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Udemy Complete Data Science Machine Learning A Z with Python

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Tutorials

Language:

English

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Files:

[CourseClub.Me].url 122 bytes
[FreeCourseSite.com].url 127 bytes
[GigaCourse.Com].url 49 bytes
1. Installing Anaconda Distribution for Windows.mp4 118.3 MB
2. Notebook Project Files Link regarding NumPy Python Programming Language Library.html 155 bytes
3. Installing Anaconda Distribution for MacOs.mp4 46.3 MB
4. 6 Article Advice And Links about Numpy, Numpy Pyhon.html 4.2 KB
5. Installing Anaconda Distribution for Linux.mp4 114.8 MB
1. Element Selection Operations in Pandas DataFrames Lesson 1.mp4 29.9 MB
2. Element Selection Operations in Pandas DataFrames Lesson 2.mp4 31.8 MB
3. Top Level Element Selection in Pandas DataFramesLesson 1.mp4 38.3 MB
4. Top Level Element Selection in Pandas DataFramesLesson 2.mp4 31.4 MB
5. Top Level Element Selection in Pandas DataFramesLesson 3.mp4 22.1 MB
6. Element Selection with Conditional Operations in.mp4 46.4 MB
7. Quiz.html 205 bytes
[CourseClub.Me].url 122 bytes
[FreeCourseSite.com].url 127 bytes
[GigaCourse.Com].url 49 bytes
1. Adding Columns to Pandas Data Frames.mp4 33.6 MB
2. Removing Rows and Columns from Pandas Data frames.mp4 15.6 MB
3. Null Values in Pandas Dataframes.mp4 67.0 MB
4. Dropping Null Values Dropna() Function.mp4 34.5 MB
5. Filling Null Values Fillna() Function.mp4 51.6 MB
6. Setting Index in Pandas DataFrames.mp4 39.7 MB
7. Quiz.html 205 bytes
1. Multi-Index and Index Hierarchy in Pandas DataFrames.mp4 42.7 MB
2. Element Selection in Multi-Indexed DataFrames.mp4 24.6 MB
3. Selecting Elements Using the xs() Function in Multi-Indexed DataFrames.mp4 31.3 MB
4. Quiz.html 205 bytes
1. Concatenating Pandas Dataframes Concat Function.mp4 63.8 MB
2. Merge Pandas Dataframes Merge() Function Lesson 1.mp4 57.3 MB
3. Merge Pandas Dataframes Merge() Function Lesson 2.mp4 30.5 MB
4. Merge Pandas Dataframes Merge() Function Lesson 3.mp4 60.2 MB
5. Merge Pandas Dataframes Merge() Function Lesson 4.mp4 40.7 MB
6. Joining Pandas Dataframes Join() Function.mp4 56.1 MB
7. Quiz.html 205 bytes
1. Loading a Dataset from the Seaborn Library.mp4 37.7 MB
10. Quiz.html 205 bytes
2. Examining the Data Set 1.mp4 42.9 MB
3. Aggregation Functions in Pandas DataFrames.mp4 90.7 MB
4. Examining the Data Set 2.mp4 46.6 MB
5. Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4 88.1 MB
6. Advanced Aggregation Functions Aggregate() Function.mp4 29.2 MB
7. Advanced Aggregation Functions Filter() Function.mp4 24.4 MB
8. Advanced Aggregation Functions Transform() Function.mp4 47.1 MB
9. Advanced Aggregation Functions Apply() Function.mp4 41.4 MB
1. Examining the Data Set 3.mp4 39.1 MB
2. Pivot Tables in Pandas Library.mp4 54.2 MB
3. Quiz.html 205 bytes
1. Accessing and Making Files Available.mp4 34.6 MB
2. Data Entry with Csv and Txt Files.mp4 64.3 MB
3. Data Entry with Excel Files.mp4 21.8 MB
4. Outputting as an CSV Extension.mp4 35.7 MB
5. Outputting as an Excel File.mp4 19.7 MB
6. Quiz.html 205 bytes
1. Data Visualisation - Matplotlib Files.html 170 bytes
2. Data Visualisation - Seaborn Files.html 170 bytes
3. Data Visualisation - Geoplotlib.html 168 bytes
1. Introduction to Data Visualization with Python.mp4 12.8 MB
2. FAQ regarding Data Visualization, Python.html 8.6 KB
1. Data Types in Python.mp4 47.1 MB
10. Exercise - Solution in Python.mp4 51.9 MB
11. Quiz.html 205 bytes
2. Operators in Python.mp4 35.7 MB
3. Conditionals in Python.mp4 41.2 MB
4. Loops in Python.mp4 58.8 MB
5. Lists, Tuples, Dictionaries and Sets in pyhton.mp4 75.3 MB
6. Data Type Operators and Methods in Python.mp4 43.9 MB
7. Modules in Python.mp4 23.9 MB
8. Functions in Python.mp4 28.9 MB
9. Exercise - Analyse in Python.mp4 8.5 MB
1. Introduction to NumPy Library.mp4 45.3 MB
2. The Power of NumPy.mp4 59.9 MB
3. Quiz.html 205 bytes
1. Logic of Object Oriented Programming.mp4 17.4 MB
2. Constructor in Object Oriented Programming (OOP).mp4 35.8 MB
3. Methods in Object Oriented Programming (OOP).mp4 25.1 MB
4. Inheritance in Object Oriented Programming (OOP).mp4 34.6 MB
5. Overriding and Overloading in Object Oriented Programming (OOP).mp4 62.7 MB
6. Quiz.html 205 bytes
1. What is Matplotlib.mp4 19.1 MB
10. Quiz.html 205 bytes
2. Using Pyplot.mp4 28.2 MB
3. Pyplot – Pylab - Matplotlib.mp4 28.4 MB
4. Figure, Subplot and Axex.mp4 69.9 MB
5. Figure Customization.mp4 63.3 MB
6. Plot Customization.mp4 27.4 MB
7. Grid, Spines, Ticks.mp4 23.9 MB
8. Basic Plots in Matplotlib I.mp4 111.2 MB
9. Basic Plots in Matplotlib II.mp4 54.8 MB
1. What is Seaborn.mp4 13.6 MB
2. Controlling Figure Aesthetics in Seaborn.mp4 41.8 MB
3. Example in Seaborn.mp4 54.9 MB
4. Color Palettes in Seaborn.mp4 48.3 MB
5. Basic Plots in Seaborn.mp4 98.8 MB
6. Multi-Plots in Seaborn.mp4 43.0 MB
7. Regression Plots and Squarify in Seaborn.mp4 60.1 MB
8. Quiz.html 205 bytes
1. What is Geoplotlib.mp4 34.2 MB
2. Example - 1.mp4 38.9 MB
3. Example - 2.mp4 81.1 MB
4. Example - 3.mp4 51.3 MB
5. Quiz.html 205 bytes
1. What is Machine Learning.mp4 27.6 MB
2. Machine Learning Terminology.mp4 14.0 MB
3. Machine Learning Project Files.html 254 bytes
4. FAQ regarding Python.html 6.2 KB
5. FAQ regarding Machine Learning.html 6.6 KB
6. Quiz.html 205 bytes
1. Classification vs Regression in Machine Learning.mp4 19.9 MB
2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 100.3 MB
3. Evaluating Performance Regression Error Metrics in Python.mp4 45.7 MB
4. Machine Learning With Python.mp4 92.2 MB
5. Quiz.html 205 bytes
[CourseClub.Me].url 122 bytes
[FreeCourseSite.com].url 127 bytes
[GigaCourse.Com].url 49 bytes
1. What is Supervised Learning in Machine Learning.mp4 31.7 MB
2. Quiz.html 205 bytes
1. Linear Regression Algorithm Theory in Machine Learning A-Z.mp4 34.1 MB
2. Linear Regression Algorithm With Python Part 1.mp4 76.2 MB
3. Linear Regression Algorithm With Python Part 2.mp4 106.9 MB
4. Linear Regression Algorithm With Python Part 3.mp4 70.3 MB
5. Linear Regression Algorithm With Python Part 4.mp4 90.0 MB
1. What is Bias Variance Trade-Off.mp4 55.0 MB
2. Quiz.html 205 bytes
1. What is Logistic Regression Algorithm in Machine Learning.mp4 27.8 MB
2. Logistic Regression Algorithm with Python Part 1.mp4 72.2 MB
3. Logistic Regression Algorithm with Python Part 2.mp4 81.5 MB
4. Logistic Regression Algorithm with Python Part 3.mp4 47.3 MB
5. Logistic Regression Algorithm with Python Part 4.mp4 47.2 MB
6. Logistic Regression Algorithm with Python Part 5.mp4 39.3 MB
7. Quiz.html 205 bytes
1. Creating NumPy Array with The Array() Function.mp4 29.5 MB
10. Quiz.html 205 bytes
2. Creating NumPy Array with Zeros() Function.mp4 24.1 MB
3. Creating NumPy Array with Ones() Function.mp4 15.9 MB
4. Creating NumPy Array with Full() Function.mp4 11.2 MB
5. Creating NumPy Array with Arange() Function.mp4 12.1 MB
6. Creating NumPy Array with Eye() Function.mp4 12.6 MB
7. Creating NumPy Array with Linspace() Function.mp4 7.3 MB
8. Creating NumPy Array with Random() Function.mp4 43.3 MB
9. Properties of NumPy Array.mp4 22.0 MB
1. K-Fold Cross-Validation Theory.mp4 17.4 MB
2. K-Fold Cross-Validation with Python.mp4 34.7 MB
1. K Nearest Neighbors Algorithm Theory.mp4 28.7 MB
2. K Nearest Neighbors Algorithm with Python Part 1.mp4 35.0 MB
3. K Nearest Neighbors Algorithm with Python Part 2.mp4 59.4 MB
4. K Nearest Neighbors Algorithm with Python Part 3.mp4 31.4 MB
5. Quiz.html 205 bytes
1. Hyperparameter Optimization Theory.mp4 33.1 MB
2. Hyperparameter Optimization with Python.mp4 47.5 MB
1. Decision Tree Algorithm Theory.mp4 35.8 MB
2. Decision Tree Algorithm with Python Part 1.mp4 31.5 MB
3. Decision Tree Algorithm with Python Part 2.mp4 48.9 MB
4. Decision Tree Algorithm with Python Part 3.mp4 14.7 MB
5. Decision Tree Algorithm with Python Part 4.mp4 42.5 MB
6. Decision Tree Algorithm with Python Part 5.mp4 32.7 MB
7. Quiz.html 205 bytes
1. Random Forest Algorithm Theory.mp4 22.9 MB
2. Random Forest Algorithm with Pyhon Part 1.mp4 38.6 MB
3. Random Forest Algorithm with Pyhon Part 2.mp4 38.7 MB
1. Support Vector Machine Algorithm Theory.mp4 21.8 MB
2. Support Vector Machine Algorithm with Python Part 1.mp4 35.6 MB
3. Support Vector Machine Algorithm with Python Part 2.mp4 41.7 MB
4. Support Vector Machine Algorithm with Python Part 3.mp4 34.8 MB
5. Support Vector Machine Algorithm with Python Part 4.mp4 37.6 MB
6. Quiz.html 205 bytes
1. Unsupervised Learning Overview.mp4 16.9 MB
1. K Means Clustering Algorithm Theory.mp4 17.1 MB
2. K Means Clustering Algorithm with Python Part 1.mp4 30.0 MB
3. K Means Clustering Algorithm with Python Part 2.mp4 29.6 MB
4. K Means Clustering Algorithm with Python Part 3.mp4 27.8 MB
5. K Means Clustering Algorithm with Python Part 4.mp4 29.0 MB
6. Quiz.html 205 bytes
1. Hierarchical Clustering Algorithm Theory.mp4 28.6 MB
2. Hierarchical Clustering Algorithm with Python Part 2.mp4 35.5 MB
3. Hierarchical Clustering Algorithm with Python Part 2.mp4 28.9 MB
1. Principal Component Analysis (PCA) Theory.mp4 38.0 MB
2. Principal Component Analysis (PCA) with Python Part 1.mp4 26.0 MB
3. Principal Component Analysis (PCA) with Python Part 2.mp4 8.4 MB
4. Principal Component Analysis (PCA) with Python Part 3.mp4 37.2 MB
1. Reshaping a NumPy Array Reshape() Function.mp4 26.2 MB
2. Identifying the Largest Element of a Numpy Array.mp4 15.1 MB
3. Detecting Least Element of Numpy Array Min(), Ar.mp4 10.2 MB
4. Concatenating Numpy Arrays Concatenate() Functio.mp4 38.4 MB
5. Splitting One-Dimensional Numpy Arrays The Split.mp4 20.9 MB
6. Splitting Two-Dimensional Numpy Arrays Split(),.mp4 35.7 MB
7. Sorting Numpy Arrays Sort() Function.mp4 17.0 MB
8. Quiz.html 205 bytes
1. What is the Recommender System Part 1.mp4 23.0 MB
2. What is the Recommender System Part 2.mp4 18.0 MB
1. What is Kaggle.mp4 129.7 MB
2. FAQ about Kaggle.html 10.9 KB
3. Registering on Kaggle and Member Login Procedures.mp4 43.5 MB
4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html 97 bytes
5. Getting to Know the Kaggle Homepage.mp4 122.9 MB
6. quiz.html 205 bytes
1. Competitions on Kaggle Lesson 1.mp4 188.2 MB
2. Competitions on Kaggle Lesson 2.mp4 191.7 MB
1. Datasets on Kaggle.mp4 133.2 MB
2. Quiz.html 205 bytes
1. Examining the Code Section in Kaggle Lesson 1.mp4 79.5 MB
2. Examining the Code Section in Kaggle Lesson 2.mp4 105.8 MB
3. Examining the Code Section in Kaggle Lesson 3.mp4 159.9 MB
4. Quiz.html 205 bytes
1. What is Discussion on Kaggle.mp4 40.6 MB
2. Quiz.html 205 bytes
1. Courses in Kaggle.mp4 52.1 MB
2. Ranking Among Users on Kaggle.mp4 107.0 MB
3. Blog and Documentation Sections.mp4 40.9 MB
4. Quiz.html 205 bytes
1. User Page Review on Kaggle.mp4 81.5 MB
2. Treasure in The Kaggle.mp4 74.6 MB
3. Publishing Notebooks on Kaggle.mp4 38.2 MB
4. What Should Be Done to Achieve Success in Kaggle.mp4 58.5 MB
5. Quiz.html 205 bytes
1. First Step to the Hearth Attack Prediction Project.mp4 117.1 MB
2. FAQ about Machine Learning, Data Science.html 15.3 KB
3. Notebook Design to be Used in the Project.mp4 104.9 MB
4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html 108 bytes
5. Examining the Project Topic.mp4 76.5 MB
6. Recognizing Variables In Dataset.mp4 126.9 MB
7. Quiz.html 205 bytes
1. Required Python Libraries.mp4 63.6 MB
2. Loading the Statistics Dataset in Data Science.mp4 10.0 MB
3. Initial analysis on the dataset.mp4 64.0 MB
4. Quiz.html 205 bytes
1. Indexing Numpy Arrays,.mp4 26.6 MB
2. Slicing One-Dimensional Numpy Arrays.mp4 22.3 MB
3. Slicing Two-Dimensional Numpy Arrays.mp4 34.3 MB
4. Assigning Value to One-Dimensional Arrays.mp4 18.2 MB
5. Assigning Value to Two-Dimensional Array.mp4 35.4 MB
6. Fancy Indexing of One-Dimensional Arrrays.mp4 20.5 MB
7. Fancy Indexing of Two-Dimensional Arrrays.mp4 45.7 MB
8. Combining Fancy Index with Normal Indexing.mp4 12.7 MB
9. Combining Fancy Index with Normal Slicing.mp4 16.5 MB
1. Examining Missing Values.mp4 45.8 MB
2. Examining Unique Values.mp4 44.5 MB
3. Separating variables (Numeric or Categorical).mp4 15.8 MB
4. Examining Statistics of Variables.mp4 91.4 MB
5. Quiz.html 205 bytes
1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 80.4 MB
2. Numeric Variables (Analysis with Distplot) Lesson 2.mp4 19.7 MB
3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 74.7 MB
4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 84.1 MB
5. Examining the Missing Data According to the Analysis Result.mp4 53.8 MB
6. Quiz.html 205 bytes
1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 49.4 MB
10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 68.1 MB
11. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 38.1 MB
12. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 35.5 MB
13. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 36.4 MB
14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 90.7 MB
15. Quiz.html 205 bytes
2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 35.6 MB
3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 24.1 MB
4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 56.3 MB
5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 28.3 MB
6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 47.1 MB
7. Feature Scaling with the Robust Scaler Method.mp4 35.2 MB
8. Creating a New DataFrame with the Melt() Function.mp4 52.9 MB
9. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 41.7 MB
1. Dropping Columns with Low Correlation.mp4 26.8 MB
10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 11.4 MB
11. Separating Data into Test and Training Set.mp4 29.8 MB
12. Quiz.html 205 bytes
2. Visualizing Outliers.mp4 34.9 MB
3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4 42.8 MB
4. Dealing with Outliers – Trtbps Variable Lesson 2.mp4 43.9 MB
5. Dealing with Outliers – Thalach Variable.mp4 36.2 MB
6. Dealing with Outliers – Oldpeak Variable.mp4 36.1 MB
7. Determining Distributions of Numeric Variables.mp4 25.2 MB
8. Transformation Operations on Unsymmetrical Data.mp4 24.0 MB
9. Applying One Hot Encoding Method to Categorical Variables.mp4 24.1 MB
1. Logistic Regression.mp4 29.3 MB
2. Cross Validation.mp4 30.2 MB
3. Roc Curve and Area Under Curve (AUC).mp4 41.7 MB
4. Hyperparameter Optimization (with GridSearchCV).mp4 58.8 MB
5. Decision Tree Algorithm.mp4 25.7 MB
6. Support Vector Machine Algorithm.mp4 24.5 MB
7. Random Forest Algorithm.mp4 29.8 MB
8. Hyperparameter Optimization (with GridSearchCV).mp4 52.7 MB
9. Quiz.html 205 bytes
1. Project Conclusion and Sharing.mp4 28.7 MB
2. Quiz.html 205 bytes
1. Complete Data Science & Machine Learning A-Z with Python.html 266 bytes
1. Operations with Comparison Operators.mp4 21.1 MB
2. Arithmetic Operations in Numpy.mp4 71.8 MB
3. Statistical Operations in Numpy.mp4 32.0 MB
4. Solving Second-Degree Equations with NumPy.mp4 24.2 MB
1. Introduction to Pandas Library.mp4 33.9 MB
2. Pandas Project Files Link.html 180 bytes
3. Quiz.html 205 bytes
1. Creating a Pandas Series with a List.mp4 39.2 MB
2. Creating a Pandas Series with a Dictionary.mp4 18.3 MB
3. Creating Pandas Series with NumPy Array.mp4 12.0 MB
4. Object Types in Series.mp4 19.6 MB
5. Examining the Primary Features of the Pandas Seri.mp4 18.9 MB
6. Most Applied Methods on Pandas Series.mp4 48.2 MB
7. Indexing and Slicing Pandas Series.mp4 29.9 MB
8. Quiz.html 205 bytes
1. Creating Pandas DataFrame with List.mp4 22.6 MB
2. Creating Pandas DataFrame with NumPy Array.mp4 12.1 MB
3. Creating Pandas DataFrame with Dictionary.mp4 15.8 MB
4. Examining the Properties of Pandas DataFrames.mp4 25.9 MB
5. Quiz.html 205 bytes

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