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+# Mathematics Dataset
+
+This dataset code generates mathematical question and answer pairs, from a range
+of question types at roughly school-level difficulty. This is designed to test
+the mathematical learning and algebraic reasoning skills of learning models.
+
+Original paper: [Analysing Mathematical
+Reasoning Abilities of Neural Models](https://openreview.net/pdf?id=H1gR5iR5FX)
+(Saxton, Grefenstette, Hill, Kohli).
+
+## Example questions
+
+```
+Question: Solve -42*r + 27*c = -1167 and 130*r + 4*c = 372 for r.
+Answer: 4
+
+Question: Calculate -841880142.544 + 411127.
+Answer: -841469015.544
+
+Question: Let x(g) = 9*g + 1. Let q(c) = 2*c + 1. Let f(i) = 3*i - 39. Let w(j) = q(x(j)). Calculate f(w(a)).
+Answer: 54*a - 30
+
+Question: Let e(l) = l - 6. Is 2 a factor of both e(9) and 2?
+Answer: False
+
+Question: Let u(n) = -n**3 - n**2. Let e(c) = -2*c**3 + c. Let l(j) = -118*e(j) + 54*u(j). What is the derivative of l(a)?
+Answer: 546*a**2 - 108*a - 118
+
+Question: Three letters picked without replacement from qqqkkklkqkkk. Give prob of sequence qql.
+Answer: 1/110
+```
+
+## Pre-generated data
+
+[Pre-generated files](https://console.cloud.google.com/storage/browser/mathematics-dataset)
+
+### Version 1.0
+
+This is the version released with the original paper. It contains 2 million
+(question, answer) pairs per module, with questions limited to 160 characters in
+length, and answers to 30 characters in length. Note the training data for each
+question type is split into "train-easy", "train-medium", and "train-hard". This
+allows training models via a curriculum. The data can also be mixed together
+uniformly from these training datasets to obtain the results reported in the
+paper. Categories:
+
+* **algebra** (linear equations, polynomial roots, sequences)
+* **arithmetic** (pairwise operations and mixed expressions, surds)
+* **calculus** (differentiation)
+* **comparison** (closest numbers, pairwise comparisons, sorting)
+* **measurement** (conversion, working with time)
+* **numbers** (base conversion, remainders, common divisors and multiples,
+  primality, place value, rounding numbers)
+* **polynomials** (addition, simplification, composition, evaluating, expansion)
+* **probability** (sampling without replacement)
+
+## Getting the source
+
+### PyPI
+
+The easiest way to get the source is to use pip:
+
+```shell
+$ pip install mathematics_dataset
+```
+
+### From GitHub
+
+Alternately you can get the source by cloning the mathematics_dataset
+repository:
+
+```shell
+$ git clone https://github.com/deepmind/mathematics_dataset
+$ pip install --upgrade mathematics_dataset/
+```
+
+## Generating examples
+
+Generated examples can be printed to stdout via the `generate` script. For
+example:
+
+```shell
+python -m mathematics_dataset.generate --filter=linear_1d
+```
+
+will generate example (question, answer) pairs for solving linear equations in
+one variable.
+
+We've also included `generate_to_file.py` as an example of how to write the
+generated examples to text files. You can use this directly, or adapt it for
+your generation and training needs.
+
+## Dataset Metadata
+The following table is necessary for this dataset to be indexed by search
+engines such as <a href="https://g.co/datasetsearch">Google Dataset Search</a>.
+<div itemscope itemtype="http://schema.org/Dataset">
+<table>
+  <tr>
+    <th>property</th>
+    <th>value</th>
+  </tr>
+  <tr>
+    <td>name</td>
+    <td><code itemprop="name">Mathematics Dataset</code></td>
+  </tr>
+  <tr>
+    <td>url</td>
+    <td><code itemprop="url">https://github.com/deepmind/mathematics_dataset</code></td>
+  </tr>
+  <tr>
+    <td>sameAs</td>
+    <td><code itemprop="sameAs">https://github.com/deepmind/mathematics_dataset</code></td>
+  </tr>
+  <tr>
+    <td>description</td>
+    <td><code itemprop="description">This dataset consists of mathematical question and answer pairs, from a range
+of question types at roughly school-level difficulty. This is designed to test
+the mathematical learning and algebraic reasoning skills of learning models.\n
+\n
+## Example questions\n
+\n
+```\n
+Question: Solve -42*r + 27*c = -1167 and 130*r + 4*c = 372 for r.\n
+Answer: 4\n
+\n
+Question: Calculate -841880142.544 + 411127.\n
+Answer: -841469015.544\n
+\n
+Question: Let x(g) = 9*g + 1. Let q(c) = 2*c + 1. Let f(i) = 3*i - 39. Let w(j) = q(x(j)). Calculate f(w(a)).\n
+Answer: 54*a - 30\n
+```\n
+\n
+It contains 2 million
+(question, answer) pairs per module, with questions limited to 160 characters in
+length, and answers to 30 characters in length. Note the training data for each
+question type is split into "train-easy", "train-medium", and "train-hard". This
+allows training models via a curriculum. The data can also be mixed together
+uniformly from these training datasets to obtain the results reported in the
+paper. Categories:\n
+\n
+* **algebra** (linear equations, polynomial roots, sequences)\n
+* **arithmetic** (pairwise operations and mixed expressions, surds)\n
+* **calculus** (differentiation)\n
+* **comparison** (closest numbers, pairwise comparisons, sorting)\n
+* **measurement** (conversion, working with time)\n
+* **numbers** (base conversion, remainders, common divisors and multiples,\n
+  primality, place value, rounding numbers)\n
+* **polynomials** (addition, simplification, composition, evaluating, expansion)\n
+* **probability** (sampling without replacement)</code></td>
+  </tr>
+  <tr>
+    <td>provider</td>
+    <td>
+      <div itemscope itemtype="http://schema.org/Organization" itemprop="provider">
+        <table>
+          <tr>
+            <th>property</th>
+            <th>value</th>
+          </tr>
+          <tr>
+            <td>name</td>
+            <td><code itemprop="name">DeepMind</code></td>
+          </tr>
+          <tr>
+            <td>sameAs</td>
+            <td><code itemprop="sameAs">https://en.wikipedia.org/wiki/DeepMind</code></td>
+          </tr>
+        </table>
+      </div>
+    </td>
+  </tr>
+  <tr>
+    <td>citation</td>
+    <td><code itemprop="citation">https://identifiers.org/arxiv:1904.01557</code></td>
+  </tr>
+</table>
+</div>