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| [CourseClub.ME].url |
122б |
| [FCS Forum].url |
133б |
| [FreeCourseSite.com].url |
127б |
| 1. [Activity] Find the Most Popular Movie.mp4 |
30.57Мб |
| 1. [Activity] Find the Most Popular Movie.srt |
9.32Кб |
| 1.1 popular-movies-dataframe.py |
933б |
| 1. Introducing Elastic MapReduce.mp4 |
48.01Мб |
| 1. Introducing Elastic MapReduce.srt |
9.03Кб |
| 1. Introducing MLLib.mp4 |
30.93Мб |
| 1. Introducing MLLib.srt |
14.34Кб |
| 1. Introducing SparkSQL.mp4 |
49.81Мб |
| 1. Introducing SparkSQL.srt |
22.00Кб |
| 1. Introduction.mp4 |
35.48Мб |
| 1. Introduction.srt |
5.38Кб |
| 1. Learning More about Spark and Data Science.mp4 |
82.96Мб |
| 1. Learning More about Spark and Data Science.srt |
7.31Кб |
| 1. Spark Streaming.mp4 |
44.97Мб |
| 1. Spark Streaming.srt |
14.33Кб |
| 1. What's new in Spark 3.mp4 |
151.64Мб |
| 1. What's new in Spark 3.srt |
12.14Кб |
| 10. [Activity] Counting Word Occurrences using flatmap().mp4 |
54.35Мб |
| 10. [Activity] Counting Word Occurrences using flatmap().srt |
12.75Кб |
| 10.1 word-count.py |
441б |
| 10.2 Book.txt |
258.67Кб |
| 10. Item-Based Collaborative Filtering in Spark, cache(), and persist().mp4 |
34.35Мб |
| 10. Item-Based Collaborative Filtering in Spark, cache(), and persist().srt |
13.38Кб |
| 11. [Activity] Improving the Word Count Script with Regular Expressions.mp4 |
40.40Мб |
| 11. [Activity] Improving the Word Count Script with Regular Expressions.srt |
40.41Мб |
| 11. [Activity] Running the Similar Movies Script using Spark's Cluster Manager.mp4 |
138.20Мб |
| 11. [Activity] Running the Similar Movies Script using Spark's Cluster Manager.srt |
31.32Кб |
| 11.1 movie-similarities-dataframe.py |
4.22Кб |
| 11.1 word-count-better.py |
539б |
| 12. [Activity] Sorting the Word Count Results.mp4 |
57.54Мб |
| 12. [Activity] Sorting the Word Count Results.srt |
13.37Кб |
| 12. [Exercise] Improve the Quality of Similar Movies.mp4 |
33.96Мб |
| 12. [Exercise] Improve the Quality of Similar Movies.srt |
6.47Кб |
| 12.1 word-count-better-sorted.py |
690б |
| 13. [Exercise] Find the Total Amount Spent by Customer.mp4 |
31.22Мб |
| 13. [Exercise] Find the Total Amount Spent by Customer.srt |
7.36Кб |
| 13.1 customer-orders.csv.html |
115б |
| 14. [Excercise] Check your Results, and Now Sort them by Total Amount Spent..mp4 |
49.21Мб |
| 14. [Excercise] Check your Results, and Now Sort them by Total Amount Spent..srt |
9.05Кб |
| 14.1 total-spent-by-customer.py |
529б |
| 14.2 customer-orders.csv.html |
115б |
| 15.1 total-spent-by-customer-sorted.py |
735б |
| 15.2 customer-orders.csv.html |
115б |
| 15. Check Your Sorted Implementation and Results Against Mine..mp4 |
24.70Мб |
| 15. Check Your Sorted Implementation and Results Against Mine..srt |
4.48Кб |
| 2. [Activity] Executing SQL commands and SQL-style functions on a DataFrame.mp4 |
67.08Мб |
| 2. [Activity] Executing SQL commands and SQL-style functions on a DataFrame.srt |
17.66Кб |
| 2. [Activity] Setting up your AWS Elastic MapReduce Account and Setting Up PuTTY.mp4 |
112.66Мб |
| 2. [Activity] Setting up your AWS Elastic MapReduce Account and Setting Up PuTTY.srt |
112.68Мб |
| 2. [Activity] Structured Streaming in Python.mp4 |
80.99Мб |
| 2. [Activity] Structured Streaming in Python.srt |
15.01Кб |
| 2. [Activity] Use Broadcast Variables to Display Movie Names Instead of ID Numbers.mp4 |
90.65Мб |
| 2. [Activity] Use Broadcast Variables to Display Movie Names Instead of ID Numbers.srt |
25.01Кб |
| 2. [Activity] Using Spark ML to Produce Movie Recommendations.mp4 |
100.50Мб |
| 2. [Activity] Using Spark ML to Produce Movie Recommendations.srt |
22.92Кб |
| 2.1 movie-recommendations-als-dataframe.py |
1.97Кб |
| 2.1 popular-movies-nice-dataframe.py |
1.74Кб |
| 2.1 spark-sql.py |
981б |
| 2.1 structured-streaming.py |
1.82Кб |
| 2.2 access_log.txt |
10.14Мб |
| 2.2 fakefriends.csv |
8.55Кб |
| 2. Bonus Lecture More courses to explore!.html |
6.83Кб |
| 2. How to Use This Course.mp4 |
11.35Мб |
| 2. How to Use This Course.srt |
6.22Кб |
| 2. Introduction to Spark.mp4 |
58.30Мб |
| 2. Introduction to Spark.srt |
17.25Кб |
| 3. [Exercise] Use Windows with Structured Streaming to Track Most-Viewed URL's.mp4 |
31.44Мб |
| 3. [Exercise] Use Windows with Structured Streaming to Track Most-Viewed URL's.srt |
10.57Кб |
| 3.1 access_log.txt |
10.14Мб |
| 3.1 fakefriends-header.csv |
8.57Кб |
| 3.1 most-popular-superhero-dataframe.py |
1.19Кб |
| 3.2 Marvel Names.txt |
343.60Кб |
| 3.2 spark-sql-dataframe.py |
632б |
| 3.3 Marvel Graph.txt |
1.60Мб |
| 3. Analyzing the ALS Recommendations Results.mp4 |
30.03Мб |
| 3. Analyzing the ALS Recommendations Results.srt |
10.25Кб |
| 3. Find the Most Popular Superhero in a Social Graph.mp4 |
19.73Мб |
| 3. Find the Most Popular Superhero in a Social Graph.srt |
7.18Кб |
| 3. Partitioning.mp4 |
40.88Мб |
| 3. Partitioning.srt |
7.63Кб |
| 3. The Resilient Distributed Dataset (RDD).mp4 |
68.76Мб |
| 3. The Resilient Distributed Dataset (RDD).srt |
19.65Кб |
| 3. Udemy 101 Getting the Most From This Course.mp4 |
19.74Мб |
| 3. Udemy 101 Getting the Most From This Course.srt |
8.09Кб |
| 3. Using DataFrames instead of RDD's.mp4 |
60.26Мб |
| 3. Using DataFrames instead of RDD's.srt |
17.91Кб |
| 4. [Activity]Getting Set Up Installing Python, a JDK, Spark, and its Dependencies..mp4 |
227.08Мб |
| 4. [Activity]Getting Set Up Installing Python, a JDK, Spark, and its Dependencies..srt |
24.11Кб |
| 4. [Activity] Linear Regression with Spark ML.mp4 |
101.54Мб |
| 4. [Activity] Linear Regression with Spark ML.srt |
31.59Кб |
| 4. [Activity] Run the Script - Discover Who the Most Popular Superhero is!.mp4 |
87.61Мб |
| 4. [Activity] Run the Script - Discover Who the Most Popular Superhero is!.srt |
17.94Кб |
| 4. [Exercise] Friends by Age, with DataFrames.mp4 |
7.80Мб |
| 4. [Exercise] Friends by Age, with DataFrames.srt |
3.56Кб |
| 4.1 fakefriends-header.csv |
8.57Кб |
| 4.1 most-popular-superhero-dataframe.py |
1.19Кб |
| 4.1 movie-similarities-1m.py |
3.63Кб |
| 4.1 ratings-counter.py |
452б |
| 4.1 regression.txt |
11.72Кб |
| 4.1 top-urls.py |
1.80Кб |
| 4.1 winutils.exe.html |
108б |
| 4.2 access_log.txt |
10.14Мб |
| 4.2 Apache Spark.html |
100б |
| 4.2 Marvel Graph.txt |
1.60Мб |
| 4.2 spark-linear-regression.py |
1.96Кб |
| 4.3 JDK.html |
127б |
| 4.3 Marvel Names.txt |
343.60Кб |
| 4. Create Similar Movies from One Million Ratings - Part 1.mp4 |
51.10Мб |
| 4. Create Similar Movies from One Million Ratings - Part 1.srt |
8.90Кб |
| 4. Exercise Solution Using Structured Streaming with Windows.mp4 |
66.63Мб |
| 4. Exercise Solution Using Structured Streaming with Windows.srt |
11.72Кб |
| 4. Ratings Histogram Walkthrough.mp4 |
83.05Мб |
| 4. Ratings Histogram Walkthrough.srt |
20.70Кб |
| 5. [Activity] Create Similar Movies from One Million Ratings - Part 2.mp4 |
104.28Мб |
| 5. [Activity] Create Similar Movies from One Million Ratings - Part 2.srt |
17.80Кб |
| 5. [Activity] Installing the MovieLens Movie Rating Dataset.mp4 |
45.38Мб |
| 5. [Activity] Installing the MovieLens Movie Rating Dataset.srt |
6.21Кб |
| 5. [Exercise] Find the Most Obscure Superheroes.mp4 |
11.27Мб |
| 5. [Exercise] Find the Most Obscure Superheroes.srt |
5.19Кб |
| 5. [Exercise] Using Decision Trees in Spark ML to Predict Real Estate Prices.mp4 |
34.20Мб |
| 5. [Exercise] Using Decision Trees in Spark ML to Predict Real Estate Prices.srt |
15.45Кб |
| 5.1 fakefriends-header.csv |
8.57Кб |
| 5.1 realestate.csv |
21.14Кб |
| 5.2 friends-by-age-dataframe.py |
865б |
| 5. Exercise Solution Friends by Age, with DataFrames.mp4 |
71.61Мб |
| 5. Exercise Solution Friends by Age, with DataFrames.srt |
17.51Кб |
| 5. GraphX.mp4 |
12.05Мб |
| 5. GraphX.srt |
4.15Кб |
| 5. KeyValue RDD's, and the Average Friends by Age Example.mp4 |
110.31Мб |
| 5. KeyValue RDD's, and the Average Friends by Age Example.srt |
28.11Кб |
| 6. [Activity] Running the Average Friends by Age Example.mp4 |
49.16Мб |
| 6. [Activity] Running the Average Friends by Age Example.srt |
9.24Кб |
| 6. [Activity] Run your first Spark program! Ratings histogram example..mp4 |
65.82Мб |
| 6. [Activity] Run your first Spark program! Ratings histogram example..srt |
10.47Кб |
| 6. [Activity] Word Count, with DataFrames.mp4 |
63.24Мб |
| 6. [Activity] Word Count, with DataFrames.srt |
23.12Кб |
| 6.1 book.txt |
258.67Кб |
| 6.1 friends-by-age.py |
618б |
| 6.1 most-obscure-superheroes.py |
1.29Кб |
| 6.1 ratings-counter.py |
452б |
| 6.1 realestate.csv |
21.14Кб |
| 6.2 fakefriends.csv.html |
111б |
| 6.2 real-estate.py |
1.83Кб |
| 6.2 word-count-better-sorted-dataframe.py |
773б |
| 6. Create Similar Movies from One Million Ratings - Part 3.mp4 |
50.60Мб |
| 6. Create Similar Movies from One Million Ratings - Part 3.srt |
6.72Кб |
| 6. Exercise Solution Decision Trees with Spark.mp4 |
59.00Мб |
| 6. Exercise Solution Decision Trees with Spark.srt |
14.22Кб |
| 6. Exercise Solution Most Obscure Superheroes.mp4 |
41.46Мб |
| 6. Exercise Solution Most Obscure Superheroes.srt |
9.86Кб |
| 7. [Activity] Minimum Temperature, with DataFrames (using a custom schema).mp4 |
93.63Мб |
| 7. [Activity] Minimum Temperature, with DataFrames (using a custom schema).srt |
31.19Кб |
| 7.1 1800.csv.html |
104б |
| 7.1 min-temperatures-dataframe.py |
1.63Кб |
| 7.2 1800.csv |
61.26Кб |
| 7.2 min-temperatures.py |
739б |
| 7. Filtering RDD's, and the Minimum Temperature by Location Example.mp4 |
54.45Мб |
| 7. Filtering RDD's, and the Minimum Temperature by Location Example.srt |
13.51Кб |
| 7. Superhero Degrees of Separation Introducing Breadth-First Search.mp4 |
61.81Мб |
| 7. Superhero Degrees of Separation Introducing Breadth-First Search.srt |
18.74Кб |
| 7. Troubleshooting Spark on a Cluster.mp4 |
37.49Мб |
| 7. Troubleshooting Spark on a Cluster.srt |
6.48Кб |
| 8. [Activity]Running the Minimum Temperature Example, and Modifying it for Maximums.mp4 |
56.24Мб |
| 8. [Activity]Running the Minimum Temperature Example, and Modifying it for Maximums.srt |
8.50Кб |
| 8. [Exercise] Implement Total Spent by Customer with DataFrames.mp4 |
9.32Мб |
| 8. [Exercise] Implement Total Spent by Customer with DataFrames.srt |
4.38Кб |
| 8.1 customer-orders.csv |
143.41Кб |
| 8.1 min-temperatures.py |
739б |
| 8.2 1800.csv.html |
104б |
| 8. More Troubleshooting, and Managing Dependencies.mp4 |
54.73Мб |
| 8. More Troubleshooting, and Managing Dependencies.srt |
11.14Кб |
| 8. Superhero Degrees of Separation Accumulators, and Implementing BFS in Spark.mp4 |
47.88Мб |
| 8. Superhero Degrees of Separation Accumulators, and Implementing BFS in Spark.srt |
15.77Кб |
| 9. [Activity] Running the Maximum Temperature by Location Example.mp4 |
37.29Мб |
| 9. [Activity] Running the Maximum Temperature by Location Example.srt |
6.21Кб |
| 9. [Activity] Superhero Degrees of Separation Review the Code and Run it.mp4 |
93.99Мб |
| 9. [Activity] Superhero Degrees of Separation Review the Code and Run it.srt |
16.36Кб |
| 9.1 customer-orders.csv |
143.41Кб |
| 9.1 degrees-of-separation.py |
3.64Кб |
| 9.1 max-temperatures.py |
739б |
| 9.2 total-spent-customer-sorted-dataframe.py |
1.04Кб |
| 9. Exercise Solution Total Spent by Customer, with DataFrames.mp4 |
32.41Мб |
| 9. Exercise Solution Total Spent by Customer, with DataFrames.srt |
9.10Кб |