mask_detection.ipynb

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    "# Mask Detection Demo\n",
    "The following example demonstrates an end-to-end data science workflow for building an image classifier model.<br/>\n",
    "The model is trained on a dataset containing images of people with or without masks.<br/>\n",
    "The model is then deployed to a Nuclio function allowing users to send an http request with an image and receive a \n",
    "response back with the probability that the person in the image is wearing a mask.\n",
    "\n",
    "## Key Technologies\n",
    "- [**Tensorflow-Keras**](https://www.tensorflow.org/api_docs/python/tf/keras) to train the model\n",
    "- [**Horovod**](https://horovod.ai/) to run distributed training\n",
    "- [**Nuclio**](https://nuclio.io/) to create a high-performance serverless Serving function\n",
    "- [**MLRun**](https://www.mlrun.org/) to orchestrate the process"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set up the Project and Environment\n",
    "Create a new project, set the environment and create the paths where we'll store the project's artifacts:"
   ]
  },
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       "('/home/jovyan/data/mask-detection',\n",
       " '/home/jovyan/data/mask-detection/dataset',\n",
       " '/home/jovyan/data/mask-detection/models')"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import mlrun\n",
    "import os\n",
    "\n",
    "project_name='mask-detection'\n",
    "project_dir = os.path.abspath('./')\n",
    "project = mlrun.new_project(project_name, project_dir)\n",
    "mlrun.set_environment(project=project.metadata.name)\n",
    "artifact_path = mlrun.mlconf.artifact_path\n",
    "\n",
    "code_dir = project_dir\n",
    "dataset_path = os.path.join(project_dir, 'dataset') \n",
    "model_path = os.path.join(project_dir,'models')\n",
    "code_dir, dataset_path, model_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import the Dataset\n",
    "[The MLRun functions marketplace](https://github.com/mlrun/functions/) (a.k.a. \"the MLRun functions hub\") is a \n",
    "centralized location for open-source contributions of function components that are commonly used in machine learning \n",
    "development.\n",
    "\n",
    "This step uses the [Open archive marketplace function](https://github.com/mlrun/functions/tree/master/open_archive), \n",
    "which opens a remote zip archive into a local folder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "open_archive_function = mlrun.import_function('hub://open_archive:development')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Run the Function**\n",
    "\n",
    "Note that we're setting the `local` param to `True` which means the function code will run locally inside the jupyter \n",
    "kernel. Alternatively, we could set it to `False` (the default), in which case MLRun would automatically spawn a k8s pod\n",
    "and run the function inside it, allowing us to isolate the function running environment and use our k8s cluster \n",
    "resources."
   ]
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     "text": [
      "> 2021-05-11 15:02:48,669 [info] starting run open-archive-open_archive uid=317dad445bea4b999dbc6f365cf6dba6 DB=http://mlrun-api:8080\n",
      "> 2021-05-11 15:02:48,737 [info] downloading https://s3.wasabisys.com/iguazio/data/mask-detection/Dataset.zip to local tmp\n"
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       "      <td>mask-detection</td>\n",
       "      <td><div title=\"317dad445bea4b999dbc6f365cf6dba6\"><a href=\"http://localhost:30060/projects/mask-detection/jobs/monitor/317dad445bea4b999dbc6f365cf6dba6/overview\" target=\"_blank\" >...5cf6dba6</a></div></td>\n",
       "      <td>0</td>\n",
       "      <td>May 11 15:02:48</td>\n",
       "      <td>completed</td>\n",
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     "text": [
      "to track results use .show() or .logs() or in CLI: \n",
      "!mlrun get run 317dad445bea4b999dbc6f365cf6dba6 --project mask-detection , !mlrun logs 317dad445bea4b999dbc6f365cf6dba6 --project mask-detection\n",
      "> 2021-05-11 15:04:18,328 [info] run executed, status=completed\n"
     ]
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   "source": [
    "open_archive_function.apply(mlrun.platforms.auto_mount())\n",
    "open_archive_function.run(handler='open_archive', \n",
    "                          params={'target_path' : dataset_path}, \n",
    "                          inputs={\"archive_url\": \"https://s3.wasabisys.com/iguazio/data/mask-detection/Dataset.zip\"},\n",
    "                          local=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train the Model\n",
    "The training code is basically the same as the code from [the kaggle project](https://www.kaggle.com/notadithyabhat/face-mask-detector/execution) \n",
    "with slight changes to allow us to use Horovod to do distributed training (more info [here](https://docs.mlrun.org/en/latest/runtimes/horovod.html)). \n",
    "The original training code can be found [here](training_code_original.py).\n",
    "\n",
    "Roughly, the changes I made to the training code were:\n",
    "- Code at the beginning to extract job params from MLRun context\n",
    "- Code to initialize Horovod and assign devices (CPU/GPU) before building the model\n",
    "- Replace to use the Horovod optimizer\n",
    "- Code at the end to log the results to MLRun DB\n",
    "\n",
    "In the following code sample, you can start to see **the value of MLRun**: with a simple value change, you can \n",
    "**distribute** your model **training** across **multiple workers** (i.e., perform distributed training), assign **GPUs**, \n",
    "and more. You don't need to bother with Dockerfiles or K8s YAML configuration files — MLRun does all of this for you."
   ]
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    "gpus = 0\n",
    "epochs = 5\n",
    "replicas = 1\n",
    "batch_size = 16\n",
    "\n",
    "image = 'mlrun/ml-models-gpu' if gpus else 'mlrun/ml-models'\n",
    "\n",
    "code_file = os.path.join(code_dir, 'training_code.py')\n",
    "trainer = mlrun.new_function(name='trainer',\n",
    "                             kind='mpijob',\n",
    "                             command=code_file,\n",
    "                             image=image)\n",
    "\n",
    "trainer.spec.replicas = replicas\n",
    "\n",
    "trainer.apply(mlrun.platforms.auto_mount())\n",
    "\n",
    "if gpus:\n",
    "    trainer.gpus(gpus)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Running the Function** <br/>\n",
    "Every function execution in MLRun is recorded in an object called **Run**, which enables us a good **tracking** of what\n",
    "we did: the **function inputs, outputs, logs, etc.** This lets us play with the different configurations, and later on \n",
    "examine which one was the best. Attached screenshot is from the MLRun UI, showing the history of the experiments, \n",
    "allowing you to compare the different runs, rerun them, monitor them and much more..."
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
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     "text": [
      "> 2021-05-11 15:07:23,230 [info] starting run trainer uid=d64289304bfc48b19e426e7f27b506e7 DB=http://mlrun-api:8080\n",
      "> 2021-05-11 15:07:33,375 [info] MpiJob trainer-6d4ea409 launcher pod trainer-6d4ea409-launcher state active\n",
      "+ POD_NAME=trainer-6d4ea409-worker-0\n",
      "+ shift\n",
      "+ /opt/kube/kubectl exec trainer-6d4ea409-worker-0 -- /bin/sh -c        PATH=/usr/local/bin:$PATH ; export PATH ; LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH ; export LD_LIBRARY_PATH ; DYLD_LIBRARY_PATH=/usr/local/lib:$DYLD_LIBRARY_PATH ; export DYLD_LIBRARY_PATH ;   /usr/local/bin/orted -mca ess \"env\" -mca ess_base_jobid \"2312568832\" -mca ess_base_vpid 1 -mca ess_base_num_procs \"2\" -mca orte_node_regex \"trainer-[1:6]d4ea409-launcher,trainer-[1:6]d4ea409-worker-0@0(2)\" -mca orte_hnp_uri \"2312568832.0;tcp://10.1.2.100:38389\" -mca plm \"rsh\" --tree-spawn -mca routed \"radix\" -mca orte_parent_uri \"2312568832.0;tcp://10.1.2.100:38389\" -mca plm_rsh_agent \"/etc/mpi/kubexec.sh\" -mca orte_default_hostfile \"/etc/mpi/hostfile\" -mca pmix \"^s1,s2,cray,isolated\"\n",
      "> 2021-05-11 15:07:40,841 [info] logging run results to: http://mlrun-api:8080\n",
      "Generating data in CSV format....\n",
      "Extracting each data into respective label folders....\n",
      "Done!\n",
      "Using device: CPU:0\n",
      "WARNING:tensorflow:`input_shape` is undefined or non-square, or `rows` is not in [96, 128, 160, 192, 224]. Weights for input shape (224, 224) will be loaded as the default.\n",
      "2021-05-11 15:07:43.839244: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA\n",
      "2021-05-11 15:07:43.861847: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 2599990000 Hz\n",
      "2021-05-11 15:07:43.862083: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x562f14b36d10 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",
      "2021-05-11 15:07:43.862100: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",
      "2021-05-11 15:07:43.862290: I tensorflow/core/common_runtime/process_util.cc:147] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.\n",
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/mobilenet_v2/mobilenet_v2_weights_tf_dim_ordering_tf_kernels_1.0_224_no_top.h5\n",
      "9412608/9406464 [==============================] - 8s 1us/step\n",
      "[INFO] compiling model...\n",
      "[INFO] training head...\n",
      "Epoch 1/5\n",
      "3/3 [==============================] - 7s 2s/step - loss: 1.3346 - accuracy: 0.5000 - val_loss: 0.9306 - val_accuracy: 0.5385\n",
      "Epoch 2/5\n",
      "3/3 [==============================] - 3s 901ms/step - loss: 1.1608 - accuracy: 0.4524 - val_loss: 0.7278 - val_accuracy: 0.7692\n",
      "Epoch 3/5\n",
      "3/3 [==============================] - 3s 912ms/step - loss: 0.9867 - accuracy: 0.5714 - val_loss: 0.6362 - val_accuracy: 0.8462\n",
      "Epoch 4/5\n",
      "3/3 [==============================] - 3s 885ms/step - loss: 0.7200 - accuracy: 0.7619 - val_loss: 0.6033 - val_accuracy: 0.8462\n",
      "Epoch 5/5\n",
      "3/3 [==============================] - 3s 898ms/step - loss: 0.7377 - accuracy: 0.6905 - val_loss: 0.5971 - val_accuracy: 0.8462\n",
      "> 2021-05-11 15:08:31,704 [info] history:\n",
      "MA: /home/jovyan/data/mask-detection/models\n",
      "final state: completed\n"
     ]
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       "\n",
       "        } finally {\n",
       "            document.body.removeChild(textarea);\n",
       "        }\n",
       "    }\n",
       "}\n",
       "function expandPanel(el) {\n",
       "  const panelName = \"#\" + el.getAttribute('paneName');\n",
       "  console.log(el.title);\n",
       "\n",
       "  document.querySelector(panelName + \"-title\").innerHTML = el.title\n",
       "  iframe = document.querySelector(panelName + \"-body\");\n",
       "\n",
       "  const tblcss = `<style> body { font-family: Arial, Helvetica, sans-serif;}\n",
       "    #csv { margin-bottom: 15px; }\n",
       "    #csv table { border-collapse: collapse;}\n",
       "    #csv table td { padding: 4px 8px; border: 1px solid silver;} </style>`;\n",
       "\n",
       "  function csvToHtmlTable(str) {\n",
       "    return '<div id=\"csv\"><table><tr><td>' +  str.replace(/[\\n\\r]+$/g, '').replace(/[\\n\\r]+/g, '</td></tr><tr><td>')\n",
       "      .replace(/,/g, '</td><td>') + '</td></tr></table></div>';\n",
       "  }\n",
       "\n",
       "  function reqListener () {\n",
       "    if (el.title.endsWith(\".csv\")) {\n",
       "      iframe.setAttribute(\"srcdoc\", tblcss + csvToHtmlTable(this.responseText));\n",
       "    } else {\n",
       "      iframe.setAttribute(\"srcdoc\", this.responseText);\n",
       "    }\n",
       "    console.log(this.responseText);\n",
       "  }\n",
       "\n",
       "  const oReq = new XMLHttpRequest();\n",
       "  oReq.addEventListener(\"load\", reqListener);\n",
       "  oReq.open(\"GET\", el.title);\n",
       "  oReq.send();\n",
       "\n",
       "\n",
       "  //iframe.src = el.title;\n",
       "  const resultPane = document.querySelector(panelName + \"-pane\");\n",
       "  if (resultPane.classList.contains(\"hidden\")) {\n",
       "    resultPane.classList.remove(\"hidden\");\n",
       "  }\n",
       "}\n",
       "function closePanel(el) {\n",
       "  const panelName = \"#\" + el.getAttribute('paneName')\n",
       "  const resultPane = document.querySelector(panelName + \"-pane\");\n",
       "  if (!resultPane.classList.contains(\"hidden\")) {\n",
       "    resultPane.classList.add(\"hidden\");\n",
       "  }\n",
       "}\n",
       "\n",
       "</script>\n",
       "<div class=\"master-wrapper\">\n",
       "  <div class=\"block master-tbl\"><div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>project</th>\n",
       "      <th>uid</th>\n",
       "      <th>iter</th>\n",
       "      <th>start</th>\n",
       "      <th>state</th>\n",
       "      <th>name</th>\n",
       "      <th>labels</th>\n",
       "      <th>inputs</th>\n",
       "      <th>parameters</th>\n",
       "      <th>results</th>\n",
       "      <th>artifacts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>mask-detection</td>\n",
       "      <td><div title=\"d64289304bfc48b19e426e7f27b506e7\"><a href=\"http://localhost:30060/projects/mask-detection/jobs/monitor/d64289304bfc48b19e426e7f27b506e7/overview\" target=\"_blank\" >...27b506e7</a></div></td>\n",
       "      <td>0</td>\n",
       "      <td>May 11 15:07:40</td>\n",
       "      <td>completed</td>\n",
       "      <td>trainer</td>\n",
       "      <td><div class=\"dictlist\">kind=mpijob</div><div class=\"dictlist\">owner=jovyan</div><div class=\"dictlist\">mlrun/job=trainer-6d4ea409</div><div class=\"dictlist\">host=trainer-6d4ea409-worker-0</div></td>\n",
       "      <td></td>\n",
       "      <td><div class=\"dictlist\">epochs=5</div><div class=\"dictlist\">batch_size=16</div><div class=\"dictlist\">images=/home/jovyan/data/mask-detection/dataset/images</div><div class=\"dictlist\">annotations=/home/jovyan/data/mask-detection/dataset/annotations</div><div class=\"dictlist\">model_artifacts=/home/jovyan/data/mask-detection/models</div><div class=\"dictlist\">image_width=224</div><div class=\"dictlist\">image_height=224</div><div class=\"dictlist\">image_channels=3</div><div class=\"dictlist\">random_state=1</div><div class=\"dictlist\">test_size=0.3</div></td>\n",
       "      <td><div class=\"dictlist\">loss=0.7377297878265381</div><div class=\"dictlist\">accuracy=0.6904761791229248</div></td>\n",
       "      <td><div class=\"artifact\" onclick=\"expandPanel(this)\" paneName=\"resultb6e85b95\" title=\"/files/data/mask-detection/models/training-summary.html\">summary.html</div><div title=\"/home/jovyan/data/mask-detection/models/model-weights.h5\">model-weights</div><div title=\"/home/jovyan/data/mask-detection/models\">model</div></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div></div>\n",
       "  <div id=\"resultb6e85b95-pane\" class=\"right-pane block hidden\">\n",
       "    <div class=\"pane-header\">\n",
       "      <span id=\"resultb6e85b95-title\" class=\"pane-header-title\">Title</span>\n",
       "      <span onclick=\"closePanel(this)\" paneName=\"resultb6e85b95\" class=\"close clickable\">&times;</span>\n",
       "    </div>\n",
       "    <iframe class=\"fileview\" id=\"resultb6e85b95-body\"></iframe>\n",
       "  </div>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "to track results use .show() or .logs() or in CLI: \n",
      "!mlrun get run d64289304bfc48b19e426e7f27b506e7 --project mask-detection , !mlrun logs d64289304bfc48b19e426e7f27b506e7 --project mask-detection\n",
      "> 2021-05-11 15:09:01,051 [info] run executed, status=completed\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<mlrun.model.RunObject at 0x7f17e87fc100>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.run(params={'epochs'         : epochs,\n",
    "                    'batch_size'     : batch_size,\n",
    "                    'images'         : dataset_path + '/images',\n",
    "                    'annotations'    : dataset_path + '/annotations',\n",
    "                    'model_artifacts': model_path})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"MLRun-ui-screenshot.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Deploying the Model\n",
    "\n",
    "This time we're using the [tensorflow v2 serving function](https://github.com/mlrun/functions/tree/master/tf2_serving) \n",
    "from the hub.\n",
    "The serving function kind is using [Nuclio](https://github.com/nuclio/nuclio/): a high-performance serverless event \n",
    "and data processing open-source platform.\n",
    "With just a few lines of code we can take our model, **expose** it with an **http endpoint** and deploy it on \n",
    "**high-performance** infrastructure that can easily scale up to serve on a **production environment** with hundreds of \n",
    "thousands of requests per second."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mlrun.runtimes.serving.ServingRuntime at 0x7f180161b7f0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "serving_function = mlrun.import_function('hub://tf2_serving_v2:development')\n",
    "serving_function.apply(mlrun.platforms.auto_mount())\n",
    "serving_function.add_model('mask-detection-model', model_path, class_name='TFModel')\n",
    "function_envs = {\n",
    "    'IMAGE_HEIGHT': 224,\n",
    "    'IMAGE_WIDTH': 224,\n",
    "}\n",
    "serving_function.set_envs(function_envs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "> 2021-05-11 15:09:10,460 [info] Starting remote function deploy\n",
      "2021-05-11 15:09:10  (info) Deploying function\n",
      "2021-05-11 15:09:10  (info) Building\n",
      "2021-05-11 15:09:10  (info) Staging files and preparing base images\n",
      "2021-05-11 15:09:10  (info) Building processor image\n",
      "2021-05-11 15:09:22  (info) Build complete\n",
      "2021-05-11 15:09:36  (info) Function deploy complete\n",
      "> 2021-05-11 15:09:37,411 [info] function deployed, address=192.168.65.4:31960\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'http://192.168.65.4:31960'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "serving_function.deploy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using the Model\n",
    "Here's a demonstration how to send an image to our serving function API, and see the model's prediction of the \n",
    "probability that the people in the image are wearing a mask."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f178ea16c70>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "image_url = 'https://unsplash.com/photos/hB_gwZCEIfs/download?force=true&w=640'\n",
    "response = requests.get(image_url)\n",
    "plt.imshow(Image.open(BytesIO(response.content)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mask weared incorrectly probability: 0.0973595345020294\n",
      "with mask probability: 0.8526288318634033\n",
      "without mask probability: 0.050011624321341515\n",
      "\n"
     ]
    }
   ],
   "source": [
    "response = serving_function.invoke(path='v2/models/mask-detection-model/predict', body={\"data_url\" : image_url})\n",
    "print(f\"\"\"\n",
    "mask weared incorrectly probability: {response['outputs'][0]}\n",
    "with mask probability: {response['outputs'][1]}\n",
    "without mask probability: {response['outputs'][2]}\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving Time and Effort\n",
    "It’s a very exciting time to be working in machine learning, because there are so many great use cases that are just \n",
    "waiting to be productized. Operationalizing a data science project can balloon in complexity, fast. That’s why planning \n",
    "an MLOps strategy is a critical initial stage. The right framework--MLRun in this case--can be a force multiplier, \n",
    "enabling you to take existing training code and quickly build it into a full production-ready application. With just \n",
    "200 lines of code, we were able to distribute our training, track our trials, and deploy our final model on \n",
    "production-scale infrastructure.\n",
    " \n",
    "MLRun has even more to offer, like function versioning, experiment tracking, feature store, automatic pipeline \n",
    "scheduling, model monitoring and more. \n",
    "\n",
    "We invite you to join our upcoming global virtual Hackathon for Good, where ML teams will compete to build ML solutions\n",
    "with a real-world impact.\n",
    "\n",
    "\n",
    "### The author\n",
    "Hedi Ingber is the main maintainer of MLRun. He's also a Backend Engineer at Iguazio, which offers the enterprise \n",
    "version of MLRun.\n",
    " "
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