# Classifying Higgs boson processes in the HIGGS Data Set
## Overview
The [HIGGS Data Set](https://archive.ics.uci.edu/ml/datasets/HIGGS) contains 11 million samples with 28 features, and is for the classification problem to distinguish between a signal process which produces Higgs bosons and a background process which does not.
# Transformer Translation Model
This is an implementation of the Transformer translation model as described in the [Attention is All You Need](https://arxiv.org/abs/1706.03762) paper. Based on the code provided by the authors: [Transformer code](https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/models/transformer.py) from [Tensor2Tensor](https://github.com/tensorflow/tensor2tensor). Also, check out the [tutorial](https://www.tensorflow.org/beta/tutorials/text/transformer) on Transformer in TF 2.0.
# Predicting Income with the Census Income Dataset
Note that, the implementation is based on TF 1.x.
It is subjected to move to R1 archive folder.
The implementation is based on TensorFlow 1.x.
## Overview
The [Census Income Data Set](https://archive.ics.uci.edu/ml/datasets/Census+Income) contains over 48,000 samples with attributes including age, occupation, education, and income (a binary label, either `>50K` or `<=50K`). The dataset is split into roughly 32,000 training and 16,000 testing samples.
