Added Notebooks

ML Engineering MLFlow/02. Data Science Workbench/.gitignore

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+mlruns
+.ipynb_checkpoints

ML Engineering MLFlow/02. Data Science Workbench/notebooks/mlflow.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# IMPORTING MODULES:\n",
+    "import mlflow"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2022/08/22 21:03:52 INFO mlflow.tracking.fluent: Experiment with name 'mlflow_experiments' does not exist. Creating a new experiment.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# RUNNING MLFLOW:\n",
+    "mlflow.set_experiment(\"mlflow_experiments\")\n",
+    "with mlflow.start_run():\n",
+    "    mlflow.log_param(\"name\", \"mlflow_test\")\n",
+    "    mlflow.log_param(\"category\", \"algorithm\")\n",
+    "    mlflow.log_param(\"type\", \"classification\")\n",
+    "    for i in range(5):\n",
+    "        mlflow.log_metric(\"i\", i, step=i)\n",
+    "    mlflow.log_artifact(\"mlflow.ipynb\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.4 64-bit",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.4"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

ML Engineering MLFlow/02. Data Science Workbench/notebooks/randomizer_model/MLmodel

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+flavors:
+  python_function:
+    cloudpickle_version: 2.1.0
+    env: conda.yaml
+    loader_module: mlflow.pyfunc.model
+    python_model: python_model.pkl
+    python_version: 3.10.4
+mlflow_version: 1.26.1
+model_uuid: 02c1b2316ae945da8660d2089dd5dc43
+utc_time_created: '2022-08-27 06:12:05.575524'

ML Engineering MLFlow/02. Data Science Workbench/notebooks/randomizer_model/conda.yaml

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+channels:
+- conda-forge
+dependencies:
+- python=3.10.4
+- pip<=22.2.1
+- pip:
+  - mlflow
+  - cloudpickle==2.1.0
+name: mlflow-env

ML Engineering MLFlow/02. Data Science Workbench/notebooks/randomizer_model/python_env.yaml

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+python: 3.10.4
+build_dependencies:
+- pip==22.2.1
+- setuptools==58.3.0
+- wheel==0.37.1
+dependencies:
+- -r requirements.txt

ML Engineering MLFlow/02. Data Science Workbench/notebooks/randomizer_model/requirements.txt

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+mlflow
+cloudpickle==2.1.0

ML Engineering MLFlow/02. Data Science Workbench/notebooks/stockpred.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# IMPORTING MODULES:\n",
+    "import random\n",
+    "import mlflow\n",
+    "import pandas as pd\n",
+    "from mlflow.pyfunc.model import PythonModel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# DEFINING THE PYTHON MODEL:\n",
+    "class RandomPredictor(PythonModel): # Defining the model.\n",
+    "    def __init__(self): # Initializing contructor function.\n",
+    "        pass\n",
+    "\n",
+    "    def predict(self, context, model_input): # Defining predict function. \n",
+    "        return model_input.apply(lambda x: random.randint(0, 1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# INITIALIZING AND SAVING THE MODEL:\n",
+    "model_path = \"randomizer_model\" # Initialization.\n",
+    "model = RandomPredictor() # Initializing the model.\n",
+    "mlflow.pyfunc.save_model(path=model_path, python_model=model) # Saving the model. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model loaded successfully\n"
+     ]
+    }
+   ],
+   "source": [
+    "# LOADING THE MODEL:\n",
+    "loaded_model = mlflow.pyfunc.load_model(model_path) # Loading the model.\n",
+    "print(\"Model loaded successfully\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2022/08/27 11:57:38 INFO mlflow.tracking.fluent: Experiment with name 'stockpred_experiment' does not exist. Creating a new experiment.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# IMPLEMENTATION OF THE MODEL:\n",
+    "model_input = pd.DataFrame([range(10)]) # Initializing input example.\n",
+    "mlflow.set_experiment(\"stockpred_experiment\") # Initializing mlflow experiment.\n",
+    "with mlflow.start_run():\n",
+    "    model_output = loaded_model.predict(model_input) # Implementation of the model.\n",
+    "    mlflow.log_metric(\"Days Up\", model_output.sum())\n",
+    "    mlflow.log_artifact(\"stockpred.ipynb\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.4 64-bit",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.4"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}