This device is not compatible.
PROJECT
Getting Started With TFJS
Learn to make a deep learning model using Tensorflow Javascript. In this project, we'll build and train a deep learning model from scratch for the CIFAR-10 dataset. We'll also load a pre-trained model to make predictions on the test data.
You will learn to:
Make a deep learning model using TFJS
Train a model on CIFAR-10 dataset
Load a pre-trained model in TFJS
Use TensorBoard to visualize training
Skills
Machine Learning
Deep Learning
Deep Neural Networks
Prerequisites
Tensorflow
Javascript
Technologies
Node.js
TensorFlowJS
Project Description
Oftentimes, web developers need to use a machine learning model in a website. Instead of making a model in Python and connecting it with the front-end, we can make a model in Javascript and use it directly on the website. In this project, we’ll make a beginner-friendly deep learning model using TensorFlow Javascript.
In this project, we’ll use CIFAR-10 dataset. CIFAR-10 is a small dataset with 10 classes: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck. The classes are mutually exclusive. For example, the automobile class includes SUVs, sedans, and so on. On the other hand, truck class includes only large trucks.
After building and running the project, we’ll load a pre-trained model and use it to make predictions.
Project Tasks
1
Getting Started
Task 0: Instructions
Task 1: Loading Dataset
2
Preprocessing
Task 2: Normalization
Task 3: Reshape
Task 4: Preprocessing Features
Task 5: Implementing One-hot Encoding
Task 6: Preprocessing Labels
3
Building a Model
Task 7: Define the Model
Task 8: Compile Model
Task 9: Fit Model
Task 10: Start Training
4
Prediction
Task 11: Export Functions
Task 12: Load Trained Model
Task 13: Make Predictions
Congratulations!
Relevant Course
Use the following content to review prerequisites or explore specific concepts in detail.