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Merged
joshterrill merged 1 commit into from
Mar 13, 2026
Merged

fixed spelling #186

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8 changes: 4 additions & 4 deletions crypto/example_model.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
Expand All @@ -46,7 +46,7 @@
],
"source": [
"# Install dependencies\n",
"!pip install -q --upgrade numerapi pandas pyarrow matplotlib lightgbm scikit-learn scipy cloudpickle==3.1.1\n",
"!pip install -q --upgrade numerapi pandas pyarrow matplotlib lightgbm scikit-learn scipy cloudpickle==2.2.1\n",
"!pip install -q --no-deps numerai-tools"
]
},
Expand Down Expand Up @@ -3719,7 +3719,7 @@
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"display_name": "3.10.18",
"language": "python",
"name": "python3"
},
Expand All @@ -3733,7 +3733,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.11"
"version": "3.10.18"
},
"orig_nbformat": 4
},
Expand Down
156 changes: 95 additions & 61 deletions numerai/example_model.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,75 +11,136 @@
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2025-12-14T21:23:24.577253Z",
"start_time": "2025-12-14T21:23:24.420881Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"execution": {
"iopub.execute_input": "2026-03-04T09:50:06.921017Z",
"iopub.status.busy": "2026-03-04T09:50:06.920633Z",
"iopub.status.idle": "2026-03-04T09:50:07.111156Z",
"shell.execute_reply": "2026-03-04T09:50:07.110785Z"
},
"id": "Ekw8Z93ljC3v",
"outputId": "bdd16698-2ad0-4423-b090-c5ce55fe3053",
"ExecuteTime": {
"end_time": "2025-12-14T21:23:24.577253Z",
"start_time": "2025-12-14T21:23:24.420881Z"
}
"outputId": "bdd16698-2ad0-4423-b090-c5ce55fe3053"
},
"source": [
"!python --version"
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Python 3.11.11\r\n"
"Python 3.12.11\r\n"
]
}
],
"execution_count": 1
"source": [
"!python --version"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2025-12-14T21:23:25.628662Z",
"start_time": "2025-12-14T21:23:24.578722Z"
},
"colab": {
"base_uri": "https://localhost:8080/"
},
"execution": {
"iopub.execute_input": "2026-03-04T09:50:07.112715Z",
"iopub.status.busy": "2026-03-04T09:50:07.112578Z",
"iopub.status.idle": "2026-03-04T09:50:08.208975Z",
"shell.execute_reply": "2026-03-04T09:50:08.208610Z"
},
"id": "yoy_wT1rhMqF",
"outputId": "e038b50f-1b61-4334-be62-28f4dc40a0a0",
"ExecuteTime": {
"end_time": "2025-12-14T21:23:25.628662Z",
"start_time": "2025-12-14T21:23:24.578722Z"
}
"outputId": "e038b50f-1b61-4334-be62-28f4dc40a0a0"
},
"source": [
"# Install dependencies\n",
"!pip install -q --upgrade numerapi pandas pyarrow matplotlib lightgbm scikit-learn scipy cloudpickle==3.1.1"
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m A new release of pip is available: \u001B[0m\u001B[31;49m25.2\u001B[0m\u001B[39;49m -> \u001B[0m\u001B[32;49m25.3\u001B[0m\r\n",
"\u001B[1m[\u001B[0m\u001B[34;49mnotice\u001B[0m\u001B[1;39;49m]\u001B[0m\u001B[39;49m To update, run: \u001B[0m\u001B[32;49mpip install --upgrade pip\u001B[0m\r\n"
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m26.0.1\u001b[0m\r\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\r\n"
]
}
],
"execution_count": 2
"source": [
"# Install dependencies\n",
"!pip install -q --upgrade numerapi pandas pyarrow matplotlib lightgbm scikit-learn scipy cloudpickle==2.2.1"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2025-12-14T21:28:28.979818Z",
"start_time": "2025-12-14T21:23:25.629875Z"
},
"colab": {
"base_uri": "https://localhost:8080/",
"height": 160
},
"execution": {
"iopub.execute_input": "2026-03-04T09:50:08.210682Z",
"iopub.status.busy": "2026-03-04T09:50:08.210563Z",
"iopub.status.idle": "2026-03-04T09:50:28.439383Z",
"shell.execute_reply": "2026-03-04T09:50:28.438971Z"
},
"id": "13hdRk9ghMqI",
"outputId": "d2274374-fd85-4189-f27b-d9d466cc63ca",
"ExecuteTime": {
"end_time": "2025-12-14T21:28:28.979818Z",
"start_time": "2025-12-14T21:23:25.629875Z"
}
"outputId": "d2274374-fd85-4189-f27b-d9d466cc63ca"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2026-03-04 01:50:09,132 INFO numerapi.utils: target file already exists\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2026-03-04 01:50:09,133 INFO numerapi.utils: download complete\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2026-03-04 01:50:09,575 INFO numerapi.utils: target file already exists\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2026-03-04 01:50:09,577 INFO numerapi.utils: download complete\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001699 seconds.\n",
"You can set `force_row_wise=true` to remove the overhead.\n",
"And if memory is not enough, you can set `force_col_wise=true`.\n",
"[LightGBM] [Info] Total Bins 210\n",
"[LightGBM] [Info] Number of data points in the train set: 688182, number of used features: 42\n",
"[LightGBM] [Info] Start training from score 0.499948\n"
]
}
],
"source": [
"from numerapi import NumerAPI\n",
"import pandas as pd\n",
Expand Down Expand Up @@ -155,53 +216,27 @@
" files.download('example_model.pkl')\n",
"except:\n",
" pass"
],
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2025-12-14 13:23:26,450 INFO numerapi.utils: target file already exists\n",
"2025-12-14 13:23:26,452 INFO numerapi.utils: starting download\n",
"v5.2/train.parquet: 7.67GB [04:40, 27.4MB/s] \n",
"2025-12-14 13:28:07,043 INFO numerapi.utils: target file already exists\n",
"2025-12-14 13:28:07,045 INFO numerapi.utils: download complete\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001209 seconds.\n",
"You can set `force_row_wise=true` to remove the overhead.\n",
"And if memory is not enough, you can set `force_col_wise=true`.\n",
"[LightGBM] [Info] Total Bins 210\n",
"[LightGBM] [Info] Number of data points in the train set: 688184, number of used features: 42\n",
"[LightGBM] [Info] Start training from score 0.499946\n"
]
}
],
"execution_count": 3
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2025-12-14T21:28:28.982147Z",
"start_time": "2025-12-14T21:28:28.980721Z"
}
},
"cell_type": "code",
"source": "",
"outputs": [],
"execution_count": 3
"source": []
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "venv",
"display_name": "3.12.8",
"language": "python",
"name": "python3"
},
Expand All @@ -215,9 +250,8 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
},
"orig_nbformat": 4
"version": "3.13.5"
}
},
"nbformat": 4,
"nbformat_minor": 0
Expand Down
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