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[ DevCourseWeb com ] Udemy - Azure Databricks - Build data engineering and AI - ML pipeline
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01 - Introduction
001 Introduction.mp4
001 Introduction_en.srt
002 Prerequisite.mp4
002 Prerequisite_en.srt
003 Importing Notebooks into Databricks workspace.mp4
003 Importing Notebooks into Databricks workspace_en.srt
38033216-Introduction.pptx
02 - Introduction to anomaly detection
001 Introduction.mp4
001 Introduction_en.srt
002 Density based outlier detection.mp4
002 Density based outlier detection_en.srt
003 Support vector machine.mp4
003 Support vector machine_en.srt
004 Isolation Forest.mp4
004 Isolation Forest_en.srt
38033346-Anomaly-detection.pptx
03 - Anomaly detection-LAB
001 Clustering based approach.mp4
001 Clustering based approach_en.srt
002 Angle based approach.mp4
002 Angle based approach_en.srt
003 Feature bagging.mp4
003 Feature bagging_en.srt
004 KNN.mp4
004 KNN_en.srt
005 Local outlier factor.mp4
005 Local outlier factor_en.srt
006 PCA based approach.mp4
006 PCA based approach_en.srt
38033564-Clustering-based-outlier-detection.ipynb
38033580-Angle-based-outlier-detection.ipynb
38033582-Sample-Superstore.xls
38033584-train.csv
38033610-Feature-bagging.ipynb
38033624-k-Nearest-Neighbors-based-anomaly-detection.ipynb
38033640-Anomaly-detection-using-LOF.ipynb
38033658-Anomaly-detection-using-Principle-component-analysis.ipynb
04 - Data Lake house architecture
001 Data lake.mp4
001 Data lake_en.srt
002 Delta Lake.mp4
002 Delta Lake_en.srt
003 Elements of delta lake.mp4
003 Elements of delta lake_en.srt
004 Delta lake - LAB.mp4
004 Delta lake - LAB_en.srt
38033754-Lakehouse.pptx
38033818-Delta-lake-ingest-LAB.dbc
38033828-Iot-sensor-data.csv
05 - Build Data pipeline using Azure tech stack
001 Architecture design overview.mp4
001 Architecture design overview_en.srt
002 Upload files to DBFS.mp4
002 Upload files to DBFS_en.srt
003 Streaming concepts.mp4
003 Streaming concepts_en.srt
004 Autoloader concepts.mp4
004 Autoloader concepts_en.srt
005 Mounting DBFS File location.mp4
005 Mounting DBFS File location_en.srt
006 Data walkthrough.mp4
006 Data walkthrough_en.srt
007 Autoloader LAB.mp4
007 Autoloader LAB_en.srt
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38033872-Architecture.pptx
38033908-Streaming-Concepts.dbc
38033918-AUTOLOADER.pptx
38035402-Blob-storage-structure.png
38035414-Blob-Storage-Bronze-table-view.png
38035494-Autoloader.dbc
Sreaming json data
1.json
10.json
11.json
12.json
13.json
14.json
15.json
16.json
17.json
18.json
19.json
2.json
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9.json
06 - Explainable AI
001 Anomaly detection using Isolation forest.mp4
001 Anomaly detection using Isolation forest_en.srt
002 Model interpretation introduction.mp4
002 Model interpretation introduction_en.srt
003 Model interpretation using Shapley value.mp4
003 Model interpretation using Shapley value_en.srt
004 Model interpretation using Shapley values-2.mp4
004 Model interpretation using Shapley values-2_en.srt
38035610-Anomaly-detection-on-transactional-data.ipynb
38035622-processed.csv
38035750-Model-interpretation.ipynb
38035798-Udemy-course-ppt-model-interpreattion.pptx
07 - Spark Structured streaming
001 Structured streaming with Kafka- Theory.mp4
001 Structured streaming with Kafka- Theory_en.srt
002 Demo - Anonymous Wikipedia edits.mp4
002 Demo - Anonymous Wikipedia edits_en.srt
003 Demo - Log analysis using Kafka.mp4
003 Demo - Log analysis using Kafka_en.srt
004 Demo - Twitter analysis using Kafka.mp4
004 Demo - Twitter analysis using Kafka_en.srt
005 Spark structured streaming using Azure EventHub - TBA.html
38035838-Structured-streaming-using-kafka.pptx
38035896-Wiki-anonymous-edit-using-Kafka.dbc
38035918-Log-analysis-using-kafka.dbc
38035956-ISOCountryLookup.csv
38035966-Spark-structured-streaming-with-Kafka-Tweet-analysis.dbc
08 - MLOPS using MLFlow in DataBricks
001 Introduction.mp4
001 Introduction_en.srt
002 MlFlow tracking demo.mp4
002 MlFlow tracking demo_en.srt
003 Model registry.mp4
003 Model registry_en.srt
004 Model registry demo.mp4
004 Model registry demo_en.srt
005 Inference using MLFLOW.mp4
005 Inference using MLFLOW_en.srt
006 Parallelly Training ML Models with pandas UDF.mp4
006 Parallelly Training ML Models with pandas UDF_en.srt
007 How ApplyInPandas() function works.mp4
007 How ApplyInPandas() function works_en.srt
008 Productionizing the ML model parallelly.mp4
008 Productionizing the ML model parallelly_en.srt
38045376-Training-model-with-mlflow.dbc
38045580-Inferencing-model-with-mlflow.dbc
38045750-ML-12-Training-with-Pandas-UDFs.dbc
38045772-applyinpandas.pptx
09 - Anomaly detection on Time Series Data
001 TBA.html
10 - Building CI_CD Pipeline using Azure Devops
001 TBA.html
11 - Building Data Pipeline using Azure Data Factory
001 TBA.html
12 - Productionizing model using Azure Function and Docker
001 TBA.html
Bonus Resources.txt
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