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    <title>topic ML for predictive maintenence use cases?! in Machine Learning</title>
    <link>https://community.databricks.com/t5/machine-learning/ml-for-predictive-maintenence-use-cases/m-p/121400#M4113</link>
    <description>&lt;P&gt;How are you using ML to help determine predictive maintenance needs for your systems or operations?&lt;/P&gt;</description>
    <pubDate>Tue, 10 Jun 2025 23:22:06 GMT</pubDate>
    <dc:creator>LDogg</dc:creator>
    <dc:date>2025-06-10T23:22:06Z</dc:date>
    <item>
      <title>ML for predictive maintenence use cases?!</title>
      <link>https://community.databricks.com/t5/machine-learning/ml-for-predictive-maintenence-use-cases/m-p/121400#M4113</link>
      <description>&lt;P&gt;How are you using ML to help determine predictive maintenance needs for your systems or operations?&lt;/P&gt;</description>
      <pubDate>Tue, 10 Jun 2025 23:22:06 GMT</pubDate>
      <guid>https://community.databricks.com/t5/machine-learning/ml-for-predictive-maintenence-use-cases/m-p/121400#M4113</guid>
      <dc:creator>LDogg</dc:creator>
      <dc:date>2025-06-10T23:22:06Z</dc:date>
    </item>
    <item>
      <title>Re: ML for predictive maintenence use cases?!</title>
      <link>https://community.databricks.com/t5/machine-learning/ml-for-predictive-maintenence-use-cases/m-p/121587#M4115</link>
      <description>&lt;P&gt;Hi&amp;nbsp;&lt;a href="https://community.databricks.com/t5/user/viewprofilepage/user-id/168164"&gt;@LDogg&lt;/a&gt;,&amp;nbsp;&lt;/P&gt;&lt;P&gt;You can do predictive maintenance something like this:&lt;/P&gt;&lt;P&gt;Start by streaming sensor or IoT data like temperature, pressure, vibration, etc. into Delta Lake using tools like Structured Streaming or Delta Live Tables.&lt;/P&gt;&lt;P&gt;Next, we can process and engineer features, for example, rolling averages, trend detection, or sudden spikes using Spark and Pandas UDFs.&lt;/P&gt;&lt;P&gt;Then, we can use AutoML or build custom machine learning models like classification, anomaly detection, or time-series forecasting to predict potential failures.&lt;/P&gt;&lt;P&gt;Once the model is ready, we can run it in real-time on incoming data or as a scheduled batch job to flag any risks early.&lt;/P&gt;&lt;P&gt;With MLflow, we can track the experiments, manage model versions, monitor performance, and even automate retraining if needed.&lt;/P&gt;</description>
      <pubDate>Thu, 12 Jun 2025 11:00:19 GMT</pubDate>
      <guid>https://community.databricks.com/t5/machine-learning/ml-for-predictive-maintenence-use-cases/m-p/121587#M4115</guid>
      <dc:creator>SP_6721</dc:creator>
      <dc:date>2025-06-12T11:00:19Z</dc:date>
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