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Your First Model

A comprehensive guide to building your first ML model from scratch.

Overview

In this tutorial, you will learn how to create a simple image classification model using 1.ML. By the end, you will have a fully trained model deployed and ready to make predictions.

1. Prepare Your Data

from oneml import Dataset

# Load and prepare your dataset
dataset = Dataset.load("./images")
train, test = dataset.split(ratio=0.8)

2. Define Your Model

from oneml import Model, layers

model = Model([
  layers.Conv2D(32, kernel=3),
  layers.MaxPool2D(),
  layers.Dense(128),
  layers.Output(10)
])

3. Train and Deploy

# Train the model
model.fit(train, epochs=10)

# Deploy to production
model.deploy("my-classifier")