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Merge pull request #382 from v3io/development
Fix demo links
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‎README.md

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@@ -102,7 +102,7 @@ For full usage instructions, run the script with the `-h` or `--help` flag:
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<a href="demos/mask-detection/README.md"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/tree/1.3.x-latest/mask-detection/">
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<a target="_blank" href="https://github.com/mlrun/demos/tree/release/1.3.x-latest/mask-detection/">
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<img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>This demo contains 3 notebooks where we:
@@ -117,7 +117,7 @@ For full usage instructions, run the script with the `-h` or `--help` flag:
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<a href="demos/fraud-prevention-feature-store/README.md"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/blob/1.3.x-latest/fraud-prevention-feature-store/">
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<a target="_blank" href="https://github.com/mlrun/demos/blob/release/1.3.x-latest/fraud-prevention-feature-store/">
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<img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>Demonstrates the feature store usage for fraud prevention: Data ingestion & preparation; Model training & testing; Model serving; Building An Automated ML Pipeline.
@@ -129,7 +129,7 @@ For full usage instructions, run the script with the `-h` or `--help` flag:
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<a href="demos/news-article-nlp/README.md"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/tree/1.3.x-latest/news-article-nlp/"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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<a target="_blank" href="https://github.com/mlrun/demos/tree/release/1.3.x-latest/news-article-nlp/"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>This demo creates an NLP pipeline that summarizes and extract keywords from a news article URL. We will be using state-of-the-art transformer models. such as BERT. to perform these NLP tasks.
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Additionally, we will use MLRun's real-time inference graphs to create the pipeline. This allows for easy containerization and deployment of the pipeline on top of a production-ready Kubernetes cluster.
@@ -141,7 +141,7 @@ Additionally, we will use MLRun's real-time inference graphs to create the pipel
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<a href="demos/network-operations/README.md"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/tree/1.3.x-latest/network-operations/"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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<a target="_blank" href="https://github.com/mlrun/demos/tree/release/1.3.x-latest/network-operations/"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>This demo demonstrates how to build an automated machine-learning (ML) pipeline for predicting network outages based on network-device telemetry, also known as Network Operations (NetOps).
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The demo implements feature engineering, model training, testing, inference, and model monitoring (with concept-drift detection).
@@ -154,7 +154,7 @@ The demo uses a offline/real-time metrics simulator to generate semi-random netw
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<a href="demosstocke-prediction/README.md"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/tree/1.3.x-latest/stocks-prediction/"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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<a target="_blank" href="https://github.com/mlrun/demos/tree/release/1.3.x-latest/stocks-prediction/"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>This demo illustrates using Iguazio's latest technologies and methods for model serving, the platform feature store, and the MLRun frameworks (sub-modules for the most commonly
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used machine and deep learning frameworks, providing features such as automatic logging, model management, and distributed training). The demo predicts stock prices,
@@ -180,7 +180,7 @@ The demo uses a offline/real-time metrics simulator to generate semi-random netw
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<a href="demos/howto/converting-to-mlrun/mlrun-code.ipynb"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/tree/1.3.x-latest/howto/converting-to-mlrun"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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<a target="_blank" href="https://github.com/mlrun/demos/tree/release/v1.3.x-latest/howto/converting-to-mlrun"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>Demonstrates how to convert existing ML code to an MLRun project.
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The demo implements an MLRun project for taxi ride-fare prediction based on a <a href="https://www.kaggle.com/jsylas/python-version-of-top-ten-rank-r-22-m-2-88">Kaggle notebook</a> with an ML Python script that uses data from the <a href="https://www.kaggle.com/c/new-york-city-taxi-fare-prediction">New York City Taxi Fare Prediction competition</a>.
@@ -192,7 +192,7 @@ The demo uses a offline/real-time metrics simulator to generate semi-random netw
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<a href="demos/howto/spark/spark-mlrun-read-csv.ipynb"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/blob/1.3.x-latest/howto/spark/spark-mlrun-read-csv.ipynb"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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<a target="_blank" href="https://github.com/mlrun/demos/blob/release/1.3.x-latest/howto/spark/spark-mlrun-read-csv.ipynb"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>Demonstrates how to run a Spark job that reads a CSV file and logs the data set to an MLRun database.
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</td>
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<a href="demos/howto/spark/spark-mlrun-describe.ipynb"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/blob/1.3.x-latest/howto/spark/spark-mlrun-describe.ipynb"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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<a target="_blank" href="https://github.com/mlrun/demos/blob/release/1.3.x-latest/howto/spark/spark-mlrun-describe.ipynb"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>Demonstrates how to create and run a Spark job that generates a profile report from an Apache Spark DataFrame based on pandas profiling.
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</td>
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<a href="demos/howto/spark/spark-operator.ipynb"><img src="./assets/images/Jupyter-Logo-32px.png"/><br>Open locally</a>
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</td>
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<td align="center", style="min-width:45px; padding: 10px;">
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<a target="_blank" href="https://github.com/mlrun/demos/blob/1.3.x-latest/howto/spark/spark-operator.ipynb"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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<a target="_blank" href="https://github.com/mlrun/demos/blob/release/1.3.x-latest/howto/spark/spark-operator.ipynb"><img src="./assets/images/GitHub-Mark-32px.png"/><br>View on GitHub</a>
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</td>
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<td>Demonstrates how to use <a target="_blank" href="https://github.com/GoogleCloudPlatform/spark-on-k8s-operator">Spark Operator</a> to run a Spark job over Kubernetes with MLRun.
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</td>

‎welcome.ipynb

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" <a href=\"demos/mask-detection/README.md\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/1.3.x-latest/mask-detection/\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/release/1.3.x-latest/mask-detection/\">\n",
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" <img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>This demo contains 3 notebooks where we:\n",
@@ -210,7 +210,7 @@
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" <a href=\"demos/fraud-prevention-feature-store/README.md\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/1.3.x-latest/fraud-prevention-feature-store/\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/release/1.3.x-latest/fraud-prevention-feature-store/\">\n",
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" <img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>Demonstrates the feature store usage for fraud prevention: Data ingestion & preparation; Model training & testing; Model serving; Building An Automated ML Pipeline.\n",
@@ -222,7 +222,7 @@
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" <a href=\"demos/news-article-nlp/README.md\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/1.3.x-latest/news-article-nlp/\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/release/1.3.x-latest/news-article-nlp/\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>This demo creates an NLP pipeline that summarizes and extract keywords from a news article URL. We will be using state-of-the-art transformer models. such as BERT. to perform these NLP tasks.\n",
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"Additionally, we will use MLRun's real-time inference graphs to create the pipeline. This allows for easy containerization and deployment of the pipeline on top of a production-ready Kubernetes cluster.\n",
@@ -234,7 +234,7 @@
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" <a href=\"demos/network-operations/README.md\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/1.3.x-latest/network-operations/\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/release/1.3.x-latest/network-operations/\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>This demo demonstrates how to build an automated machine-learning (ML) pipeline for predicting network outages based on network-device telemetry, also known as Network Operations (NetOps).\n",
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"The demo implements feature engineering, model training, testing, inference, and model monitoring (with concept-drift detection).\n",
@@ -247,7 +247,7 @@
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" <a href=\"demosstocke-prediction/README.md\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/1.3.x-latest/stocks-prediction/\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/release/1.3.x-latest/stocks-prediction/\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>This demo illustrates using Iguazio's latest technologies and methods for model serving, the platform feature store, and the MLRun frameworks (sub-modules for the most commonly \n",
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"\t\tused machine and deep learning frameworks, providing features such as automatic logging, model management, and distributed training). The demo predicts stock prices, \n",
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" <a href=\"demos/howto/converting-to-mlrun/mlrun-code.ipynb\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/1.3.x-latest/howto/converting-to-mlrun\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/tree/release/v1.3.x-latest/howto/converting-to-mlrun\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>Demonstrates how to convert existing ML code to an MLRun project.\n",
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" The demo implements an MLRun project for taxi ride-fare prediction based on a <a href=\"https://www.kaggle.com/jsylas/python-version-of-top-ten-rank-r-22-m-2-88\">Kaggle notebook</a> with an ML Python script that uses data from the <a href=\"https://www.kaggle.com/c/new-york-city-taxi-fare-prediction\">New York City Taxi Fare Prediction competition</a>.\n",
@@ -301,7 +301,7 @@
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" <a href=\"demos/howto/spark/spark-mlrun-read-csv.ipynb\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/1.3.x-latest/howto/spark/spark-mlrun-read-csv.ipynb\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/release/1.3.x-latest/howto/spark/spark-mlrun-read-csv.ipynb\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>Demonstrates how to run a Spark job that reads a CSV file and logs the data set to an MLRun database.\n",
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" </td>\n",
@@ -312,7 +312,7 @@
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" <a href=\"demos/howto/spark/spark-mlrun-describe.ipynb\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/1.3.x-latest/howto/spark/spark-mlrun-describe.ipynb\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/release/1.3.x-latest/howto/spark/spark-mlrun-describe.ipynb\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>Demonstrates how to create and run a Spark job that generates a profile report from an Apache Spark DataFrame based on pandas profiling.\n",
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" </td>\n",
@@ -323,7 +323,7 @@
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" <a href=\"demos/howto/spark/spark-operator.ipynb\"><img src=\"./assets/images/Jupyter-Logo-32px.png\"/><br>Open locally</a>\n",
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" </td>\n",
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" <td align=\"center\", style=\"min-width:45px; padding: 10px;\">\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/1.3.x-latest/howto/spark/spark-operator.ipynb\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" <a target=\"_blank\" href=\"https://github.com/mlrun/demos/blob/release/1.3.x-latest/howto/spark/spark-operator.ipynb\"><img src=\"./assets/images/GitHub-Mark-32px.png\"/><br>View on GitHub</a>\n",
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" </td>\n",
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" <td>Demonstrates how to use <a target=\"_blank\" href=\"https://github.com/GoogleCloudPlatform/spark-on-k8s-operator\">Spark Operator</a> to run a Spark job over Kubernetes with MLRun.\n",
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" </td>\n",

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