[FreeCourseLab.com] Udemy - Spark and Python for Big Data with PySpark

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[FreeCourseLab.com] Udemy - Spark and Python for Big Data with PySpark

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种子哈希：3c09c47130a3efe607ca331c6f13ccc1a63cb5c8
文件大小： 1.56G
已经下载：2147次
下载速度：极快
收录时间：2021-04-10
最近下载：2025-07-29

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文件列表

  • 4. AWS EC2 PySpark Set-up/2. Creating the EC2 Instance.mp4 66.0 MB
  • 17. Spark Streaming with Python/5. Spark Streaming Twitter Project - Part Three.mp4 57.7 MB
  • 12. Logistic Regression/2. Logistic Regression Example Code Along.mp4 56.0 MB
  • 10. Introduction to Machine Learning with MLlib/2. Machine Learning with Spark and Python with MLlib.mp4 53.8 MB
  • 4. AWS EC2 PySpark Set-up/4. Installations on EC2.mp4 52.9 MB
  • 13. Decision Trees and Random Forests/3. Decision Tress and Random Forest Code Along Examples.mp4 51.5 MB
  • 1. Introduction to Course/4. What is Spark Why Python.mp4 50.5 MB
  • 3. Local VirtualBox Set-up/2. Local Installation VirtualBox Part 2.mp4 48.8 MB
  • 6. AWS EMR Cluster Setup/1. AWS EMR Setup.mp4 47.5 MB
  • 9. Spark DataFrame Project Exercise/2. DataFrame Project Exercise Solutions.mp4 47.3 MB
  • 12. Logistic Regression/3. Logistic Regression Code Along.mp4 43.5 MB
  • 11. Linear Regression/2. Linear Regression Documentation Example.mp4 42.6 MB
  • 11. Linear Regression/4. Linear Regression Example Code Along.mp4 41.1 MB
  • 11. Linear Regression/6. Linear Regression Consulting Project Solutions.mp4 40.6 MB
  • 3. Local VirtualBox Set-up/1. Local Installation VirtualBox Part 1.mp4 39.5 MB
  • 16. Natural Language Processing/2. NLP Tools Part One.mp4 37.9 MB
  • 16. Natural Language Processing/4. Natural Language Processing Code Along Project.mp4 36.9 MB
  • 13. Decision Trees and Random Forests/2. Tree Methods Documentation Examples.mp4 35.8 MB
  • 12. Logistic Regression/5. Logistic Regression Consulting Project Solutions.mp4 35.6 MB
  • 17. Spark Streaming with Python/1. Introduction to Streaming with Spark!.mp4 34.2 MB
  • 7. Python Crash Course/3. Python Crash Course Part One.mp4 31.0 MB
  • 17. Spark Streaming with Python/4. Spark Streaming Twitter Project - Part Two.mp4 30.7 MB
  • 8. Spark DataFrame Basics/5. Groupby and Aggregate Operations.mp4 30.2 MB
  • 17. Spark Streaming with Python/2. Spark Streaming Documentation Example.mp4 30.0 MB
  • 14. K-means Clustering/3. Clustering Example Code Along.mp4 29.2 MB
  • 5. Databricks Setup/1. Databricks Setup.mp4 29.0 MB
  • 8. Spark DataFrame Basics/4. Spark DataFrame Basic Operations.mp4 28.9 MB
  • 7. Python Crash Course/7. Python Crash Course Exercise Solutions.mp4 26.3 MB
  • 15. Collaborative Filtering for Recommender Systems/2. Recommender System - Code Along Project.mp4 25.8 MB
  • 8. Spark DataFrame Basics/7. Dates and Timestamps.mp4 25.3 MB
  • 7. Python Crash Course/5. Python Crash Course Part Three.mp4 24.3 MB
  • 14. K-means Clustering/5. Clustering Consulting Project Solutions.mp4 24.2 MB
  • 7. Python Crash Course/4. Python Crash Course Part Two.mp4 23.3 MB
  • 8. Spark DataFrame Basics/2. Spark DataFrame Basics.mp4 22.1 MB
  • 14. K-means Clustering/2. KMeans Clustering Documentation Example.mp4 21.9 MB
  • 12. Logistic Regression/1. Logistic Regression Theory and Reading.mp4 21.7 MB
  • 8. Spark DataFrame Basics/3. Spark DataFrame Basics Part Two.mp4 20.7 MB
  • 10. Introduction to Machine Learning with MLlib/1. Introduction to Machine Learning and ISLR.mp4 19.8 MB
  • 16. Natural Language Processing/3. NLP Tools Part Two.mp4 19.8 MB
  • 8. Spark DataFrame Basics/6. Missing Data.mp4 18.1 MB
  • 13. Decision Trees and Random Forests/5. Random Forest Classification Consulting Project Solutions.mp4 16.7 MB
  • 3. Local VirtualBox Set-up/3. Setting up PySpark.mp4 16.3 MB
  • 13. Decision Trees and Random Forests/1. Tree Methods Theory and Reading.mp4 15.4 MB
  • 1. Introduction to Course/2. Course Overview.mp4 15.1 MB
  • 16. Natural Language Processing/1. Introduction to Natural Language Processing.mp4 15.0 MB
  • 7. Python Crash Course/2. Jupyter Notebook Overview.mp4 13.9 MB
  • 14. K-means Clustering/1. K-means Clustering Theory and Reading.mp4 13.5 MB
  • 15. Collaborative Filtering for Recommender Systems/1. Introduction to Recommender Systems.mp4 13.3 MB
  • 11. Linear Regression/3. Regression Evaluation.mp4 12.6 MB
  • 9. Spark DataFrame Project Exercise/1. DataFrame Project Exercise.mp4 12.5 MB
  • 17. Spark Streaming with Python/3. Spark Streaming Twitter Project - Part.mp4 12.4 MB
  • 1. Introduction to Course/1. Introduction.mp4 12.2 MB
  • 2. Setting up Python with Spark/1. Set-up Overview.mp4 11.4 MB
  • 11. Linear Regression/1. Linear Regression Theory and Reading.mp4 10.4 MB
  • 4. AWS EC2 PySpark Set-up/3. SSH with Mac or Linux.mp4 9.7 MB
  • 11. Linear Regression/5. Linear Regression Consulting Project.mp4 7.1 MB
  • 14. K-means Clustering/4. Clustering Consulting Project.mp4 6.9 MB
  • 12. Logistic Regression/4. Logistic Regression Consulting Project.mp4 6.7 MB
  • 13. Decision Trees and Random Forests/4. Random Forest - Classification Consulting Project.mp4 5.7 MB
  • 4. AWS EC2 PySpark Set-up/1. AWS EC2 Set-up Guide.mp4 5.6 MB
  • 7. Python Crash Course/6. Python Crash Course Exercises.mp4 5.3 MB
  • 8. Spark DataFrame Basics/1. Introduction to Spark DataFrames.mp4 4.9 MB
  • 7. Python Crash Course/1. Introduction to Python Crash Course.mp4 3.2 MB
  • 1. Introduction to Course/2.1 Python-and-Spark-for-Big-Data-master.zip.zip 1.7 MB
  • 1. Introduction to Course/3.1 Python-and-Spark-for-Big-Data-master.zip.zip 1.7 MB
  • 11. Linear Regression/4.1 Ecommerce_Customers.csv.csv 86.9 kB
  • 1. Introduction to Course/4. What is Spark Why Python.vtt 27.6 kB
  • 13. Decision Trees and Random Forests/3. Decision Tress and Random Forest Code Along Examples.vtt 27.4 kB
  • 17. Spark Streaming with Python/5. Spark Streaming Twitter Project - Part Three.vtt 26.1 kB
  • 12. Logistic Regression/3. Logistic Regression Code Along.vtt 24.5 kB
  • 6. AWS EMR Cluster Setup/1. AWS EMR Setup.vtt 23.7 kB
  • 4. AWS EC2 PySpark Set-up/2. Creating the EC2 Instance.vtt 21.7 kB
  • 7. Python Crash Course/3. Python Crash Course Part One.vtt 21.2 kB
  • 12. Logistic Regression/2. Logistic Regression Example Code Along.vtt 21.1 kB
  • 11. Linear Regression/4. Linear Regression Example Code Along.vtt 20.8 kB
  • 16. Natural Language Processing/2. NLP Tools Part One.vtt 20.5 kB
  • 11. Linear Regression/6. Linear Regression Consulting Project Solutions.vtt 20.3 kB
  • 9. Spark DataFrame Project Exercise/2. DataFrame Project Exercise Solutions.vtt 20.1 kB
  • 11. Linear Regression/2. Linear Regression Documentation Example.vtt 19.6 kB
  • 13. Decision Trees and Random Forests/2. Tree Methods Documentation Examples.vtt 18.5 kB
  • 4. AWS EC2 PySpark Set-up/4. Installations on EC2.vtt 18.1 kB
  • 16. Natural Language Processing/4. Natural Language Processing Code Along Project.vtt 17.6 kB
  • 5. Databricks Setup/1. Databricks Setup.vtt 16.9 kB
  • 8. Spark DataFrame Basics/5. Groupby and Aggregate Operations.vtt 16.9 kB
  • 3. Local VirtualBox Set-up/2. Local Installation VirtualBox Part 2.vtt 16.8 kB
  • 14. K-means Clustering/3. Clustering Example Code Along.vtt 16.7 kB
  • 3. Local VirtualBox Set-up/1. Local Installation VirtualBox Part 1.vtt 16.3 kB
  • 17. Spark Streaming with Python/4. Spark Streaming Twitter Project - Part Two.vtt 16.2 kB
  • 15. Collaborative Filtering for Recommender Systems/2. Recommender System - Code Along Project.vtt 16.1 kB
  • 12. Logistic Regression/1. Logistic Regression Theory and Reading.vtt 16.0 kB
  • 10. Introduction to Machine Learning with MLlib/1. Introduction to Machine Learning and ISLR.vtt 15.8 kB
  • 17. Spark Streaming with Python/1. Introduction to Streaming with Spark!.vtt 15.8 kB
  • 17. Spark Streaming with Python/2. Spark Streaming Documentation Example.vtt 15.6 kB
  • 7. Python Crash Course/4. Python Crash Course Part Two.vtt 15.4 kB
  • 8. Spark DataFrame Basics/2. Spark DataFrame Basics.vtt 14.7 kB
  • 7. Python Crash Course/5. Python Crash Course Part Three.vtt 14.3 kB
  • 8. Spark DataFrame Basics/4. Spark DataFrame Basic Operations.vtt 14.3 kB
  • 10. Introduction to Machine Learning with MLlib/2. Machine Learning with Spark and Python with MLlib.vtt 14.2 kB
  • 12. Logistic Regression/5. Logistic Regression Consulting Project Solutions.vtt 13.7 kB
  • 14. K-means Clustering/2. KMeans Clustering Documentation Example.vtt 13.2 kB
  • 1. Introduction to Course/2. Course Overview.vtt 13.2 kB
  • 8. Spark DataFrame Basics/7. Dates and Timestamps.vtt 13.0 kB
  • 8. Spark DataFrame Basics/3. Spark DataFrame Basics Part Two.vtt 12.9 kB
  • 8. Spark DataFrame Basics/6. Missing Data.vtt 12.0 kB
  • 16. Natural Language Processing/1. Introduction to Natural Language Processing.vtt 11.9 kB
  • 7. Python Crash Course/7. Python Crash Course Exercise Solutions.vtt 11.5 kB
  • 13. Decision Trees and Random Forests/1. Tree Methods Theory and Reading.vtt 10.6 kB
  • 13. Decision Trees and Random Forests/5. Random Forest Classification Consulting Project Solutions.vtt 10.6 kB
  • 14. K-means Clustering/5. Clustering Consulting Project Solutions.vtt 10.3 kB
  • 7. Python Crash Course/2. Jupyter Notebook Overview.vtt 10.2 kB
  • 11. Linear Regression/3. Regression Evaluation.vtt 9.8 kB
  • 16. Natural Language Processing/3. NLP Tools Part Two.vtt 9.7 kB
  • 14. K-means Clustering/1. K-means Clustering Theory and Reading.vtt 9.6 kB
  • 2. Setting up Python with Spark/1. Set-up Overview.vtt 9.2 kB
  • 15. Collaborative Filtering for Recommender Systems/1. Introduction to Recommender Systems.vtt 9.1 kB
  • 3. Local VirtualBox Set-up/3. Setting up PySpark.vtt 7.4 kB
  • 11. Linear Regression/1. Linear Regression Theory and Reading.vtt 7.3 kB
  • 4. AWS EC2 PySpark Set-up/3. SSH with Mac or Linux.vtt 6.7 kB
  • 17. Spark Streaming with Python/3. Spark Streaming Twitter Project - Part.vtt 6.5 kB
  • 18. Bonus/1. Bonus Lecture Coupons.html 5.9 kB
  • 9. Spark DataFrame Project Exercise/1. DataFrame Project Exercise.vtt 4.9 kB
  • 12. Logistic Regression/4. Logistic Regression Consulting Project.vtt 4.8 kB
  • 11. Linear Regression/5. Linear Regression Consulting Project.vtt 4.4 kB
  • 14. K-means Clustering/4. Clustering Consulting Project.vtt 4.3 kB
  • 1. Introduction to Course/1. Introduction.vtt 4.1 kB
  • 4. AWS EC2 PySpark Set-up/1. AWS EC2 Set-up Guide.vtt 4.0 kB
  • 13. Decision Trees and Random Forests/4. Random Forest - Classification Consulting Project.vtt 3.5 kB
  • 8. Spark DataFrame Basics/1. Introduction to Spark DataFrames.vtt 3.3 kB
  • 7. Python Crash Course/6. Python Crash Course Exercises.vtt 2.2 kB
  • 7. Python Crash Course/1. Introduction to Python Crash Course.vtt 2.2 kB
  • 1. Introduction to Course/3. Frequently Asked Questions.html 447 Bytes
  • 2. Setting up Python with Spark/2. Note on Installation Sections.html 347 Bytes
  • 1. Introduction to Course/2.2 Course Overview Slides.html 161 Bytes
  • 1. Introduction to Course/4.1 Spark and Python Slides.html 161 Bytes
  • 10. Introduction to Machine Learning with MLlib/1.1 Slides for ML Intro.html 161 Bytes
  • 11. Linear Regression/1.1 Slides for Linear Regression.html 161 Bytes
  • 12. Logistic Regression/1.1 Slides for Logistic Regression.html 161 Bytes
  • 13. Decision Trees and Random Forests/1.1 Slides for Tree Methods.html 161 Bytes
  • 14. K-means Clustering/1.1 Slides for Clustering.html 161 Bytes
  • 15. Collaborative Filtering for Recommender Systems/1.1 Recommender Slides.html 161 Bytes
  • 16. Natural Language Processing/1.1 NLP Slides.html 161 Bytes
  • 17. Spark Streaming with Python/1.1 Spark Streaming Slides.html 161 Bytes
  • 2. Setting up Python with Spark/1.1 Slides for Installation Options Overview.html 161 Bytes
  • 2. Setting up Python with Spark/1.2 Slides for Installation.html 161 Bytes
  • 7. Python Crash Course/1.1 Slides for Python Crash Course.html 161 Bytes
  • 8. Spark DataFrame Basics/1.1 Slides for Spark DataFrame Basics.html 161 Bytes
  • 12. Logistic Regression/3.1 Great Example from Databricks.html 150 Bytes
  • 12. Logistic Regression/3.2 Explanation of AUC.html 148 Bytes
  • [FreeCourseLab.com].url 126 Bytes

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