Classification video tutorials - SentiSight.ai
Basic workflow tutorial

Basic workflow tutorial

Topics covered:
  • Training a single label classification model
  • Analyzing model's performance
  • Using the model inside the platform or via REST API
Labeling images for classification

Labeling images for classification

Topics covered:
  • Labeling images during the upload
  • Adjusting the labels after the upload
  • Changing thedefault label for the image
Selecting images for training

Selecting images for training

Topics covered:
  • The default platform's behavior - training on all images
  • Filtering images by label or by type
  • Selecting images for training manually
Training a single label classification model in detail

Training a single label classification model in detail

Topics covered:
  • Explanation of training parameters
  • The relationship of per-class and global performance statistics
  • Viewing and downloading predictions on train/validation sets
  • Analyzing the learning curves
  • Analyzing the confusion matrix
  • Using the model inside the platform or via REST API
Training a multi-label classification model in detail

Training a multi-label classification model in detail

Topics covered:
  • Uploading images from a folder
  • Uploading image classification labels
  • Including/excluding image labels from training
  • Analyzing multi-label predictions
  • Changing score thresholds for classification
  • Analyzing precision-recall curve
  • The definition of "best" and "last" model
  • Making multi-label predictions
Training a model on one class tutorial

Training a model on one class tutorial

Topics covered:
  • How to train a classification model on one class
  • How to train multiple one-class classification models in an easy way
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