| 1. AQE1.mp4 | 32 MB | ||
| 1. AQE1.srt | 8.7 KB | ||
| 1. Introduction to Apache Spark.mp4 | 39 MB | ||
| 1. Introduction to Apache Spark.srt | 10 KB | ||
| 1. Introduction.mp4 | 3.5 MB | ||
| 1. Introduction.srt | 1.5 KB | ||
| 1. Overview.mp4 | 41.7 MB | ||
| 1. Overview.srt | 5.6 KB | ||
| 1. Pandas overview.mp4 | 61.6 MB | ||
| 1. Pandas overview.srt | 8.7 KB | ||
| 1. Skew.mp4 | 51.4 MB | ||
| 1. Skew.srt | 12.1 KB | ||
| 1. Spark Transformations 1 - Hands-on.mp4 | 105.4 MB | ||
| 1. Spark Transformations 1 - Hands-on.srt | 13.5 KB | ||
| 1. Spark actions - Hnads-on.mp4 | 51.8 MB | ||
| 1. Spark actions - Hnads-on.srt | 7.5 KB | ||
| 1. Spark ingestion.mp4 | 49.7 MB | ||
| 1. Spark ingestion.srt | 11 KB | ||
| 1. Streaming concepts - Hands-on.mp4 | 108.2 MB | ||
| 1. Streaming concepts - Hands-on.srt | 15.7 KB | ||
| 1. Structured streaming with Kafka - Concepts.mp4 | 41.3 MB | ||
| 1. Structured streaming with Kafka - Concepts.srt | 9.6 KB | ||
| 1. Time series modelling using Facebook Prophet.mp4 | 51.2 MB | ||
| 1. Time series modelling using Facebook Prophet.srt | 7.6 KB | ||
| 1. What is data lake.mp4 | 18.2 MB | ||
| 1. What is data lake.srt | 3.3 KB | ||
| 1.1 Lakehouse.pptx | 269.5 KB | ||
| 1.1 NLP Course Overview.dbc | 1.1 MB | ||
| 1.1 Pandas overview.dbc | 8.6 KB | ||
| 1.1 Prophet modelling.dbc | 238.8 KB | ||
| 1.1 SKEW.pptx | 3.2 MB | ||
| 1.1 Spark Transformations1.dbc | 8.5 KB | ||
| 1.1 Structured streaming using kafka.pptx | 973 KB | ||
| 1.1 aqe.pptx | 1.2 MB | ||
| 1.1 ingestion-optimization.pptx | 2.1 MB | ||
| 1.1 spark actions.dbc | 7 KB | ||
| 1.1 spark architecure.pptx | 263.3 KB | ||
| 1.2 Streaming Concepts.dbc | 31 KB | ||
| 1.2 review_data.csv | 1.7 MB | ||
| 1.2 train.csv | 16.5 MB | ||
| 1.json | 103.8 KB | ||
| 10.json | 103.9 KB | ||
| 11.json | 103.4 KB | ||
| 12.json | 103.7 KB | ||
| 13.json | 103.7 KB | ||
| 14.json | 103.7 KB | ||
| 15.json | 103.4 KB | ||
| 16.json | 103.7 KB | ||
| 17.json | 103.8 KB | ||
| 18.json | 103.4 KB | ||
| 19.json | 104 KB | ||
| 2. AQE2.mp4 | 31.5 MB | ||
| 2. AQE2.srt | 6.6 KB | ||
| 2. Databricks setup.mp4 | 16.3 MB | ||
| 2. Databricks setup.srt | 2.4 KB | ||
| 2. Demo - Anonymous wikipedia edits.mp4 | 177.1 MB | ||
| 2. Demo - Anonymous wikipedia edits.srt | 20.3 KB | ||
| 2. Disk partitioning.mp4 | 17.1 MB | ||
| 2. Disk partitioning.srt | 4.2 KB | ||
| 2. How Filtering works in Apache spark.mp4 | 25.4 MB | ||
| 2. How Filtering works in Apache spark.srt | 6.9 KB | ||
| 2. Parallelly train the prophet model using spark.mp4 | 39.3 MB | ||
| 2. Parallelly train the prophet model using spark.srt | 5.5 KB | ||
| 2. Pre-processing.mp4 | 98 MB | ||
| 2. Pre-processing.srt | 11.6 KB | ||
| 2. Spark Transformations 2 - Hands-on.mp4 | 49 MB | ||
| 2. Spark Transformations 2 - Hands-on.srt | 6.3 KB | ||
| 2. Spill.mp4 | 28.9 MB | ||
| 2. Spill.srt | 7.5 KB | ||
| 2. What is Delta Lake.mp4 | 10.3 MB | ||
| 2. What is Delta Lake.srt | 2.6 KB | ||
| 2. udfs.mp4 | 141.4 MB | ||
| 2. udfs.srt | 21 KB | ||
| 2.1 Disk partitioning.pptx | 400.6 KB | ||
| 2.1 Preprocessing Text.dbc | 172.4 KB | ||
| 2.1 Spark Transformations2.dbc | 28.3 KB | ||
| 2.1 Spill.pptx | 975.7 KB | ||
| 2.1 Training hundreds of time series forecasting models in parallel with Prophet and Spark.dbc | 24.5 KB | ||
| 2.1 Wiki anonymous edit using Kafka.dbc | 145.9 KB | ||
| 2.1 user defined functions.dbc | 9.5 KB | ||
| 2.json | 103.8 KB | ||
| 20.json | 103.8 KB | ||
| 3. Elements of Delta Lake.mp4 | 22.5 MB | ||
| 3. Elements of Delta Lake.srt | 4.3 KB | ||
| 3. How Counting operation works in Apache spark.mp4 | 7.3 MB | ||
| 3. How Counting operation works in Apache spark.srt | 2.6 KB | ||
| 3. Shuffle.mp4 | 45.2 MB | ||
| 3. Shuffle.srt | 11.2 KB | ||
| 3. Spark Transformations 3- Hands-on.mp4 | 76.8 MB | ||
| 3. Spark Transformations 3- Hands-on.srt | 10 KB | ||
| 3. Storage.mp4 | 43.8 MB | ||
| 3. Storage.srt | 10.8 KB | ||
| 3. Upload files to DBFS.mp4 | 6.5 MB | ||
| 3. Upload files to DBFS.srt | 614.4 B | ||
| 3. User Defined functions.mp4 | 54.9 MB | ||
| 3. User Defined functions.srt | 8 KB | ||
| 3.1 Shuffle.pptx | 1.9 MB | ||
| 3.1 Spark Transformations3.dbc | 5.7 KB | ||
| 3.1 UDFs with External Libraries.dbc | 914.9 KB | ||
| 3.1 storage.pptx | 2.7 MB | ||
| 3.json | 103.5 KB | ||
| 4. Aggregations.mp4 | 34.4 MB | ||
| 4. Aggregations.srt | 5.1 KB | ||
| 4. Delta Lake Demo.mp4 | 116.3 MB | ||
| 4. Delta Lake Demo.srt | 16.3 KB | ||
| 4. How shuffle works in Apache spark.mp4 | 8.8 MB | ||
| 4. How shuffle works in Apache spark.srt | 2.5 KB | ||
| 4. Importing Notebooks into Databricks workspace.mp4 | 5.2 MB | ||
| 4. Importing Notebooks into Databricks workspace.srt | 716.8 B | ||
| 4. Predicate Pushdown.mp4 | 29.9 MB | ||
| 4. Predicate Pushdown.srt | 7 KB | ||
| 4. Rule Based Sentiment Analysis.mp4 | 51.8 MB | ||
| 4. Rule Based Sentiment Analysis.srt | 7.1 KB | ||
| 4.1 Delta lake ingest LAB.dbc | 55.1 KB | ||
| 4.1 Groupby.dbc | 3.1 KB | ||
| 4.1 Predicate pushdown.pptx | 904.8 KB | ||
| 4.1 Sentiment analysis using rule based approach.dbc | 299.9 KB | ||
| 4.2 Iot_sensor_data.csv | 22.6 MB | ||
| 4.2 Join.dbc | 2.7 KB | ||
| 4.json | 103.5 KB | ||
| 5. Information Retravel system using WORD2VEC.mp4 | 102 MB | ||
| 5. Information Retravel system using WORD2VEC.srt | 13.9 KB | ||
| 5. Regular expressions.mp4 | 35.9 MB | ||
| 5. Regular expressions.srt | 4.5 KB | ||
| 5. Serialization.mp4 | 14.5 MB | ||
| 5. Serialization.srt | 3.3 KB | ||
| 5.1 Embeddings.dbc | 738.5 KB | ||
| 5.1 Serialization.pptx | 467.4 KB | ||
| 5.1 pyspark_reg expressions.dbc | 4.1 KB | ||
| 5.json | 103.7 KB | ||
| 6. Bucketing.mp4 | 41.9 MB | ||
| 6. Bucketing.srt | 9.4 KB | ||
| 6. Sentiment Analysis on IMDB dataet.mp4 | 65.3 MB | ||
| 6. Sentiment Analysis on IMDB dataet.srt | 8.5 KB | ||
| 6. Window transformations.mp4 | 30.4 MB | ||
| 6. Window transformations.srt | 5 KB | ||
| 6.1 Bucketing.pptx | 1.6 MB | ||
| 6.1 imdb.csv | 912.7 KB | ||
| 6.1 window_ops.pptx | 56.7 KB | ||
| 6.2 Sentiment classification using IMBD Dataset.dbc | 818.2 KB | ||
| 6.2 window.dbc | 3.4 KB | ||
| 6.json | 104.1 KB | ||
| 7. Zordering.mp4 | 22 MB | ||
| 7. Zordering.srt | 5.5 KB | ||
| 7.1 Z Ordering.pptx | 734.4 KB | ||
| 7.json | 103.8 KB | ||
| 8.json | 103.7 KB | ||
| 9.json | 103.9 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 150 total files | |||
Apache Spark : Master Big Data with PySpark and DataBricks
https://DevCourseWeb.com
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 2.11 GB | Duration: 4h 56m
Learn Pyspark, streaming using Kafka, Delta lake, crazy optimization techniques, NLP, time series, distributed computing
What you'll learn
Learn the Spark Architecture
What is distributed computing
Learn Spark Transformations and Actions using the Structured API
Learn Spark on Databricks
Spark optimization techniques
Data Lake House architecture
Spark structured streaming using Kafka
Information retriever system using word2vec
Sentiment analysis using pyspark
Training hundreds of time series forecasting models in parallel with Prophet and Spark
Description
This course is designed to help you develop the skill necessary to perform ETL operations in Databricks using pyspark, build production ready ML models, learn spark optimization techniques and master distributed computing.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.1 GB | freecoursewb | 3 months | 0 | 0 | |
| 328.1 MB | freecoursewb | 4 months | 4 | 0 | |
| 1.6 GB | freecoursewb | 4 months | 11 | 2 | |
|
Udemy - Apache Kafka Series - Confluent Schema Registry and REST Proxy Posted by
freecoursewb in Other
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1.8 GB | freecoursewb | 4 months | 0 | 0 |
| 1.3 GB | freecoursewb | 6 months | 3 | 0 |
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