Skip to content
/ Applied-data-science-using-pyspark-code-files Public

"Applied data science using PySpark" code files are programs that use PySpark to analyze, manipulate, and process large datasets. They leverage the distributed computing power of Apache Spark for efficiency, and often use built-in functions and libraries for data analysis.

0 stars 0 forks Branches Tags Activity
Star
Notifications You must be signed in to change notification settings

malikbaqi12/Applied-data-science-using-pyspark-code-files

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

22 Commits
3_supply_chain_data_analysis_99_accuracy.ipynb
3_supply_chain_data_analysis_99_accuracy.ipynb
 
 
BIG_DATA_Project_RFM.ipynb
BIG_DATA_Project_RFM.ipynb
 
 
Ch_2_Spark_Demonstration.ipynb
Ch_2_Spark_Demonstration.ipynb
 
 
Copy_of_Spark_Demonstration.ipynb
Copy_of_Spark_Demonstration.ipynb
 
 
Exercise_3_1_Missing_values_and_cardinality.ipynb
Exercise_3_1_Missing_values_and_cardinality.ipynb
 
 
Exercise_3_2_Model_based_Selection.ipynb
Exercise_3_2_Model_based_Selection.ipynb
 
 
KDD Process (titanic dataset) using pyspark.ipynb
KDD Process (titanic dataset) using pyspark.ipynb
 
 
KDD_Steps_Vincent_Wen_(my_assignment).ipynb
KDD_Steps_Vincent_Wen_(my_assignment).ipynb
 
 
Model_Validation.ipynb
Model_Validation.ipynb
 
 
README.md
README.md
 
 
Spark_Demonstration_chapter_3.ipynb
Spark_Demonstration_chapter_3.ipynb
 
 
Supervised_learning.ipynb
Supervised_learning.ipynb
 
 
Variable_Selection.ipynb
Variable_Selection.ipynb
 
 
data_cleaning_aggregation_and_bipartite_graph.ipynb
data_cleaning_aggregation_and_bipartite_graph.ipynb
 
 
dataco_supply_chain_analysis.ipynb
dataco_supply_chain_analysis.ipynb
 
 
demand_forecasting_in_supply_chain_analytics.ipynb
demand_forecasting_in_supply_chain_analytics.ipynb
 
 
zameen_com_dataset_analysis_11.ipynb
zameen_com_dataset_analysis_11.ipynb
 
 
zameen_dataset (FM, AB).ipynb
zameen_dataset (FM, AB).ipynb
 
 

Repository files navigation

Applied-data-science-using-pyspark-code-files

"Applied data science using PySpark" code files are programs that use PySpark to analyze, manipulate, and process large datasets. They leverage the distributed computing power of Apache Spark for efficiency, and often use built-in functions and libraries for data analysis.

About

"Applied data science using PySpark" code files are programs that use PySpark to analyze, manipulate, and process large datasets. They leverage the distributed computing power of Apache Spark for efficiency, and often use built-in functions and libraries for data analysis.

Resources

Readme
Activity

Stars

0 stars

Watchers

1 watching

Forks

0 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages