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لغة R | Unboxing Big Data

Unboxing Big Data

Unboxing Big Data

Unboxing Big Data channel has been created with an aim to teach Big Data tools from scratch. It lets you dive in to Big Data ecosystem which includes frameworks/tools such as Apache Hadoop, Apache Spark, Apache Flink, Apache Storm, Apache Hive, Apache Pig, Apache Flume, Apache Kafka and many more.

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  1. 1 | A short introduction to R programming language 00:03:13
  2. 2 | R Tutorial #1 Getting Help in R language 00:04:43
  3. 3 | R Tutorial #2 Understanding RStudio Interface 00:03:10
  4. 4 | R Tutorial #3 Basic Calculations in R language 00:05:24
  5. 5 | R Tutorial #4 Working with data types in R programming language 00:05:13
  6. 6 | R Tutorial #5 Basic Calculations in R language (Part - 2) (With Examples) 00:03:53
  7. 7 | R Tutorial #6 Different Types of Operators in R language 00:06:49
  8. 8 | R Tutorial#7 Different Data Structures in R language (A Quick Intro) 00:03:03
  9. 9 | R Tutorial #8 Vectors in R language (With Examples) 00:06:14
  10. 10 | R Tutorial #9 Matrices and its operations in R language (With Examples) 00:10:23
  11. 11 | R Tutorial #10 Data Frames in R language (With Examples) 00:10:00
  12. 12 | R Tutorial #11 Working with List in R (With Examples) 00:05:36
  13. 13 | R Tutorial #12 Working with Arrays in R language (With Examples) 00:08:04
  14. 14 | R Tutorial #13 Working with Factors in R language (With Examples) 00:07:07
  15. 15 | Learn Subsetting in R programming language (in quick time) 00:09:40
  16. 16 | Conditional Statements and Loops in R 00:05:48
  17. 17 | String Functions in R 00:13:07
  18. 18 | Regular Expressions in R language (With Examples) 00:23:33
  19. 19 | Tutorial on Apply Family of Functions in R language 00:09:34
  20. 20 | Working with date and timestamp in R language 00:17:39
  21. 21 | Reading and Writing CSV Files in R language (A short little video) 00:05:45
  22. 22 | SQLDF : Writing SQL Queries in R language 00:06:13
  23. 23 | Understanding DPLYR package and its functions in R language (With Examples) 00:31:16
  24. 24 | Tidy Messy Data with TidyR package (With Examples) 00:17:55
  25. 25 | Beginner's Guide to R : Easy Ways to do basic data analysis 00:18:33
  26. 26 | Handling Missing Values in R 00:14:14
  27. 27 | Fundamentals of Text Mining and Word Cloud in R language 00:12:07
  28. 28 | Basic Plots (Part - 1) - How to draw Bar Plot in R language ? 00:07:38
  29. 29 | Basic Plots (Part - 2) - How to draw Scatter Plot in R language ? 00:06:35
  30. 30 | Basic Plots (Part - 3) - How to draw Line Chart in R language ? 00:04:38
  31. 31 | Basic Plots (Part - 4) - How to draw Pie Chart in R language ? 00:04:57
  32. 32 | How to draw Heat Map in R language ? 00:07:16
  33. 33 | How to draw Box Plot in R language ? 00:05:13
  34. 34 | How to draw Bollinger Band in R language ? 00:08:31
  35. 35 | Learn GGPLOT2 and its layers in R language in an easiest way. 00:16:02
  36. 36 | Learn PLOTLY in R language in an easiest way (With Examples) 00:18:14
  37. 37 | How to get access to Twitter's data using R language ? 00:11:27
  38. 38 | Getting Started with R Markdown : Creating first R Markdown document 00:10:25
  39. 39 | Getting Started with R Markdown Flexdashboard 00:07:58
  40. 40 | R Shiny Tutorial 00:06:50
  41. 41 | R Shiny Tutorial (Part-2) : Building the basic User Interface of Shiny App 00:10:05
  42. 42 | R Shiny Tutorial (Part-3) : Building Interactive Shiny App in R language 00:12:16
  43. 43 | How to get CHATGPT in RSTUDIO IDE 00:03:43
  44. 44 | Machine Learning Tutorial : Data Pre-processing in R language 00:13:40
  45. 45 | Machine Learning Tutorial : Learn Simple Linear Regression in R (With Example) 00:19:52
  46. 46 | Machine Learning Tutorial : Assumptions of Linear Regression 00:07:31
  47. 47 | Machine Learning Tutorial: Multiple Linear Regression using R 00:10:42
  48. 48 | Introduction to Polynomial Regression 00:05:42
  49. 49 | Implementation of Polynomial Regression in R Comparison of Linear and Polynomial Regression 00:15:13
  50. 50 | Introduction to SVR (Support Vector Regression) 00:05:25
  51. 51 | Implementation of Support Vector Regression in R Language 00:10:22
  52. 52 | What is Classification in Machine Learning ? (A 2-minute tutorial) 00:02:48
  53. 53 | How to perform Logistic Regression in R programming language (Step-By-Step) 00:12:31
  54. 54 | How the K-Nearest Neighbors (KNN) Algorithm Works ? (A 5-minute tutorial) 00:05:14
  55. 55 | Implementation of K-Nearest Neighbors (KNN) algorithm in R programming language 00:09:56
  56. 56 | A short introduction to Support Vector Machine (SVM) 00:07:37
  57. 57 | Implementing Support Vector Machine (SVM) in R language 00:08:37
  58. 58 | Naive Bayes in R : Understanding Bayes Theorem 00:05:24
  59. 59 | How Naive Bayes Algorithm works? 00:08:48
  60. 60 | Implementation of Naive Bayes Algorithm in R language (in less than 10 minutes) 00:09:10
  61. 61 | Machine Learning Tutorial - Working of Decision Tree Classifier 00:07:35
  62. 62 | Implementation of Decision Tree Classifier in RStudio (in less than 10 minutes) 00:09:30
  63. 63 | A short little introduction to Random Forest Classifier 00:03:29
  64. 64 | Implementation of Random Forest Classifier in RStudio 00:08:09
  65. 65 | INTRO TO CLUSTERING DIFFERENCE BETWEEN SUPERVISED AND UNSUPERVISED LEARNING 00:03:34
  66. 66 | INTRO TO K-MEANS CLUSTERING 00:03:54
  67. 67 | Implementation of K-Means Clustering in R (Part - 1) 00:03:05
  68. 68 | Implementation of K-Means Clustering in R (Part - 2) 00:11:32
  69. 69 | Basics of Apriori : Association Rule Learning Model 00:08:16
  70. 70 | Implementation of Apriori in R programming language 00:17:43
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    10-08-2024