Data Analyst Full Course - Comprehensive Guide for 2024

Data Analyst Full Course - Comprehensive Guide for 2024

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Bagging and Random Forest

54 of 70

54 of 70

Bagging and Random Forest

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Data Analyst Full Course - Comprehensive Guide for 2024

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  1. 1 Introduction
  2. 2 Who is Data Analyst and their Key Roles
  3. 3 Real-world Applications
  4. 4 Introduction to Data Analytics
  5. 5 What is Statistics?
  6. 6 Inter-quartile Range
  7. 7 Box-plot - 5 number summary
  8. 8 Data cleaning using Excel
  9. 9 Functions in Excel
  10. 10 Types of Functions in Excel
  11. 11 Sort and Filter
  12. 12 Data Validation in Excel
  13. 13 Pivot Table in Excel
  14. 14 Data Visualization using Excel
  15. 15 SQL - Introduction and Installation
  16. 16 Data Types in SQL
  17. 17 Hands-on based on HR Database Management System
  18. 18 Python Numpy Array
  19. 19 Numpy Methods
  20. 20 Numpy Array Mathematics
  21. 21 Numpy Matrix
  22. 22 Numpy Save and Load
  23. 23 Pandas- Introduction
  24. 24 Pandas Series Object
  25. 25 Pandas- Changing Index
  26. 26 Pandas- Series object from Dictionary
  27. 27 Pandas- Dataframe in-built Function
  28. 28 Pandas- iloc and loc function
  29. 29 Pandas- Dropping Rows and Column
  30. 30 Matplotlib Library
  31. 31 Matplotlib Line Plot
  32. 32 Matplotlib- Barplot
  33. 33 Matplotlib- Scatter plot
  34. 34 Matplotlib Histogram
  35. 35 Seaborn Line plot
  36. 36 Seaborn Barplot
  37. 37 Seaborn Scatterplot
  38. 38 Seaborn Histogram/Distplot
  39. 39 Tableau- Introduction
  40. 40 Tableau Architecture
  41. 41 Tableau Dashboards
  42. 42 Regression and its Use cases
  43. 43 Types of Regression [Linear Regression and Multiple Linear Regression]
  44. 44 Hands-on Linear Regression and MLR
  45. 45 Case study on Salary Expectation
  46. 46 Logistic Regression and its use cases
  47. 47 Credit card fraud detection using Logistic Regression
  48. 48 Naive Bayes Algorithm
  49. 49 Diabetes Prediction using Naive Bayes
  50. 50 Decision Tree
  51. 51 Decision Tree - CART
  52. 52 How are Decision Tree built?
  53. 53 Hands-on Decision Tree
  54. 54 Bagging and Random Forest
  55. 55 Hands-on Random Forest
  56. 56 Hierarchical Clustering
  57. 57 Types of Hierarchical Clustering
  58. 58 Agglomerative Hierarchical Clustering- Working
  59. 59 Distance formulas for Clustering [Eucledian Distance; Manhattan Distance; Minkowski Distance; Jaccard Similarity Coefficient]
  60. 60 Finding Optimal Numbers of Clustering
  61. 61 Generative AI- Introduction
  62. 62 Discriminative vs. Generative AI
  63. 63 How Gen AI Works?
  64. 64 Types of Generative AI
  65. 65 ChatGPT Basics
  66. 66 Introduction of Data Analysis using ChatGPT
  67. 67 Loading the Dataset
  68. 68 Data Analysis Project using ChatGPT
  69. 69 Data Analysis Project using Python
  70. 70 Summary

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