Transforms the result of TensorFlow computations.

This document is the first in a two-part series that explores the topic of data engineering and feature engineering for machine learning (ML), with a focus on supervised learning tasks. This first ...

Stay organized with collections Save and categorize content based on your preferences. This tutorial also assumes that you're familiar with the concepts of preprocessing types, challenges, and options ...

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Libraries for the federated CIFAR-100 dataset for simulation.

Models for running TensorFlow Federated simulations.

import tensorflow_decision_forests as tfdf import pandas as pd # Load a dataset in a Pandas dataframe. train_df = pd.read_csv("project/train.csv") test_df = pd.read ...

import numpy as np import tensorflow as tf import tensorflow_lattice as tfl model = tf.keras.models.Sequential() model.add( tfl.layers.ParallelCombination ...