Data Analysis and Machine Learning: Python + GPT 3.5 & GPT 4

سرفصل های دوره

Hands-on Data Analysis and Machine Learning in Python + GPT 3.5. Apply GPT-4 to Analyze and Develop ML Models Smoothly.

1 - Setting Up Your Analysis Environment

1 - Install Python and Jupyter Notebook.html

1 - Mac.pdf

1 - Windows.pdf

2 - Setting up ChatGPT and GPT 4

3 - Download Practice datasets.html

3 - Practice-datasets.zip

3 - Practice-datasets-for-GPT-4.zip

2 - Data Analysis and Its Workflow

4 - Data Analysis and Its Characteristics

5 - Complete data analysis workflow

3 - Statistical Analysis and Its Workflow

6 - Statistical Analysis and Its Characteristics

7 - Confidence level significance level and Pvalue

8 - Complete hypothesis testing workflow

4 - Machine Learning and Its Workflow

9 - Machine Learning and Its Characteristics

10 - Complete Machine Learning Workflow

5 - Python Programming Basics Level 1

11 - Your First Python Code

12 - Variables and naming conventions

13 - Data types integers float strings boolean

14 - Type conversion and casting

15 - Arithmetic operators

16 - Comparison operators

17 - Logical operators and or not

6 - Python Programming Basics Level 2

18 - Lists creation indexing slicing modifying

19 - Sets unique elements operations

20 - Dictionaries keyvalue pairs methods

21 - Conditional statements if elif else

22 - Logical expressions in conditions

23 - Looping structures for loops while loops

24 - Defining Creating and Calling functions

7 - Python GPT 35 Learn Data Cleaning

25 - Loading dataset

26 - Handling missing values

27 - Deal with inconsistent data

28 - Dealing with missidentified data types

29 - Dealing with duplicated data

8 - Python GPT 35 Learn Data Manipulation

30 - Sorting and arranging dataset

31 - Filter data based on conditions

32 - Merging or adding variables

33 - Concatenating extra data

9 - Python GPT 35 Learn Data Preprocessing

34 - Feature engineering

35 - Extracting day months year

36 - Feature encoding

37 - Creating dummy variables

38 - Data normalizing

39 - Splitting data

10 - Python GPT 35 Learn Regressor Machine Learning

40 - Linear regression ML model

41 - Decision Tree regression ML model

42 - Random Forest regression ML model

43 - Support Vector regression ML model

11 - Python GPT 35 Learn Classification Machine Learning

44 - Logistic Regression ML model

45 - Decision Tree classification ML model

46 - Random Forest classification ML model

47 - K Nearest Neighbours classification ML model

12 - Python GPT 35 Learn Clustering Machine Learning

48 - KMeans Clustering ML model

13 - Python GPT 4 Rapid Data Cleaning

49 - Getting Started with GPT4 Data Analyst

50 - Identify missing values

51 - Impute missing values

52 - Exploring data types

53 - Finding inconsistent values

54 - Dropping inconsistent values

55 - Dealing with duplicates

14 - Python GPT 4 Instant Data Manipulation

56 - Sorting dataset

57 - Filtering datasets

58 - Inner joining method

59 - Other joining methods

60 - Boxcox transformation

61 - Feature binning

62 - Feature encoding

63 - Creating dummy variables

15 - Python GPT 4 Fasttrack Data Analysis

64 - Nominal data analysis

65 - Descriptive analysis

66 - Group by data analysis

67 - Crosstabulation analysis

68 - Correlation analysis

16 - Python GPT 4 Quick Hypothesis Testing

69 - Oneway ANOVA analysis

70 - Pearson correlation analysis

71 - Regression analysis

17 - Python GPT 4 Build Machine Learning Models

72 - Feature scaling and preprocessing

73 - Splitting data into train and test sets

74 - Build and evaluate ML models

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تولید کننده: Udemy