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[FreeCourseSite.com] Udemy - Complete Python Data Science, Deep Learning, R Programming
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文件列表
27. Data Transformation in R/3. Filtering Rows with Filter Function in R programming.mp4
177.9 MB
18. Projects Python projects, Data science projects, machine learning/2. Project - 2.mp4
177.5 MB
11. Geoplotlib/3.1 world_cities_pop.csv
164.3 MB
12. Data Science Hands-On Projects/6. Answer for Housing and Property Sales Project.mp4
162.6 MB
12. Data Science Hands-On Projects/8. Answers for English Premier League Project.mp4
161.0 MB
13. Machine Learning/15. Choosing the right algorithm and model in deep learning.mp4
156.1 MB
27. Data Transformation in R/6. Grouped Summaries with Summarize Function in R.mp4
155.8 MB
12. Data Science Hands-On Projects/4. Bike Sharing Project Answers.mp4
154.4 MB
25. Data Frames/3. Manipulating Values in DF.mp4
152.3 MB
20. Data Management in R/3. Graphs and Charts in Python data science.mp4
146.6 MB
26. Factors in R/2. Manipulating Categorical Data with Forcats in R.mp4
139.2 MB
27. Data Transformation in R/4. Arranging Rows with Arrange Function in R.mp4
135.6 MB
9. Matplotlib/8. Basic Plots in Matplotlib I.mp4
109.5 MB
8. Data Frame with Pandas/9. Combining Data Frames in Pandas.mp4
108.6 MB
18. Projects Python projects, Data science projects, machine learning/1. Project - 1.mp4
106.5 MB
10. Seaborn/5. Basic Plots in Seaborn.mp4
97.3 MB
12. Data Science Hands-On Projects/2. Titanic Project Answers in python projects.mp4
93.3 MB
13. Machine Learning/12. Unsupervised Machine Learning Methods.mp4
92.2 MB
17. Transfer Learning/1. What is Transfer Learning.mp4
89.5 MB
8. Data Frame with Pandas/10. Combining Data Frames Part – II.mp4
88.3 MB
13. Machine Learning/16. Training and testing the model.mp4
88.1 MB
25. Data Frames/5. Tibbles in R.mp4
87.8 MB
18. Projects Python projects, Data science projects, machine learning/3. Project - 3.mp4
86.4 MB
8. Data Frame with Pandas/1. Data Frame Attributes and Methods.mp4
83.6 MB
14. Artificial Neural Network/3. Creating a Simple ANN in Artificial intelligence.mp4
83.4 MB
8. Data Frame with Pandas/6. Missing Data and Data Munging in Pandas.mp4
83.2 MB
11. Geoplotlib/3. Example - 2.mp4
80.0 MB
27. Data Transformation in R/1. Introduction to Data Transformation.mp4
79.9 MB
7. Pandas Using Pandas for Data Manipulation/2. Series and Features.mp4
77.9 MB
6. Using Numpy for Data Manipulation/5. Numpy Exercises.mp4
77.8 MB
15. Convolutional Neural Network (CNN)/1. What is CNN.mp4
75.9 MB
18. Projects Python projects, Data science projects, machine learning/4. Project - 4.mp4
75.8 MB
25. Data Frames/1. Introduction to Data Frames.mp4
74.4 MB
8. Data Frame with Pandas/11. Work with Dataset Files in Pandas.mp4
74.2 MB
13. Machine Learning/11. Supervised Machine Learning Methods - 4.mp4
73.7 MB
8. Data Frame with Pandas/8. How We Deal with Missing Data.mp4
72.6 MB
23. Arrays in R/2. Subsections of an Array in r programming.mp4
71.8 MB
3. Fundamentals of Python/5. Lists, Tuples, Dictionaries and Sets in Python.mp4
69.6 MB
9. Matplotlib/4. Figure, Subplot and Axes in Matplotlib.mp4
68.8 MB
27. Data Transformation in R/5. Adding New Variables with Mutate Function in R.mp4
66.2 MB
14. Artificial Neural Network/8. What is TensorFlow.mp4
65.7 MB
14. Artificial Neural Network/4. Tensor Operations in Artificial intelligence.mp4
65.1 MB
27. Data Transformation in R/2. Select Columns with Select Function in R programming.mp4
63.5 MB
24. Matrices in R programming/3. Calculating With Matrices in Python Data science.mp4
62.0 MB
9. Matplotlib/5. Figure Customization in Matplotlib.mp4
61.9 MB
4. Object Oriented Programming/5. Overriding and Overloading in OOP.mp4
61.7 MB
8. Data Frame with Pandas/2. Data Frame Attributes and Methods Part – II.mp4
59.7 MB
10. Seaborn/7. Regression Plots and Squarify in Seaborn.mp4
59.2 MB
13. Machine Learning/10. Supervised Machine Learning Methods - 3.mp4
58.8 MB
13. Machine Learning/9. Supervised Machine Learning Methods - 2.mp4
58.1 MB
20. Data Management in R/2. Data Manipulation in R.mp4
57.6 MB
2. Setting Up Python for Mac and Windows Python Data Science/2. Installing Anaconda for Mac, Python Data Science.mp4
55.6 MB
8. Data Frame with Pandas/5. Groupby Operations in Pandas.mp4
55.2 MB
9. Matplotlib/9. Basic Plots in Matplotlib II.mp4
54.0 MB
10. Seaborn/3. Example in Seaborn.mp4
53.8 MB
16. Recurrent Neural Network and LTSM/1. Understanding RNN and LSTM Networks.mp4
53.3 MB
8. Data Frame with Pandas/4. Multi Index in Pandas.mp4
53.3 MB
24. Matrices in R programming/1. Matrices in R programming.mp4
52.4 MB
3. Fundamentals of Python/4. Loops in Python.mp4
51.5 MB
24. Matrices in R programming/2. Naming Matrix Row and Columns in R programming.mp4
50.4 MB
8. Data Frame with Pandas/3. Data Frame Attributes and Methods Part – III.mp4
50.4 MB
6. Using Numpy for Data Manipulation/2. Array and Features in Numpy Python.mp4
50.2 MB
11. Geoplotlib/4. Example - 3.mp4
50.1 MB
3. Fundamentals of Python/10. Exercise Solution in Python.mp4
50.0 MB
21. Examining and Managing Data Structures in R/7. Subsetting Vectors in R.mp4
48.4 MB
13. Machine Learning/7. Machine Learning Methods.mp4
47.8 MB
10. Seaborn/4. Color Palettes in Seaborn.mp4
47.7 MB
22. Lists in R/1. Lists in R.mp4
45.4 MB
14. Artificial Neural Network/7. Optimizers in Artificial intelligence.mp4
44.4 MB
14. Artificial Neural Network/2. Anatomy of Neural Network in Artificial intelligence.mp4
44.3 MB
21. Examining and Managing Data Structures in R/1. Vector Basics in R.mp4
44.0 MB
25. Data Frames/4. Adding and Removing Variables in R Programming.mp4
43.5 MB
3. Fundamentals of Python/1. Data Types in Python.mp4
43.1 MB
10. Seaborn/6. Multi-Plots in Seaborn.mp4
42.9 MB
13. Machine Learning/3. Turing Machine and Turing Test.mp4
42.9 MB
8. Data Frame with Pandas/7. Missing Data and Data Munging Part II.mp4
42.8 MB
3. Fundamentals of Python/6. Data Type Operators and Methods in Python.mp4
42.4 MB
6. Using Numpy for Data Manipulation/4. Indexing and Slicing in Numpy Python.mp4
42.3 MB
2. Setting Up Python for Mac and Windows Python Data Science/1. Installing Anaconda for Windows.mp4
42.1 MB
10. Seaborn/2. Controlling Figure Aesthetics in Seaborn.mp4
41.1 MB
20. Data Management in R/1. Getting Data into R.mp4
38.6 MB
11. Geoplotlib/2. Example - 1.mp4
38.1 MB
13. Machine Learning/5. Learning representations from data.mp4
36.6 MB
3. Fundamentals of Python/3. Conditionals in Python.mp4
36.3 MB
26. Factors in R/1. Introduction to Factors in R.mp4
36.3 MB
21. Examining and Managing Data Structures in R/5. Vector Recycling and Iterations in R.mp4
36.2 MB
21. Examining and Managing Data Structures in R/6. Naming Vectors in R.mp4
35.9 MB
4. Object Oriented Programming/2. Constructor in Object Oriented Programming.mp4
35.5 MB
4. Object Oriented Programming/4. Inheritance in Object Oriented Programming.mp4
34.2 MB
11. Geoplotlib/1. What is Geoplotlib.mp4
33.8 MB
21. Examining and Managing Data Structures in R/3. Converting Data Types of Atomic Vectors in R.mp4
33.7 MB
13. Machine Learning/6. Workflow of Machine Learning.mp4
33.2 MB
13. Machine Learning/8. Supervised Machine Learning Methods - 1.mp4
32.4 MB
14. Artificial Neural Network/5. Tensor Operations 2.mp4
31.2 MB
3. Fundamentals of Python/2. Operators in Python.mp4
31.1 MB
23. Arrays in R/1. Arrays in r programming.mp4
29.4 MB
25. Data Frames/2. Naming Variables and Observations in DF.mp4
28.9 MB
6. Using Numpy for Data Manipulation/1. What is Numpy.mp4
28.0 MB
9. Matplotlib/3. Pyplot – Pylab - Matplotlib.mp4
27.9 MB
9. Matplotlib/2. Using Matplotlib.mp4
27.8 MB
3. Fundamentals of Python/8. Functions in Python.mp4
27.3 MB
13. Machine Learning/14. Data pre-processing in Deep learning.mp4
27.2 MB
9. Matplotlib/6. Plot Customization in matplotlib.mp4
27.0 MB
2. Setting Up Python for Mac and Windows Python Data Science/3. Let's Meet Jupyter Notebook for Windows.mp4
26.6 MB
19. Environment Installation for R/1. Downloading and Installing R & R Studio.mp4
26.3 MB
13. Machine Learning/17. Evaluation in deep learning.mp4
25.6 MB
21. Examining and Managing Data Structures in R/2. Atomic Vector Types in R.mp4
25.2 MB
13. Machine Learning/2. History of Machine Learning.mp4
25.0 MB
4. Object Oriented Programming/3. Methods in Object Oriented Programming.mp4
24.8 MB
14. Artificial Neural Network/6. Keras API in Artificial intelligence.mp4
24.4 MB
14. Artificial Neural Network/1. What is Artificial Neural Network (ANN).mp4
24.1 MB
9. Matplotlib/7. Grid, Spines, Ticks in python.mp4
23.5 MB
19. Environment Installation for R/2. R Console Versus R Studio.mp4
23.0 MB
3. Fundamentals of Python/7. Modules in Python.mp4
22.1 MB
13. Machine Learning/4. What is Deep Learning.mp4
21.5 MB
5. Python For Data Science Data Science/1. What Is Data Science.mp4
21.2 MB
7. Pandas Using Pandas for Data Manipulation/1. What is Pandas.mp4
21.1 MB
9. Matplotlib/1. What is Matplotlib.mp4
18.7 MB
13. Machine Learning/13. Gathering data in Deep learning.mp4
18.5 MB
6. Using Numpy for Data Manipulation/3. Array Operators in Numpy.mp4
18.4 MB
4. Object Oriented Programming/1. Logic of Object Oriented Programming.mp4
17.2 MB
13. Machine Learning/1. AI, Machine Learning and Deep Learning.mp4
17.0 MB
2. Setting Up Python for Mac and Windows Python Data Science/4. Basics of Jupyter Notebook for Mac.mp4
15.5 MB
1. Introduction to Complete Data Science, Deep Learning, R Data Science 2021/1. Be Smart and Use Data But How Answer is Data Science with Python.mp4
14.4 MB
12. Data Science Hands-On Projects/3. Project II Bike Sharing.mp4
14.4 MB
12. Data Science Hands-On Projects/7. Project IV English Premier League.mp4
14.1 MB
21. Examining and Managing Data Structures in R/4. Test Functions in R.mp4
13.6 MB
10. Seaborn/1. What is Seaborn.mp4
13.5 MB
12. Data Science Hands-On Projects/5. Project III Housing and Property Sales.mp4
10.8 MB
12. Data Science Hands-On Projects/1. Analyse Data With Different Data Sets Titanic Project.mp4
10.5 MB
5. Python For Data Science Data Science/2. Data Literacy.mp4
10.2 MB
3. Fundamentals of Python/9. Exercise Analyse in Python.mp4
6.0 MB
10. Seaborn/5.3 salary.csv
3.4 MB
12. Data Science Hands-On Projects/5.1 House Sales.csv
1.2 MB
10. Seaborn/7.1 age_data.csv
677.3 kB
9. Matplotlib/8.1 age_data.csv
677.3 kB
12. Data Science Hands-On Projects/3.1 Bike_Share_London.csv
377.3 kB
9. Matplotlib/9.1 winequality.csv
84.2 kB
12. Data Science Hands-On Projects/1.2 Titanic.csv
58.7 kB
12. Data Science Hands-On Projects/7.1 2006-2018 EPL stats.csv
55.2 kB
9. Matplotlib/8. Basic Plots in Matplotlib I.srt
31.0 kB
12. Data Science Hands-On Projects/4. Bike Sharing Project Answers.srt
30.7 kB
12. Data Science Hands-On Projects/6. Answer for Housing and Property Sales Project.srt
29.1 kB
12. Data Science Hands-On Projects/8. Answers for English Premier League Project.srt
28.8 kB
13. Machine Learning/12. Unsupervised Machine Learning Methods.srt
27.2 kB
11. Geoplotlib/2.1 poaching_points_cleaned.csv
24.8 kB
10. Seaborn/5. Basic Plots in Seaborn.srt
22.8 kB
8. Data Frame with Pandas/6. Missing Data and Data Munging in Pandas.srt
22.4 kB
12. Data Science Hands-On Projects/2. Titanic Project Answers in python projects.srt
21.9 kB
18. Projects Python projects, Data science projects, machine learning/2. Project - 2.srt
21.3 kB
14. Artificial Neural Network/8. What is TensorFlow.srt
20.5 kB
18. Projects Python projects, Data science projects, machine learning/1. Project - 1.srt
20.5 kB
1. Introduction to Complete Data Science, Deep Learning, R Data Science 2021/3. FAQ about Complete data science with R, deep learning, machine learning.html
20.5 kB
20. Data Management in R/3. Graphs and Charts in Python data science.srt
19.6 kB
13. Machine Learning/11. Supervised Machine Learning Methods - 4.srt
19.2 kB
7. Pandas Using Pandas for Data Manipulation/2. Series and Features.srt
19.2 kB
17. Transfer Learning/1. What is Transfer Learning.srt
19.2 kB
11. Geoplotlib/3. Example - 2.srt
19.0 kB
27. Data Transformation in R/6. Grouped Summaries with Summarize Function in R.srt
18.0 kB
3. Fundamentals of Python/5. Lists, Tuples, Dictionaries and Sets in Python.srt
17.9 kB
9. Matplotlib/4. Figure, Subplot and Axes in Matplotlib.srt
17.7 kB
15. Convolutional Neural Network (CNN)/1. What is CNN.srt
17.6 kB
8. Data Frame with Pandas/10. Combining Data Frames Part – II.srt
17.6 kB
8. Data Frame with Pandas/9. Combining Data Frames in Pandas.srt
17.5 kB
13. Machine Learning/7. Machine Learning Methods.srt
16.4 kB
13. Machine Learning/10. Supervised Machine Learning Methods - 3.srt
16.2 kB
9. Matplotlib/9. Basic Plots in Matplotlib II.srt
16.0 kB
10. Seaborn/7. Regression Plots and Squarify in Seaborn.srt
15.9 kB
8. Data Frame with Pandas/8. How We Deal with Missing Data.srt
15.8 kB
8. Data Frame with Pandas/1. Data Frame Attributes and Methods.srt
15.8 kB
13. Machine Learning/9. Supervised Machine Learning Methods - 2.srt
15.6 kB
27. Data Transformation in R/3. Filtering Rows with Filter Function in R programming.srt
15.5 kB
18. Projects Python projects, Data science projects, machine learning/3. Project - 3.srt
15.3 kB
6. Using Numpy for Data Manipulation/5. Numpy Exercises.srt
15.0 kB
16. Recurrent Neural Network and LTSM/1. Understanding RNN and LSTM Networks.srt
14.9 kB
18. Projects Python projects, Data science projects, machine learning/4. Project - 4.srt
14.9 kB
10. Seaborn/4. Color Palettes in Seaborn.srt
14.9 kB
14. Artificial Neural Network/3. Creating a Simple ANN in Artificial intelligence.srt
14.8 kB
9. Matplotlib/5. Figure Customization in Matplotlib.srt
14.2 kB
25. Data Frames/3. Manipulating Values in DF.srt
14.2 kB
3. Fundamentals of Python/1. Data Types in Python.srt
13.8 kB
13. Machine Learning/5. Learning representations from data.srt
13.7 kB
13. Machine Learning/3. Turing Machine and Turing Test.srt
13.6 kB
8. Data Frame with Pandas/5. Groupby Operations in Pandas.srt
12.5 kB
27. Data Transformation in R/4. Arranging Rows with Arrange Function in R.srt
12.4 kB
14. Artificial Neural Network/7. Optimizers in Artificial intelligence.srt
12.2 kB
26. Factors in R/2. Manipulating Categorical Data with Forcats in R.srt
12.2 kB
3. Fundamentals of Python/4. Loops in Python.srt
12.2 kB
8. Data Frame with Pandas/4. Multi Index in Pandas.srt
12.1 kB
8. Data Frame with Pandas/11. Work with Dataset Files in Pandas.srt
11.8 kB
6. Using Numpy for Data Manipulation/2. Array and Features in Numpy Python.srt
11.7 kB
11. Geoplotlib/4. Example - 3.srt
11.6 kB
9. Matplotlib/8.2 scatter_ex.xlsx
11.6 kB
8. Data Frame with Pandas/2. Data Frame Attributes and Methods Part – II.srt
11.5 kB
14. Artificial Neural Network/4. Tensor Operations in Artificial intelligence.srt
11.2 kB
10. Seaborn/2. Controlling Figure Aesthetics in Seaborn.srt
11.1 kB
13. Machine Learning/6. Workflow of Machine Learning.srt
11.0 kB
8. Data Frame with Pandas/7. Missing Data and Data Munging Part II.srt
11.0 kB
10. Seaborn/6. Multi-Plots in Seaborn.srt
10.9 kB
3. Fundamentals of Python/2. Operators in Python.srt
10.9 kB
13. Machine Learning/8. Supervised Machine Learning Methods - 1.srt
10.6 kB
14. Artificial Neural Network/2. Anatomy of Neural Network in Artificial intelligence.srt
10.6 kB
11. Geoplotlib/1. What is Geoplotlib.srt
10.4 kB
3. Fundamentals of Python/3. Conditionals in Python.srt
9.9 kB
10. Seaborn/3. Example in Seaborn.srt
9.9 kB
11. Geoplotlib/2. Example - 1.srt
9.8 kB
8. Data Frame with Pandas/3. Data Frame Attributes and Methods Part – III.srt
9.5 kB
4. Object Oriented Programming/5. Overriding and Overloading in OOP.srt
9.5 kB
20. Data Management in R/2. Data Manipulation in R.srt
9.3 kB
3. Fundamentals of Python/6. Data Type Operators and Methods in Python.srt
9.1 kB
13. Machine Learning/15. Choosing the right algorithm and model in deep learning.srt
9.1 kB
3. Fundamentals of Python/8. Functions in Python.srt
9.1 kB
25. Data Frames/5. Tibbles in R.srt
8.8 kB
6. Using Numpy for Data Manipulation/4. Indexing and Slicing in Numpy Python.srt
8.8 kB
27. Data Transformation in R/1. Introduction to Data Transformation.srt
8.7 kB
23. Arrays in R/2. Subsections of an Array in r programming.srt
8.5 kB
9. Matplotlib/7. Grid, Spines, Ticks in python.srt
8.3 kB
14. Artificial Neural Network/1. What is Artificial Neural Network (ANN).srt
8.3 kB
14. Artificial Neural Network/6. Keras API in Artificial intelligence.srt
8.2 kB
14. Artificial Neural Network/5. Tensor Operations 2.srt
8.1 kB
13. Machine Learning/2. History of Machine Learning.srt
7.9 kB
9. Matplotlib/2. Using Matplotlib.srt
7.6 kB
13. Machine Learning/17. Evaluation in deep learning.srt
7.6 kB
6. Using Numpy for Data Manipulation/1. What is Numpy.srt
7.5 kB
9. Matplotlib/3. Pyplot – Pylab - Matplotlib.srt
7.4 kB
20. Data Management in R/1. Getting Data into R.srt
7.3 kB
13. Machine Learning/4. What is Deep Learning.srt
7.3 kB
27. Data Transformation in R/2. Select Columns with Select Function in R programming.srt
7.1 kB
4. Object Oriented Programming/2. Constructor in Object Oriented Programming.srt
7.0 kB
27. Data Transformation in R/5. Adding New Variables with Mutate Function in R.srt
7.0 kB
25. Data Frames/1. Introduction to Data Frames.srt
6.9 kB
4. Object Oriented Programming/4. Inheritance in Object Oriented Programming.srt
6.8 kB
24. Matrices in R programming/1. Matrices in R programming.srt
6.7 kB
9. Matplotlib/6. Plot Customization in matplotlib.srt
6.7 kB
5. Python For Data Science Data Science/1. What Is Data Science.srt
6.7 kB
7. Pandas Using Pandas for Data Manipulation/1. What is Pandas.srt
6.5 kB
3. Fundamentals of Python/10. Exercise Solution in Python.srt
6.5 kB
13. Machine Learning/14. Data pre-processing in Deep learning.srt
6.4 kB
13. Machine Learning/16. Training and testing the model.srt
6.4 kB
2. Setting Up Python for Mac and Windows Python Data Science/2. Installing Anaconda for Mac, Python Data Science.srt
6.4 kB
24. Matrices in R programming/3. Calculating With Matrices in Python Data science.srt
6.2 kB
2. Setting Up Python for Mac and Windows Python Data Science/1. Installing Anaconda for Windows.srt
6.1 kB
22. Lists in R/1. Lists in R.srt
5.9 kB
2. Setting Up Python for Mac and Windows Python Data Science/3. Let's Meet Jupyter Notebook for Windows.srt
5.8 kB
13. Machine Learning/13. Gathering data in Deep learning.srt
5.8 kB
21. Examining and Managing Data Structures in R/7. Subsetting Vectors in R.srt
5.7 kB
1. Introduction to Complete Data Science, Deep Learning, R Data Science 2021/1. Be Smart and Use Data But How Answer is Data Science with Python.srt
5.6 kB
13. Machine Learning/1. AI, Machine Learning and Deep Learning.srt
5.6 kB
21. Examining and Managing Data Structures in R/1. Vector Basics in R.srt
5.6 kB
3. Fundamentals of Python/7. Modules in Python.srt
5.4 kB
24. Matrices in R programming/2. Naming Matrix Row and Columns in R programming.srt
5.3 kB
19. Environment Installation for R/2. R Console Versus R Studio.srt
5.3 kB
4. Object Oriented Programming/1. Logic of Object Oriented Programming.srt
5.2 kB
10. Seaborn/1. What is Seaborn.srt
5.1 kB
12. Data Science Hands-On Projects/3. Project II Bike Sharing.srt
5.1 kB
12. Data Science Hands-On Projects/7. Project IV English Premier League.srt
5.0 kB
26. Factors in R/1. Introduction to Factors in R.srt
4.7 kB
21. Examining and Managing Data Structures in R/5. Vector Recycling and Iterations in R.srt
4.7 kB
23. Arrays in R/1. Arrays in r programming.srt
4.6 kB
19. Environment Installation for R/1. Downloading and Installing R & R Studio.srt
4.5 kB
12. Data Science Hands-On Projects/1. Analyse Data With Different Data Sets Titanic Project.srt
4.4 kB
21. Examining and Managing Data Structures in R/6. Naming Vectors in R.srt
4.4 kB
6. Using Numpy for Data Manipulation/3. Array Operators in Numpy.srt
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