Dive into the world of big data processing with this comprehensive tutorial series on PySpark and Python. Begin with an introduction to PySpark and its installation, then progress through hands-on lessons on DataFrame operations, including handling missing values and performing filter operations. Explore advanced topics such as GroupBy and aggregate functions, and gain an introduction to PySpark MLlib for machine learning applications. Delve into the mathematical intuition behind linear regression for data science, and learn how to use Databricks for PySpark development. Conclude with a practical implementation of multiple linear regression in Databricks, equipping you with essential skills for large-scale data processing and analysis.
Overview
Syllabus
Tutorial 1-Pyspark With Python-Pyspark Introduction and Installation.
Tutorial 2-Pyspark With Python-Pyspark DataFrames- Part 1.
Tutorial 3- Pyspark With Python-Pyspark DataFrames- Handling Missing Values.
Tutorial 4- Pyspark With Python-Pyspark DataFrames- Filter Operations.
Tutorial 5- Pyspark With Python-GroupBy And Aggregate Functions.
Tutorial 6- Pyspark With Python-Introduction To Pyspark Mlib.
Tutorial 26- Linear Regression Indepth Maths Intuition- Data Science.
Tutorial 7- Pyspark With Python|Introduction To Databricks.
Tutorial 8- Pyspark Multiple Linear Regression Implementation In Databricks.
Taught by
Krish Naik
