[FTUForum.com] [UDEMY] Complete Data Wrangling & Data Visualisation With Python [FTU]

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Size

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328 B

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294 B

0. Websites you may like/How you can help Team-FTU.txt

237 B

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Welcome to the Course.mp4

12 MB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Welcome to the Course.vtt

2.9 kB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/2.1 Data and Code.zip.zip

123 MB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/2. Data & Script For the Course.html

123 B

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.mp4

105 MB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.vtt

10 kB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.mp4

50 MB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.vtt

3.8 kB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPythonJupyter.mp4

103 MB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPythonJupyter.vtt

17 kB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. ipython in Browser.mp4

40 MB

1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. ipython in Browser.vtt

3.5 kB

2. Read in Data From Different Sources With Pandas/1. What are Pandas.mp4

85 MB

2. Read in Data From Different Sources With Pandas/1. What are Pandas.vtt

9.8 kB

2. Read in Data From Different Sources With Pandas/2. Read CSV Data.mp4

54 MB

2. Read in Data From Different Sources With Pandas/2. Read CSV Data.vtt

5.7 kB

2. Read in Data From Different Sources With Pandas/3. Read Excel Data.mp4

42 MB

2. Read in Data From Different Sources With Pandas/3. Read Excel Data.vtt

3.6 kB

2. Read in Data From Different Sources With Pandas/4. Read in HTML Data.mp4

130 MB

2. Read in Data From Different Sources With Pandas/4. Read in HTML Data.vtt

11 kB

3. Data Cleaning/1. Remove NA Values.mp4

56 MB

3. Data Cleaning/1. Remove NA Values.vtt

6.5 kB

3. Data Cleaning/2. Missing Values in a Real Dataset.mp4

37 MB

3. Data Cleaning/2. Missing Values in a Real Dataset.vtt

6.3 kB

3. Data Cleaning/3. Data Imputation.mp4

56 MB

3. Data Cleaning/3. Data Imputation.vtt

9.0 kB

3. Data Cleaning/4. Imputing Qualitative Values.mp4

21 MB

3. Data Cleaning/4. Imputing Qualitative Values.vtt

3.3 kB

3. Data Cleaning/5. Theory Behind k-NN Algorithm.mp4

96 MB

3. Data Cleaning/5. Theory Behind k-NN Algorithm.vtt

6.5 kB

3. Data Cleaning/6. Use k-NN for Data Imputation.mp4

44 MB

3. Data Cleaning/6. Use k-NN for Data Imputation.vtt

6.1 kB

4. Basic Data Wrangling/1. Basic Principles.mp4

26 MB

4. Basic Data Wrangling/1. Basic Principles.vtt

4.6 kB

4. Basic Data Wrangling/2. Preliminary Data Explorations.mp4

64 MB

4. Basic Data Wrangling/2. Preliminary Data Explorations.vtt

7.8 kB

4. Basic Data Wrangling/3. Basic Data Handling With Conditional Statements.mp4

49 MB

4. Basic Data Wrangling/3. Basic Data Handling With Conditional Statements.vtt

4.1 kB

4. Basic Data Wrangling/4. Drop ColumnRow.mp4

48 MB

4. Basic Data Wrangling/4. Drop ColumnRow.vtt

4.3 kB

4. Basic Data Wrangling/5. Change Column Name.mp4

25 MB

4. Basic Data Wrangling/5. Change Column Name.vtt

3.6 kB

4. Basic Data Wrangling/6. Change the Column Type.mp4

23 MB

4. Basic Data Wrangling/6. Change the Column Type.vtt

3.9 kB

4. Basic Data Wrangling/7. Explore Date Related Data.mp4

25 MB

4. Basic Data Wrangling/7. Explore Date Related Data.vtt

3.6 kB

4. Basic Data Wrangling/8. Simple Date Related Computations.mp4

25 MB

4. Basic Data Wrangling/8. Simple Date Related Computations.vtt

3.8 kB

5. More Data Wrangling/1. Data Grouping.mp4

98 MB

5. More Data Wrangling/1. Data Grouping.vtt

8.3 kB

5. More Data Wrangling/2. Data Subsetting and Indexing.mp4

102 MB

5. More Data Wrangling/2. Data Subsetting and Indexing.vtt

7.8 kB

5. More Data Wrangling/3. More Data Subsetting.mp4

69 MB

5. More Data Wrangling/3. More Data Subsetting.vtt

8.0 kB

5. More Data Wrangling/4. Extract Information From Strings.mp4

38 MB

5. More Data Wrangling/4. Extract Information From Strings.vtt

4.2 kB

5. More Data Wrangling/5. (Fuzzy) String Matching.mp4

19 MB

5. More Data Wrangling/5. (Fuzzy) String Matching.vtt

2.7 kB

5. More Data Wrangling/6. Ranking & Sorting.mp4

82 MB

5. More Data Wrangling/6. Ranking & Sorting.vtt

7.4 kB

5. More Data Wrangling/7. Concatenate.mp4

70 MB

5. More Data Wrangling/7. Concatenate.vtt

7.9 kB

5. More Data Wrangling/8. Merging and Joining.mp4

97 MB

5. More Data Wrangling/8. Merging and Joining.vtt

11 kB

6. Feature Selection and Transformation/1. Correlation Analysis.mp4

56 MB

6. Feature Selection and Transformation/1. Correlation Analysis.vtt

8.6 kB

6. Feature Selection and Transformation/2. Using Correlation to Decide Which Features to Retain.mp4

34 MB

6. Feature Selection and Transformation/2. Using Correlation to Decide Which Features to Retain.vtt

5.0 kB

6. Feature Selection and Transformation/3. Univariate Feature Selection.mp4

39 MB

6. Feature Selection and Transformation/3. Univariate Feature Selection.vtt

4.6 kB

6. Feature Selection and Transformation/4. Recursive Feature Elimination (RFE).mp4

36 MB

6. Feature Selection and Transformation/4. Recursive Feature Elimination (RFE).vtt

4.1 kB

6. Feature Selection and Transformation/5. Theory Behind PCA.mp4

24 MB

6. Feature Selection and Transformation/5. Theory Behind PCA.vtt

2.9 kB

6. Feature Selection and Transformation/6. Implement PCA.mp4

27 MB

6. Feature Selection and Transformation/6. Implement PCA.vtt

4.1 kB

6. Feature Selection and Transformation/7. Data Standardisation.mp4

32 MB

6. Feature Selection and Transformation/7. Data Standardisation.vtt

4.1 kB

6. Feature Selection and Transformation/8. Create a New Feature.mp4

40 MB

6. Feature Selection and Transformation/8. Create a New Feature.vtt

5.8 kB

7. Theory Behind Data Visualisation/1. What is Data Visualisation.mp4

68 MB

7. Theory Behind Data Visualisation/1. What is Data Visualisation.vtt

9.9 kB

7. Theory Behind Data Visualisation/2. Some Theoretical Principles Behind Data Visualisation.mp4

66 MB

7. Theory Behind Data Visualisation/2. Some Theoretical Principles Behind Data Visualisation.vtt

7.1 kB

8. Most Common Data Visualizations/1. Histograms-Visualize the Distribution of Continuous Numerical Variables.mp4

99 MB

8. Most Common Data Visualizations/1. Histograms-Visualize the Distribution of Continuous Numerical Variables.vtt

12 kB

8. Most Common Data Visualizations/2. Boxplots-Visualize the Distribution of Continuous Numerical Variables.mp4

40 MB

8. Most Common Data Visualizations/2. Boxplots-Visualize the Distribution of Continuous Numerical Variables.vtt

5.5 kB

8. Most Common Data Visualizations/3. Scatter plot-Relationship Between Two Numerical Variables.mp4

107 MB

8. Most Common Data Visualizations/3. Scatter plot-Relationship Between Two Numerical Variables.vtt

12 kB

8. Most Common Data Visualizations/4. Barplot.mp4

171 MB

8. Most Common Data Visualizations/4. Barplot.vtt

22 kB

8. Most Common Data Visualizations/5. Pie Chart.mp4

38 MB

8. Most Common Data Visualizations/5. Pie Chart.vtt

5.8 kB

8. Most Common Data Visualizations/6. Line Charts.mp4

117 MB

8. Most Common Data Visualizations/6. Line Charts.vtt

12 kB

8. Most Common Data Visualizations/7. More Line Charts.mp4

19 MB

8. Most Common Data Visualizations/7. More Line Charts.vtt

2.3 kB

8. Most Common Data Visualizations/8. Some More Plot Types.mp4

76 MB

8. Most Common Data Visualizations/8. Some More Plot Types.vtt

11 kB

8. Most Common Data Visualizations/9. And Some More.mp4

78 MB

8. Most Common Data Visualizations/9. And Some More.vtt

8.3 kB

9. Miscallaneous Information/1. Using Colabs as an Online Jupyter Notebook.mp4

55 MB

9. Miscallaneous Information/1. Using Colabs as an Online Jupyter Notebook.vtt

6.5 kB