[DesireCourse.Net] Udemy - Spark and Python for Big Data with PySpark

Creation Time	March 13, 2024, 3:12 p.m.
Last Access Time	Dec. 15, 2024, 10:42 a.m.
File Size	1.6 GB
Keywords	and for PySpark Python DesireCourse - Udemy with Big Net Data Spark
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4. AWS EC2 PySpark Set-up/2. Creating the EC2 Instance.mp4 63.0 MB
17. Spark Streaming with Python/5. Spark Streaming Twitter Project - Part Three.mp4 55.0 MB
12. Logistic Regression/2. Logistic Regression Example Code Along.mp4 53.4 MB
10. Introduction to Machine Learning with MLlib/2. Machine Learning with Spark and Python with MLlib.mp4 51.3 MB
4. AWS EC2 PySpark Set-up/4. Installations on EC2.mp4 50.4 MB
13. Decision Trees and Random Forests/3. Decision Tress and Random Forest Code Along Examples.mp4 49.1 MB
1. Introduction to Course/4. What is Spark Why Python.mp4 48.1 MB
3. Local VirtualBox Set-up/2. Local Installation VirtualBox Part 2.mp4 46.5 MB
6. AWS EMR Cluster Setup/1. AWS EMR Setup.mp4 45.3 MB
9. Spark DataFrame Project Exercise/2. DataFrame Project Exercise Solutions.mp4 45.1 MB
12. Logistic Regression/3. Logistic Regression Code Along.mp4 41.5 MB
11. Linear Regression/2. Linear Regression Documentation Example.mp4 40.6 MB
11. Linear Regression/4. Linear Regression Example Code Along.mp4 39.2 MB
11. Linear Regression/6. Linear Regression Consulting Project Solutions.mp4 38.8 MB
3. Local VirtualBox Set-up/1. Local Installation VirtualBox Part 1.mp4 37.7 MB
16. Natural Language Processing/2. NLP Tools Part One.mp4 36.2 MB
16. Natural Language Processing/4. Natural Language Processing Code Along Project.mp4 35.2 MB
13. Decision Trees and Random Forests/2. Tree Methods Documentation Examples.mp4 34.2 MB
12. Logistic Regression/5. Logistic Regression Consulting Project Solutions.mp4 34.0 MB
17. Spark Streaming with Python/1. Introduction to Streaming with Spark!.mp4 32.6 MB
7. Python Crash Course/3. Python Crash Course Part One.mp4 29.5 MB
17. Spark Streaming with Python/4. Spark Streaming Twitter Project - Part Two.mp4 29.3 MB
8. Spark DataFrame Basics/5. Groupby and Aggregate Operations.mp4 28.8 MB
17. Spark Streaming with Python/2. Spark Streaming Documentation Example.mp4 28.6 MB
14. K-means Clustering/3. Clustering Example Code Along.mp4 27.9 MB
5. Databricks Setup/1. Databricks Setup.mp4 27.6 MB
8. Spark DataFrame Basics/4. Spark DataFrame Basic Operations.mp4 27.6 MB
7. Python Crash Course/7. Python Crash Course Exercise Solutions.mp4 25.1 MB
15. Collaborative Filtering for Recommender Systems/2. Recommender System - Code Along Project.mp4 24.6 MB
8. Spark DataFrame Basics/7. Dates and Timestamps.mp4 24.1 MB
7. Python Crash Course/5. Python Crash Course Part Three.mp4 23.2 MB
14. K-means Clustering/5. Clustering Consulting Project Solutions.mp4 23.0 MB
7. Python Crash Course/4. Python Crash Course Part Two.mp4 22.3 MB
8. Spark DataFrame Basics/2. Spark DataFrame Basics.mp4 21.1 MB
14. K-means Clustering/2. KMeans Clustering Documentation Example.mp4 20.9 MB
12. Logistic Regression/1. Logistic Regression Theory and Reading.mp4 20.6 MB
8. Spark DataFrame Basics/3. Spark DataFrame Basics Part Two.mp4 19.7 MB
10. Introduction to Machine Learning with MLlib/1. Introduction to Machine Learning and ISLR.mp4 18.9 MB
16. Natural Language Processing/3. NLP Tools Part Two.mp4 18.9 MB
8. Spark DataFrame Basics/6. Missing Data.mp4 17.2 MB
13. Decision Trees and Random Forests/5. Random Forest Classification Consulting Project Solutions.mp4 15.9 MB
3. Local VirtualBox Set-up/3. Setting up PySpark.mp4 15.6 MB
13. Decision Trees and Random Forests/1. Tree Methods Theory and Reading.mp4 14.7 MB
1. Introduction to Course/2. Course Overview.mp4 14.4 MB
16. Natural Language Processing/1. Introduction to Natural Language Processing.mp4 14.3 MB
7. Python Crash Course/2. Jupyter Notebook Overview.mp4 13.2 MB
14. K-means Clustering/1. K-means Clustering Theory and Reading.mp4 12.9 MB
15. Collaborative Filtering for Recommender Systems/1. Introduction to Recommender Systems.mp4 12.7 MB
11. Linear Regression/3. Regression Evaluation.mp4 12.0 MB
9. Spark DataFrame Project Exercise/1. DataFrame Project Exercise.mp4 11.9 MB
17. Spark Streaming with Python/3. Spark Streaming Twitter Project - Part.mp4 11.8 MB
1. Introduction to Course/1. Introduction.mp4 11.6 MB
2. Setting up Python with Spark/1. Set-up Overview.mp4 10.8 MB
11. Linear Regression/1. Linear Regression Theory and Reading.mp4 9.9 MB
4. AWS EC2 PySpark Set-up/3. SSH with Mac or Linux.mp4 9.3 MB
11. Linear Regression/5. Linear Regression Consulting Project.mp4 6.8 MB
14. K-means Clustering/4. Clustering Consulting Project.mp4 6.6 MB
12. Logistic Regression/4. Logistic Regression Consulting Project.mp4 6.3 MB
13. Decision Trees and Random Forests/4. Random Forest - Classification Consulting Project.mp4 5.4 MB
4. AWS EC2 PySpark Set-up/1. AWS EC2 Set-up Guide.mp4 5.3 MB
7. Python Crash Course/6. Python Crash Course Exercises.mp4 5.0 MB
8. Spark DataFrame Basics/1. Introduction to Spark DataFrames.mp4 4.7 MB
7. Python Crash Course/1. Introduction to Python Crash Course.mp4 3.1 MB
1. Introduction to Course/2.2 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 84.8 KB
13. Decision Trees and Random Forests/3. Decision Tress and Random Forest Code Along Examples.srt 30.8 KB
1. Introduction to Course/4. What is Spark Why Python.srt 30.5 KB
17. Spark Streaming with Python/5. Spark Streaming Twitter Project - Part Three.srt 29.3 KB
12. Logistic Regression/3. Logistic Regression Code Along.srt 27.3 KB
6. AWS EMR Cluster Setup/1. AWS EMR Setup.srt 26.4 KB
4. AWS EC2 PySpark Set-up/2. Creating the EC2 Instance.srt 24.4 KB
7. Python Crash Course/3. Python Crash Course Part One.srt 23.8 KB
12. Logistic Regression/2. Logistic Regression Example Code Along.srt 23.5 KB
11. Linear Regression/4. Linear Regression Example Code Along.srt 23.3 KB
16. Natural Language Processing/2. NLP Tools Part One.srt 22.9 KB
11. Linear Regression/6. Linear Regression Consulting Project Solutions.srt 22.7 KB
9. Spark DataFrame Project Exercise/2. DataFrame Project Exercise Solutions.srt 22.5 KB
11. Linear Regression/2. Linear Regression Documentation Example.srt 21.9 KB
13. Decision Trees and Random Forests/2. Tree Methods Documentation Examples.srt 20.7 KB
4. AWS EC2 PySpark Set-up/4. Installations on EC2.srt 20.2 KB
16. Natural Language Processing/4. Natural Language Processing Code Along Project.srt 19.6 KB
8. Spark DataFrame Basics/5. Groupby and Aggregate Operations.srt 19.0 KB
5. Databricks Setup/1. Databricks Setup.srt 18.9 KB
3. Local VirtualBox Set-up/2. Local Installation VirtualBox Part 2.srt 18.9 KB
14. K-means Clustering/3. Clustering Example Code Along.srt 18.5 KB
3. Local VirtualBox Set-up/1. Local Installation VirtualBox Part 1.srt 18.2 KB
17. Spark Streaming with Python/4. Spark Streaming Twitter Project - Part Two.srt 18.2 KB
15. Collaborative Filtering for Recommender Systems/2. Recommender System - Code Along Project.srt 18.0 KB
12. Logistic Regression/1. Logistic Regression Theory and Reading.srt 17.9 KB
10. Introduction to Machine Learning with MLlib/1. Introduction to Machine Learning and ISLR.srt 17.6 KB
7. Python Crash Course/4. Python Crash Course Part Two.srt 17.6 KB
17. Spark Streaming with Python/1. Introduction to Streaming with Spark!.srt 17.5 KB
17. Spark Streaming with Python/2. Spark Streaming Documentation Example.srt 17.4 KB
8. Spark DataFrame Basics/2. Spark DataFrame Basics.srt 16.4 KB
7. Python Crash Course/5. Python Crash Course Part Three.srt 16.1 KB
8. Spark DataFrame Basics/4. Spark DataFrame Basic Operations.srt 16.0 KB
10. Introduction to Machine Learning with MLlib/2. Machine Learning with Spark and Python with MLlib.srt 15.8 KB
12. Logistic Regression/5. Logistic Regression Consulting Project Solutions.srt 15.2 KB
1. Introduction to Course/2. Course Overview.srt 14.7 KB
14. K-means Clustering/2. KMeans Clustering Documentation Example.srt 14.7 KB
8. Spark DataFrame Basics/7. Dates and Timestamps.srt 14.6 KB
8. Spark DataFrame Basics/3. Spark DataFrame Basics Part Two.srt 14.4 KB
8. Spark DataFrame Basics/6. Missing Data.srt 13.5 KB
16. Natural Language Processing/1. Introduction to Natural Language Processing.srt 13.2 KB
7. Python Crash Course/7. Python Crash Course Exercise Solutions.srt 12.8 KB
13. Decision Trees and Random Forests/5. Random Forest Classification Consulting Project Solutions.srt 11.8 KB
13. Decision Trees and Random Forests/1. Tree Methods Theory and Reading.srt 11.7 KB
14. K-means Clustering/5. Clustering Consulting Project Solutions.srt 11.5 KB
7. Python Crash Course/2. Jupyter Notebook Overview.srt 11.4 KB
11. Linear Regression/3. Regression Evaluation.srt 10.8 KB
16. Natural Language Processing/3. NLP Tools Part Two.srt 10.7 KB
14. K-means Clustering/1. K-means Clustering Theory and Reading.srt 10.7 KB
2. Setting up Python with Spark/1. Set-up Overview.srt 10.2 KB
15. Collaborative Filtering for Recommender Systems/1. Introduction to Recommender Systems.srt 10.0 KB
3. Local VirtualBox Set-up/3. Setting up PySpark.srt 8.3 KB
11. Linear Regression/1. Linear Regression Theory and Reading.srt 8.1 KB
4. AWS EC2 PySpark Set-up/3. SSH with Mac or Linux.srt 7.5 KB
17. Spark Streaming with Python/3. Spark Streaming Twitter Project - Part.srt 7.3 KB
9. Spark DataFrame Project Exercise/1. DataFrame Project Exercise.srt 5.4 KB
12. Logistic Regression/4. Logistic Regression Consulting Project.srt 5.3 KB
11. Linear Regression/5. Linear Regression Consulting Project.srt 4.9 KB
14. K-means Clustering/4. Clustering Consulting Project.srt 4.7 KB
1. Introduction to Course/1. Introduction.srt 4.5 KB
4. AWS EC2 PySpark Set-up/1. AWS EC2 Set-up Guide.srt 4.4 KB
13. Decision Trees and Random Forests/4. Random Forest - Classification Consulting Project.srt 3.8 KB
8. Spark DataFrame Basics/1. Introduction to Spark DataFrames.srt 3.6 KB
7. Python Crash Course/6. Python Crash Course Exercises.srt 2.5 KB
7. Python Crash Course/1. Introduction to Python Crash Course.srt 2.4 KB
18. Bonus/1. Bonus Lecture.html 532 bytes
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/2.1 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/3.2 Great Example from Databricks.html 150 bytes
12. Logistic Regression/3.1 Explanation of AUC.html 148 bytes
[FreeCourseWorld.Com].url 54 bytes
[DesireCourse.Net].url 51 bytes
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[DesireCourse.Net] Udemy - Spark and Python for Big Data with PySpark

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