Spark and Python for Big Data with PySpark

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size1.6 GB
  • Uploaded ByCourseRecap
  • Downloads137
  • Last checkedJun. 19th '21
  • Date uploadedJun. 15th '21
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Spark and Python for Big Data with PySpark



Description

Learn the latest Big Data Technology - Spark! And learn to use it with one of the most popular programming languages, Python!

One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!

Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!

This course will teach the basics with a crash course in Python, continuing on to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! Once we've done that we'll go through how to use the MLlib Machine Library with the DataFrame syntax and Spark. All along the way you'll have exercises and Mock Consulting Projects that put you right into a real world situation where you need to use your new skills to solve a real problem!

We also cover the latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees! After you complete this course you will feel comfortable putting Spark and PySpark on your resume! This course also has a full 30 day money back guarantee and comes with a LinkedIn Certificate of Completion!

If you're ready to jump into the world of Python, Spark, and Big Data, this is the course for you!

Who this course is for:

Someone who knows Python and would like to learn how to use it for Big Data
Someone who is very familiar with another programming language and needs to learn Spark

Files:

Spark and Python for Big Data with PySpark Spark and Python for Big Data with PySpark 4. AWS EC2 PySpark Set-up
  • 2. Creating the EC2 Instance.mp4 (63.0 MB)
  • 1. AWS EC2 Set-up Guide.mp4 (5.3 MB)
  • 1. AWS EC2 Set-up Guide.vtt (3.9 KB)
  • 2. Creating the EC2 Instance.vtt (21.2 KB)
  • 3. SSH with Mac or Linux.mp4 (9.3 MB)
  • 3. SSH with Mac or Linux.vtt (6.5 KB)
  • 4. Installations on EC2.mp4 (50.4 MB)
  • 4. Installations on EC2.vtt (17.7 KB)
  • READ_ME.txt (0.4 KB)
    • 1. Introduction to Course
    • 1. Introduction.mp4 (11.6 MB)
    • 1. Introduction.vtt (4.0 KB)
    • 2. Course Overview.mp4 (14.4 MB)
    • 2. Course Overview.vtt (12.9 KB)
    • 2.1 Python-and-Spark-for-Big-Data-master.zip.zip (1.7 MB)
    • 2.2 Course Overview Slides.html (0.2 KB)
    • 3. Frequently Asked Questions.html (0.4 KB)
    • 3.1 Python-and-Spark-for-Big-Data-master.zip.zip (1.7 MB)
    • 4. What is Spark Why Python.mp4 (48.1 MB)
    • 4. What is Spark Why Python.vtt (26.9 KB)
    • 4.1 Spark and Python Slides.html (0.2 KB)
    • READ_ME.txt (0.4 KB)
    2. Setting up Python with Spark
    • 1. Set-up Overview.mp4 (10.8 MB)
    • 1. Set-up Overview.vtt (9.0 KB)
    • 1.1 Slides for Installation Options Overview.html (0.2 KB)
    • 1.2 Slides for Installation.html (0.2 KB)
    • 2. Note on Installation Sections.html (0.3 KB)
    3. Local VirtualBox Set-up
    • 1. Local Installation VirtualBox Part 1.mp4 (37.7 MB)
    • 1. Local Installation VirtualBox Part 1.vtt (15.9 KB)
    • 2. Local Installation VirtualBox Part 2.mp4 (46.5 MB)
    • 2. Local Installation VirtualBox Part 2.vtt (16.4 KB)
    • 3. Setting up PySpark.mp4 (15.6 MB)
    • 3. Setting up PySpark.vtt (7.3 KB)
    5. Databricks Setup
    • 1. Databricks Setup.mp4 (27.6 MB)
    • 1. Databricks Setup.vtt (16.5 KB)
    6. AWS EMR Cluster Setup
    • 1. AWS EMR Setup.mp4 (45.3 MB)
    • 1. AWS EMR Setup.vtt (23.1 KB)
    7. Python Crash Course
    • 1. Introduction to Python Crash Course.mp4 (3.1 MB)
    • 1. Introduction to Python Crash Course.vtt (2.1 KB)
    • 1.1 Slides for Python Crash Course.html (0.2 KB)
    • 2. Jupyter Notebook Overview.mp4 (13.2 MB)
    • 2. Jupyter Notebook Overview.vtt (9.9 KB)
    • 3. Python Crash Course Part One.mp4 (29.5 MB)
    • 3. Python Crash Course Part One.vtt (20.7 KB)
    • 4. Python Crash Course Part Two.mp4 (22.3 MB)
    • 4. Python Crash Course Part Two.vtt (15.1 KB)
    • 5. Python Crash Course Part Three.mp4 (23.2 MB)
    • 5. Python Crash Course Part Three.vtt (14.0 KB)
    • 6. Python Crash Course Exercises.mp4 (5.0 MB)
    • 6. Python Crash Course Exercises.vtt (2.2 KB)
    • 7. Python Crash Course Exercise Solutions.mp4 (25.1 MB)
    • 7. Python Crash Course Exercise Solutions.vtt (11.2 KB)
    8. Spark DataFrame Basics
    • 1. Introduction to Spark DataFrames.mp4 (4.7 MB)
    • 1. Introduction to Spark DataFrames.vtt (3.2 KB)
    • 1.1 Slides for Spark DataFrame Basics.html (0.2 KB)
    • 2. Spark DataFrame Basics.mp4 (21.1 MB)
    • 2. Spark DataFrame Basics.vtt (14.3 KB)
    • 3. Spark DataFrame Basics Part Two.mp4 (19.7 MB)
    • 3. Spark DataFrame Basics Part Two.vtt (12.6 KB)
    • 4. Spark DataFrame Basic Operations.mp4 (27.6 MB)
    • 4. Spark DataFrame Basic Operations.vtt (14.0 KB)
    • 5. Groupby and Aggregate Operations.mp4 (28.8 MB)
    • 5. Groupby and Aggregate Operations.vtt (16.5 KB)
    • 6. Missing Data.mp4 (17.2 MB)
    • 6. Missing Data.vtt (11.7 KB)
    • 7. Dates and Timestamps.mp4 (24.1 MB)
    • 7. Dates and Timestamps.vtt (12.7 KB)
    9. Spark DataFrame Project Exercise
    • 1. DataFrame Project Exercise.mp4 (11.9 MB)
    • 1. DataFrame Project Exercise.vtt (4.8 KB)
    • 2. DataFrame Project Exercise Solutions.mp4 (45.1 MB)
    • 2. DataFrame Project Exercise Solutions.vtt (19.6 KB)
    10. Introduction to Machine Learning with MLlib
    • 1. Introduction to Machine Learning and ISLR.mp4 (18.9 MB)
    • 1. Introduction to Machine Learning and ISLR.vtt (15.4 KB)
    • 1.1 Slides for ML Intro.html (0.2 KB)
    • 2. Machine Learning with Spark and Python with MLlib.mp4 (51.3 MB)
    • 2. Machine Learning with Spark and Python with MLlib.vtt (13.9 KB)
    11. Linear Regression
    • 1. Linear Regression Theory and Reading.mp4 (9.9 MB)
    • 1. Linear Regression Theory and Reading.vtt (7.2 KB)
    • 1.1 Slides for Linear Regression.html (0.2 KB)
    • 2. Linear Regression Documentation Example.mp4 (40.6 MB)
    • 2. Linear Regression Documentation Example.vtt (19.1 KB)
    • 3. Regression Evaluation.mp4 (12.0 MB)
    • 3. Regression Evaluation.vtt (9.5 KB)
    • 4. Linear Regression Example Code Along.mp4 (39.2 MB)
    • 4. Linear Regression Example Code Along.vtt (20.3 KB)
    • 4.1 Ecommerce_Customers.csv.csv (84.8 KB)
    • 5. Linear Regression Consulting Project.mp4 (6.8 MB)
    • 5. Linear Regression Consulting Project.vtt (4.3 KB)
    • 6. Linear Regression Consulting Project Solutions.mp4 (38.8 MB)
    • 6. Linear Regression Consulting Project Solutions.vtt (19.9 KB)
    12. Logistic Regression
    • 1. Logistic Regression Theory and Reading.mp4 (20.6 MB)
    • 1. Logistic Regression Theory and Reading.vtt (15.6 KB)
    • 1.1 Slides for Logistic Regression.html (0.2 KB)
    • 2. Logistic Regression Example Code Along.mp4 (53.4 MB)
    • 2. Logistic Regression Example Code Along.vtt (20.6 KB)
    • 3. Logistic Regression Code Along.mp4 (41.5 MB)
    • 3. Logistic Regression Code Along.vtt (24.0 KB)
    • 3.1 Great Example from Databricks.html (0.1 KB)
    • 3.2 Explanation of AUC.html

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