Master Regression & Prediction with Pandas and Python [2024]

سرفصل های دوره

Learn to Master Regression and Prediction with Pandas and Python for Data Science and Machine Learning

1 - Introduction

1 - Introduction

2 - Setup of the Anaconda Cloud Notebook

3 - Download and installation of the Anaconda Distribution optional

4 - The Conda Package Management System optional

2 - Master Python for Data Handling

5 - Overview of Python for Data Handling

6 - Python Integer

7 - Python Float

8 - Python Strings I

9 - Python Strings II Intermediate String Methods

10 - Python Strings III DateTime Objects and Strings

11 - Overview of Python Native Data Storage Structures

12 - Python Set

13 - Python Tuple

14 - Python Dictionary

15 - Python List

16 - Overview of Python Data Transformers and Functions

17 - Python Whileloop

18 - Python Forloop

19 - Python Logic Operators and conditional code branching

20 - Python Functions I Some theory

21 - Python Functions II create your own functions

22 - Python Object Oriented Programming I Some theory

23 - Python Object Oriented Programming II create your own custom objects

24 - Python Object Oriented Programming III Files and Tables

25 - Python Object Oriented Programming IV Recap and More

3 - Master Pandas for Data Handling

26 - Master Pandas for Data Handling Overview

27 - Pandas theory and terminology

28 - Creating a Pandas DataFrame from scratch

29 - Pandas File Handling Overview

30 - Pandas File Handling The csv file format

31 - Pandas File Handling The xlsx file format

32 - Pandas File Handling SQLdatabase files and Pandas DataFrame

33 - Pandas Operations Techniques Overview

34 - Pandas Operations Techniques Object Inspection

35 - Pandas Operations Techniques DataFrame Inspection

36 - Pandas Operations Techniques Column Selections

37 - Pandas Operations Techniques Row Selections

38 - Pandas Operations Techniques Conditional Selections

39 - Pandas Operations Techniques Scalers and Standardization

40 - Pandas Operations Techniques Concatenate DataFrames

41 - Pandas Operations Techniques Joining DataFrames

42 - Pandas Operations Techniques Merging DataFrames

43 - Pandas Operations Techniques Transpose Pivot Functions

44 - Pandas Data Preparation I Overview workflow

45 - Pandas Data Preparation II Edit DataFrame labels

46 - Pandas Data Preparation III Duplicates

47 - Pandas Data Preparation IV Missing Data Imputation

48 - Pandas Data Preparation V Data Binnings Extra Video

49 - Pandas Data Preparation VI Indicator Features Extra Video

50 - Pandas Data Description I Overview

51 - Pandas Data Description II Sorting and Ranking

52 - Pandas Data Description III Descriptive Statistics

53 - Pandas Data Description IV Crosstabulations Groupings

54 - Pandas Data Visualization I Overview

55 - Pandas Data Visualization II Histograms

56 - Pandas Data Visualization III Boxplots

57 - Pandas Data Visualization IV Scatterplots

58 - Pandas Data Visualization V Pie Charts

59 - Pandas Data Visualization VI Line plots

Files.zip

4 - Master Regression Models for Prediction

60 - Regression Prediction and Supervised Learning Section Overview I

61 - The Traditional Simple Regression Model II

62 - The Traditional Simple Regression Model III

63 - Some practical and useful modelling concepts IV

64 - Some practical and useful modelling concepts V

65 - Linear Multiple Regression model VI

66 - Linear Multiple Regression model VII

67 - Multivariate Polynomial Multiple Regression models VIII

68 - Multivariate Polynomial Multiple Regression models VIIII

69 - Regression Regularization Lasso and Ridge models X

70 - Decision Tree Regression models

71 - Random Forest Regression

72 - Voting Regression

Files.zip

5 - Feedforward Networks and Advanced Regression Models

73 - Overview

74 - Artificial Neural Networks Feedforward Networks and the MultiLayer Perceptron

75 - Feedforward MultiLayer Perceptrons for Prediction tasks

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تولید کننده: Udemy