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Getting Started

  • Gallery
  • Install
    • AIQC Python Package
    • Environment Setup
      • Python Version
        • Pickle Disclaimer
      • Operating System
      • Optional - JupyterLab IDE
      • Optional - Swap Space for Failover Memory
    • Location of AIQC Files
      • Location Based on OS
      • Database
      • Config
    • Optional - Deleting the Database
      • a) One-Liner
      • b) Or Line-by-Line
    • Troubleshooting
      • Reloading the Package
  • UI
    • Experiment Tracker
    • Compare Models Head-to-Head
    • What-If Analysis
    • Run the App
    • What about JupyterDash?

Documentation

  • API
    • Declarative
    • 1. Pipeline
      • 1a. Input
        • 1ai. Input.Interpolater
        • 1aii. Input.Window
        • 1aiii. Input.Encoder
      • 1b. Target
        • 1bi. Target.Interpolater
        • 1bii. Target.Encoder
      • 1c. Stratifier
    • 2. Experiment
      • 2a. Architecture
      • 2b. Trainer
    • 3. Inference
  • ORM
    • Object-Relational Model
    • 0. BaseModel
      • 0a. Methods
      • 0b. Attributes
    • 1. Dataset
      • 1a. Methods
        • 1ai. Registration
        • 1aii. Fetch
      • 1b. Attributes
    • 2. Feature
      • 2a. Methods
      • 2b. Attributes
    • 3. Label
      • 3a. Methods
      • 3b. Attributes
    • 4. Interpolate
      • 4a. LabelInterpolater
        • 4ai. Methods
        • 4aii. Attributes
      • 4b. FeatureInterpolater
        • 4bi. Methods
        • 4bii. Attributes
    • 5. Encode
      • 5a. LabelCoder
        • 5ai. Methods
        • 5aii. Attributes
      • 5b. FeatureCoder
        • 5bi. Methods
        • 5bii. Attributes
    • 6. Shape
      • 6a. Methods
      • 6b. Attributes
    • 7. Window
      • 7a. Methods
      • 7b. Attributes
    • 8. Splitset
      • 8a. Methods
      • 8b. Attributes
    • 9. Algorithm
      • 9a. Methods
      • 9b. Attributes
    • 10. Hyperparameters
      • 10a. Methods
      • 10b. Attributes
    • 11. Queue
      • 11a. Methods
      • 11b. Attributes
    • 12. Job
      • 12a. Methods
      • 12b. Attributes
    • 13. Predictor
      • 13a. Methods
      • 13b. Attributes
    • 14. Prediction
      • 14a. Methods
      • 14b. Attributes
    • Evaluation
  • Datasets
    • Overview
    • Prerequisites
    • Prepackaged Local Data
    • Remote Data
    • Alternative Sources
  • Evaluation
    • Overview
    • Prerequisites
    • Classification
      • Queue Visualization
      • Queue Metrics
      • Job Visualization
      • Job Metrics
      • Prediction Visualization
      • Prediction Metrics
    • Regression
      • Queue Visualization
      • Queue Metrics
      • Job Visualization
      • Job Metrics

About

  • Deep Learning 101
  • Open Source
    • Purpose
    • How can I get involved?
    • How can I contribute?
    • Setting up dev environment
    • Programming style
    • Code of conduct
    • Guild bylaws (aka governance)
    • AIQC, Inc. is open core
    • Open source
      • Choosing a license
  • Competition
  • Mission
    • Why Does AIQC Exist?
    • 1. Accelerate science by making deep learning accessible.
    • 2. Bring the scientific method to data science.
    • 3. Break down walled gardens to keep science open.
AIQC
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  • Gallery
  • Edit on GitHub

Gallery

🌱 Identify Plants
TensorFlow
PyTorch
Classify
Multi-label
Tabular
🧠 Detect Tumors
TensorFlow
PyTorch
Classify
Binary
Convolve
Image
💊 Design Drugs
TensorFlow
Classify
Binary
Tabular
🧬 Diagnose Cancers
TensorFlow
Classify
Multi-label
Tabular
⚡ Detect Seizures
TensorFlow
PyTorch
Classify
Multi-label
Recur
Time
Sequence
Univariate
💣 Sweep Mines
TensorFlow
TF Classic
PyTorch
Classify
Binary
Tabular
Notebook
Analysis
Data
🌡️ Exoplanet Temps.
TensorFlow
PyTorch
Regress
Tabular
🌀 Label Galaxies
TensorFlow
Classify
Binary
Multimodal
Tabular
Image
🪐 Astronomy Orbits
TensorFlow
Regress
Forecast
Convolve
Autoencode
Image
🌤️ Forecast Climate
TensorFlow
Regress
Forecast
Recur
Time
Multivariate
Tabular

Revision 1f7becdc.