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ASL Recognition with Deep Learning

Build a convolutional neural network to classify images of letters from American Sign Language.

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9 Tasks1,500 XP

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Project Description

American Sign Language (ASL) is the primary language used by many deaf individuals in North America, and it is also used by hard-of-hearing and hearing individuals. The language is as rich as spoken languages and employs signs made with the hand, along with facial gestures and bodily postures. In this project, you will train a convolutional neural network to classify images of ASL letters. After loading, examining, and preprocessing the data, you will train the network and test its performance.

Project Tasks

  1. 1
    American Sign Language (ASL)
  2. 2
    Visualize the training data
  3. 3
    Examine the dataset
  4. 4
    One-hot encode the data
  5. 5
    Define the model
  6. 6
    Compile the model
  7. 7
    Train the model
  8. 8
    Test the model
  9. 9
    Visualize mistakes

Technologies

Python Python

Topics

Data ManipulationData VisualizationMachine LearningImporting & Cleaning Data
Alexis Cook Headshot

Alexis Cook

Machine Learning Educator at Kaggle

Alexis is an AI educator with a background in mathematics. She formerly worked as a Curriculum Lead at Udacity, where she built content in deep learning, including applications to computer vision, natural language processing, and reinforcement learning.
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