative Walkthroughs

  • Fraud Detection
  • Customer Churn Prediction

Platform Guide

  • Administration
  • Project Architecture
  • Model: Artifacts, Package, Surrogate
  • Monitoring
    • Alerts
    • Data Drift
    • Traffic
    • Data Integrity
    • Performance Tracking
    • Vector Monitoring
    • Class-Imbalanced Data
  • Explainability
    • Point Explainability
    • Global Explainability
  • Fairness
  • Analytics and Evaluation
  • Model Task Types
  • Supported Browsers

UI Guide

  • Administration
    • Settings
    • Inviting Users
    • Project Structure on UI
    • Authorization and Access Control
  • Monitoring
    • Data Drift
    • Performance
    • Data Integrity
    • Traffic
    • Alerts with Fiddler UI
  • Explainability
    • Point Explainability
    • Global Explainability
    • Surrogate Models
  • Analytics
    • Useful Queries for Root Cause Analysis
  • Evaluation
  • Fairness

Client Guide

  • Installation and Setup
  • Authorizing the Client
  • Designing a Baseline Dataset
  • Uploading a Baseline Dataset
  • Customizing Your Dataset Schema
  • Specifying Custom Missing Value Encodings
  • Onboarding a Model
    • Binary Classification
    • Multiclass Classification
    • Regression
    • Ranking
  • Surrogate Models - Client Guide
  • Uploading model artifacts
  • Updating model artifacts
  • Package.py Examples
    • Binary Classification Model Package.py
    • Regression Model Package.py
    • Multi-class Classification Model Package.py
    • Ranking Model Package.py
  • ML Framework Examples
    • Uploading a scikit-learn Model Artifact
    • Uploading an XGBoost Model Artifact
    • Uploading a TensorFlow SavedModel Model Artifact
    • Uploading a TensorFlow HDF5 Model Artifact
  • Publishing Production Data
    • Streaming Live Events
    • Publishing Batches of Events
    • Publishing Events With Complex Data Formats
    • Updating Events
    • Retrieving Events
    • Using Custom Timestamps
    • Publishing Ranking Events
  • Alerts with Fiddler Client
  • Alerting Integrations
    • PagerDuty Integration
  • Data Pipeline Integrations
    • S3 Integration
    • Airflow Integration
    • SageMaker Integration
    • BigQuery Integration
    • Snowflake Integration
    • Databricks Integration
  • ML Platform Integrations
    • SageMaker ML Integration

Deployment Guide

  • Deploying Fiddler
    • System Architecture
    • On-prem Technical Requirements
    • On-prem Installation Guide
    • Routing to Fiddler (on-prem)
  • Single Sign On with Okta

Explainability

Platform information

Suggest Edits

Fiddler's Explainability offering covers:

  • Point Explainations
  • Global Explainations
  • Surrogate Model

Updated about 2 months ago