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Udemy - Spark and Python for Big Data with PySpark
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Udemy - Spark and Python for Big Data with PySpark (Size: 1.6 GB)
| 1. AWS EC2 Set-up Guide.mp4 | 5.3 MB | ||
| 1. AWS EC2 Set-up Guide.srt | 4.4 KB | ||
| 1. AWS EMR Setup.mp4 | 45.3 MB | ||
| 1. AWS EMR Setup.srt | 26.4 KB | ||
| 1. Bonus Lecture.html | 512 B | ||
| 1. DataFrame Project Exercise.mp4 | 11.9 MB | ||
| 1. DataFrame Project Exercise.srt | 5.4 KB | ||
| 1. Databricks Setup.mp4 | 27.6 MB | ||
| 1. Databricks Setup.srt | 18.9 KB | ||
| 1. Introduction to Machine Learning and ISLR.mp4 | 18.9 MB | ||
| 1. Introduction to Machine Learning and ISLR.srt | 17.6 KB | ||
| 1. Introduction to Natural Language Processing.mp4 | 14.3 MB | ||
| 1. Introduction to Natural Language Processing.srt | 13.2 KB | ||
| 1. Introduction to Python Crash Course.mp4 | 3.1 MB | ||
| 1. Introduction to Python Crash Course.srt | 2.4 KB | ||
| 1. Introduction to Recommender Systems.mp4 | 12.7 MB | ||
| 1. Introduction to Recommender Systems.srt | 10 KB | ||
| 1. Introduction to Spark DataFrames.mp4 | 4.7 MB | ||
| 1. Introduction to Spark DataFrames.srt | 3.6 KB | ||
| 1. Introduction to Streaming with Spark!.mp4 | 32.6 MB | ||
| 1. Introduction to Streaming with Spark!.srt | 17.5 KB | ||
| 1. Introduction.mp4 | 11.6 MB | ||
| 1. Introduction.srt | 4.5 KB | ||
| 1. K-means Clustering Theory and Reading.mp4 | 12.9 MB | ||
| 1. K-means Clustering Theory and Reading.srt | 10.7 KB | ||
| 1. Linear Regression Theory and Reading.mp4 | 9.9 MB | ||
| 1. Linear Regression Theory and Reading.srt | 8.1 KB | ||
| 1. Local Installation VirtualBox Part 1.mp4 | 37.7 MB | ||
| 1. Local Installation VirtualBox Part 1.srt | 18.2 KB | ||
| 1. Logistic Regression Theory and Reading.mp4 | 20.6 MB | ||
| 1. Logistic Regression Theory and Reading.srt | 17.9 KB | ||
| 1. Set-up Overview.mp4 | 10.8 MB | ||
| 1. Set-up Overview.srt | 10.2 KB | ||
| 1. Tree Methods Theory and Reading.mp4 | 14.7 MB | ||
| 1. Tree Methods Theory and Reading.srt | 11.7 KB | ||
| 1.1 NLP Slides.html | 204 B | ||
| 1.1 Recommender Slides.html | 204 B | ||
| 1.1 Slides for Clustering.html | 204 B | ||
| 1.1 Slides for Installation Options Overview.html | 204 B | ||
| 1.1 Slides for Linear Regression.html | 204 B | ||
| 1.1 Slides for Logistic Regression.html | 204 B | ||
| 1.1 Slides for ML Intro.html | 204 B | ||
| 1.1 Slides for Python Crash Course.html | 204 B | ||
| 1.1 Slides for Spark DataFrame Basics.html | 204 B | ||
| 1.1 Slides for Tree Methods.html | 204 B | ||
| 1.1 Spark Streaming Slides.html | 204 B | ||
| 1.2 Slides for Installation.html | 204 B | ||
| 2. Course Overview.mp4 | 14.4 MB | ||
| 2. Course Overview.srt | 14.7 KB | ||
| 2. Creating the EC2 Instance.mp4 | 63 MB | ||
| 2. Creating the EC2 Instance.srt | 24.4 KB | ||
| 2. DataFrame Project Exercise Solutions.mp4 | 45.1 MB | ||
| 2. DataFrame Project Exercise Solutions.srt | 22.5 KB | ||
| 2. Jupyter Notebook Overview.mp4 | 13.2 MB | ||
| 2. Jupyter Notebook Overview.srt | 11.4 KB | ||
| 2. KMeans Clustering Documentation Example.mp4 | 20.9 MB | ||
| 2. KMeans Clustering Documentation Example.srt | 14.7 KB | ||
| 2. Linear Regression Documentation Example.mp4 | 40.6 MB | ||
| 2. Linear Regression Documentation Example.srt | 21.9 KB | ||
| 2. Local Installation VirtualBox Part 2.mp4 | 46.5 MB | ||
| 2. Local Installation VirtualBox Part 2.srt | 18.9 KB | ||
| 2. Logistic Regression Example Code Along.mp4 | 53.4 MB | ||
| 2. Logistic Regression Example Code Along.srt | 23.5 KB | ||
| 2. Machine Learning with Spark and Python with MLlib.mp4 | 51.3 MB | ||
| 2. Machine Learning with Spark and Python with MLlib.srt | 15.8 KB | ||
| 2. NLP Tools Part One.mp4 | 36.2 MB | ||
| 2. NLP Tools Part One.srt | 22.9 KB | ||
| 2. Note on Installation Sections.html | 307 B | ||
| 2. Recommender System - Code Along Project.mp4 | 24.6 MB | ||
| 2. Recommender System - Code Along Project.srt | 18 KB | ||
| 2. Spark DataFrame Basics.mp4 | 21.1 MB | ||
| 2. Spark DataFrame Basics.srt | 16.4 KB | ||
| 2. Spark Streaming Documentation Example.mp4 | 28.6 MB | ||
| 2. Spark Streaming Documentation Example.srt | 17.4 KB | ||
| 2. Tree Methods Documentation Examples.mp4 | 34.2 MB | ||
| 2. Tree Methods Documentation Examples.srt | 20.7 KB | ||
| 2.1 Course Overview Slides.html | 204 B | ||
| 2.2 Python-and-Spark-for-Big-Data-master.zip.zip | 1.7 MB | ||
| 3. Clustering Example Code Along.mp4 | 27.9 MB | ||
| 3. Clustering Example Code Along.srt | 18.5 KB | ||
| 3. Decision Tress and Random Forest Code Along Examples.mp4 | 49.1 MB | ||
| 3. Decision Tress and Random Forest Code Along Examples.srt | 30.8 KB | ||
| 3. Frequently Asked Questions.html | 409 B | ||
| 3. Logistic Regression Code Along.mp4 | 41.5 MB | ||
| 3. Logistic Regression Code Along.srt | 27.3 KB | ||
| 3. NLP Tools Part Two.mp4 | 18.9 MB | ||
| 3. NLP Tools Part Two.srt | 10.7 KB | ||
| 3. Python Crash Course Part One.mp4 | 29.5 MB | ||
| 3. Python Crash Course Part One.srt | 23.8 KB | ||
| 3. Regression Evaluation.mp4 | 12 MB | ||
| 3. Regression Evaluation.srt | 10.8 KB | ||
| 3. SSH with Mac or Linux.mp4 | 9.3 MB | ||
| 3. SSH with Mac or Linux.srt | 7.5 KB | ||
| 3. Setting up PySpark.mp4 | 15.6 MB | ||
| 3. Setting up PySpark.srt | 8.3 KB | ||
| 3. Spark DataFrame Basics Part Two.mp4 | 19.7 MB | ||
| 3. Spark DataFrame Basics Part Two.srt | 14.4 KB | ||
| 3. Spark Streaming Twitter Project - Part.mp4 | 11.8 MB | ||
| 3. Spark Streaming Twitter Project - Part.srt | 7.3 KB | ||
| 3.1 Explanation of AUC.html | 102 B | ||
| 3.1 Python-and-Spark-for-Big-Data-master.zip.zip | 1.7 MB | ||
| 3.2 Great Example from Databricks.html | 102 B | ||
| 4. Clustering Consulting Project.mp4 | 6.6 MB | ||
| 4. Clustering Consulting Project.srt | 4.7 KB | ||
| 4. Installations on EC2.mp4 | 50.4 MB | ||
| 4. Installations on EC2.srt | 20.2 KB | ||
| 4. Linear Regression Example Code Along.mp4 | 39.2 MB | ||
| 4. Linear Regression Example Code Along.srt | 23.3 KB | ||
| 4. Logistic Regression Consulting Project.mp4 | 6.3 MB | ||
| 4. Logistic Regression Consulting Project.srt | 5.3 KB | ||
| 4. Natural Language Processing Code Along Project.mp4 | 35.2 MB | ||
| 4. Natural Language Processing Code Along Project.srt | 19.6 KB | ||
| 4. Python Crash Course Part Two.mp4 | 22.3 MB | ||
| 4. Python Crash Course Part Two.srt | 17.6 KB | ||
| 4. Random Forest - Classification Consulting Project.mp4 | 5.4 MB | ||
| 4. Random Forest - Classification Consulting Project.srt | 3.8 KB | ||
| 4. Spark DataFrame Basic Operations.mp4 | 27.6 MB | ||
| 4. Spark DataFrame Basic Operations.srt | 16 KB | ||
| 4. Spark Streaming Twitter Project - Part Two.mp4 | 29.3 MB | ||
| 4. Spark Streaming Twitter Project - Part Two.srt | 18.2 KB | ||
| 4. What is Spark Why Python.mp4 | 48.1 MB | ||
| 4. What is Spark Why Python.srt | 30.5 KB | ||
| 4.1 Ecommerce_Customers.csv.csv | 84.8 KB | ||
| 4.1 Spark and Python Slides.html | 204 B | ||
| 5. Clustering Consulting Project Solutions.mp4 | 23 MB | ||
| 5. Clustering Consulting Project Solutions.srt | 11.5 KB | ||
| 5. Groupby and Aggregate Operations.mp4 | 28.8 MB | ||
| 5. Groupby and Aggregate Operations.srt | 19 KB | ||
| 5. Linear Regression Consulting Project.mp4 | 6.8 MB | ||
| 5. Linear Regression Consulting Project.srt | 4.9 KB | ||
| 5. Logistic Regression Consulting Project Solutions.mp4 | 34 MB | ||
| 5. Logistic Regression Consulting Project Solutions.srt | 15.2 KB | ||
| 5. Python Crash Course Part Three.mp4 | 23.2 MB | ||
| 5. Python Crash Course Part Three.srt | 16.1 KB | ||
| 5. Random Forest Classification Consulting Project Solutions.mp4 | 15.9 MB | ||
| 5. Random Forest Classification Consulting Project Solutions.srt | 11.8 KB | ||
| 5. Spark Streaming Twitter Project - Part Three.mp4 | 55 MB | ||
| 5. Spark Streaming Twitter Project - Part Three.srt | 29.3 KB | ||
| 6. Linear Regression Consulting Project Solutions.mp4 | 38.8 MB | ||
| 6. Linear Regression Consulting Project Solutions.srt | 22.7 KB | ||
| 6. Missing Data.mp4 | 17.2 MB | ||
| 6. Missing Data.srt | 13.5 KB | ||
| 6. Python Crash Course Exercises.mp4 | 5 MB | ||
| 6. Python Crash Course Exercises.srt | 2.5 KB | ||
| 7. Dates and Timestamps.mp4 | 24.1 MB | ||
| 7. Dates and Timestamps.srt | 14.6 KB | ||
| 7. Python Crash Course Exercise Solutions.mp4 | 25.1 MB | ||
| 7. Python Crash Course Exercise Solutions.srt | 12.8 KB | ||
| Read Me.txt | 1 KB | ||
| [FreeAllCourse.Com].URL | 204 B | ||
| ▲ 150 total files | |||
Description
Spark and Python for Big Data with PySpark 
Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more!
What you’ll learn?
Use Python and Spark together to analyze Big Data
Learn how to use the new Spark 2.0 DataFrame Syntax
Work on Consulting Projects that mimic real world situations!
Classify Customer Churn with Logisitic Regression
Use Spark with Random Forests for Classification
Learn how to use Spark’s Gradient Boosted Trees
Use Spark’s MLlib to create Powerful Machine Learning Models
Created by Jose Portilla
Last updated 9/2019
English
English [Auto-generated], French [Auto-generated]
For More Updated Udemy Course: FreeAllCourse.Com
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