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[] Udemy - Complete Python for Data Science & Machine Learning from A-Z

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文件列表

  1. 53. Competition Section on Kaggle/2. Competitions on Kaggle Lesson 2.mp4 192MB
  2. 53. Competition Section on Kaggle/1. Competitions on Kaggle Lesson 1.mp4 188MB
  3. 55. Code Section on Kaggle/3. Examining the Code Section in Kaggle Lesson 3.mp4 160MB
  4. 54. Dataset Section on Kaggle/1. Datasets on Kaggle.mp4 133MB
  5. 1. Installations/1. Installing Anaconda Distribution for Windows.mp4 130MB
  6. 52. First Contact with Kaggle/1. What is Kaggle.mp4 130MB
  7. 1. Installations/3. Installing Anaconda Distribution for Linux.mp4 127MB
  8. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/6. Recognizing Variables In Dataset.mp4 127MB
  9. 52. First Contact with Kaggle/5. Getting to Know the Kaggle Homepage.mp4 123MB
  10. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/1. First Step to the Hearth Attack Prediction Project.mp4 117MB
  11. 32. Matplotlib/8. Basic Plots in Matplotlib I.mp4 111MB
  12. 57. Other Most Used Options on Kaggle/2. Ranking Among Users on Kaggle.mp4 107MB
  13. 38. Linear Regression Algorithm in Machine Learning A-Z/3. Linear Regression Algorithm With Python Part 2.mp4 107MB
  14. 55. Code Section on Kaggle/2. Examining the Code Section in Kaggle Lesson 2.mp4 106MB
  15. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/3. Notebook Design to be Used in the Project.mp4 105MB
  16. 36. Evaluation Metrics in Machine Learning/2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 100MB
  17. 33. Seaborn/5. Basic Plots in Seaborn.mp4 99MB
  18. 36. Evaluation Metrics in Machine Learning/4. Machine Learning With Python.mp4 92MB
  19. 61. Preparation For Exploratory Data Analysis (EDA) in Data Science/4. Examining Statistics of Variables.mp4 91MB
  20. 29. Functions That Can Be Applied on a DataFrame/3. Aggregation Functions in Pandas DataFrames.mp4 91MB
  21. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/14. Relationships between variables (Analysis with Heatmap) Lesson 2.mp4 91MB
  22. 38. Linear Regression Algorithm in Machine Learning A-Z/5. Linear Regression Algorithm With Python Part 4.mp4 90MB
  23. 29. Functions That Can Be Applied on a DataFrame/5. Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4 88MB
  24. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/4. Categoric Variables (Analysis with Pie Chart) Lesson 2.mp4 84MB
  25. 58. Details on Kaggle/1. User Page Review on Kaggle.mp4 82MB
  26. 40. Logistic Regression Algorithm in Machine Learning A-Z/3. Logistic Regression Algorithm with Python Part 2.mp4 81MB
  27. 34. Geoplotlib/3. Example - 2.mp4 81MB
  28. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/1. Numeric Variables (Analysis with Distplot) Lesson 1.mp4 80MB
  29. 55. Code Section on Kaggle/1. Examining the Code Section in Kaggle Lesson 1.mp4 80MB
  30. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/5. Examining the Project Topic.mp4 77MB
  31. 38. Linear Regression Algorithm in Machine Learning A-Z/2. Linear Regression Algorithm With Python Part 1.mp4 76MB
  32. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/3. Categoric Variables (Analysis with Pie Chart) Lesson 1.mp4 75MB
  33. 58. Details on Kaggle/2. Treasure in The Kaggle.mp4 75MB
  34. 1. Installations/4. Reviewing The Jupyter Notebook.mp4 73MB
  35. 40. Logistic Regression Algorithm in Machine Learning A-Z/2. Logistic Regression Algorithm with Python Part 1.mp4 72MB
  36. 21. Operations in Numpy Library/2. Arithmetic Operations in Numpy.mp4 72MB
  37. 38. Linear Regression Algorithm in Machine Learning A-Z/4. Linear Regression Algorithm With Python Part 3.mp4 70MB
  38. 32. Matplotlib/4. Figure, Subplot and Axes.mp4 70MB
  39. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/10. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 2.mp4 68MB
  40. 26. Structural Operations on Pandas DataFrame/3. Null Values in Pandas Dataframes.mp4 67MB
  41. 31. File Operations in Pandas Library/2. Data Entry with Csv and Txt Files.mp4 64MB
  42. 60. First Organization/3. Initial analysis on the dataset.mp4 64MB
  43. 28. Structural Concatenation Operations in Pandas DataFrame/1. Concatenating Pandas Dataframes Concat Function.mp4 64MB
  44. 60. First Organization/1. Required Python Libraries.mp4 64MB
  45. 32. Matplotlib/5. Figure Customization.mp4 63MB
  46. 1. Installations/2. Installing Anaconda Distribution for MacOs.mp4 61MB
  47. 28. Structural Concatenation Operations in Pandas DataFrame/4. Merge Pandas Dataframes Merge() Function Lesson 3.mp4 60MB
  48. 33. Seaborn/7. Regression Plots and Squarify in Seaborn.mp4 60MB
  49. 17. NumPy Library Introduction/3. The Power of NumPy.mp4 60MB
  50. 42. K Nearest Neighbors Algorithm in Machine Learning A-Z/3. K Nearest Neighbors Algorithm with Python Part 2.mp4 59MB
  51. 12. While Loop in Python Programming Language/2. While Loops in Python Reinforcing the Topic.mp4 59MB
  52. 65. Modelling for Machine Learning/4. Hyperparameter Optimization (with GridSearchCV).mp4 59MB
  53. 58. Details on Kaggle/4. What Should Be Done to Achieve Success in Kaggle.mp4 59MB
  54. 28. Structural Concatenation Operations in Pandas DataFrame/2. Merge Pandas Dataframes Merge() Function Lesson 1.mp4 57MB
  55. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/4. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 2.mp4 56MB
  56. 28. Structural Concatenation Operations in Pandas DataFrame/6. Joining Pandas Dataframes Join() Function.mp4 56MB
  57. 39. Bias Variance Trade-Off in Machine Learning/1. What is Bias Variance Trade-Off.mp4 55MB
  58. 33. Seaborn/3. Example in Seaborn.mp4 55MB
  59. 32. Matplotlib/9. Basic Plots in Matplotlib II.mp4 55MB
  60. 30. Pivot Tables in Pandas Library/2. Pivot Tables in Pandas Library.mp4 54MB
  61. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/5. Examining the Missing Data According to the Analysis Result.mp4 54MB
  62. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/8. Creating a New DataFrame with the Melt() Function.mp4 53MB
  63. 65. Modelling for Machine Learning/8. Hyperparameter Optimization (with GridSearchCV).mp4 53MB
  64. 6. List Data Structure in Python Programming Language/1. Creation of List.mp4 52MB
  65. 57. Other Most Used Options on Kaggle/1. Courses in Kaggle.mp4 52MB
  66. 26. Structural Operations on Pandas DataFrame/5. Filling Null Values Fillna() Function.mp4 52MB
  67. 34. Geoplotlib/4. Example - 3.mp4 51MB
  68. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/1. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 1.mp4 49MB
  69. 1. Installations/5. Reviewing The Jupyter Lab.mp4 49MB
  70. 44. Decision Tree Algorithm in Machine Learning A-Z/3. Decision Tree Algorithm with Python Part 2.mp4 49MB
  71. 33. Seaborn/4. Color Palettes in Seaborn.mp4 48MB
  72. 23. Series Structures in the Pandas Library/6. Most Applied Methods on Pandas Series.mp4 48MB
  73. 43. Hyperparameter Optimization/2. Hyperparameter Optimization with Python.mp4 47MB
  74. 14. Arguments And Parameters in Python Programming Language/1. Arguments and Parameters.mp4 47MB
  75. 46. Support Vector Machine Algorithm in Machine Learning A-Z/4. Support Vector Machine Algorithm with Python Part 3.mp4 47MB
  76. 40. Logistic Regression Algorithm in Machine Learning A-Z/5. Logistic Regression Algorithm with Python Part 4.mp4 47MB
  77. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/6. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 2.mp4 47MB
  78. 29. Functions That Can Be Applied on a DataFrame/8. Advanced Aggregation Functions Transform() Function.mp4 47MB
  79. 29. Functions That Can Be Applied on a DataFrame/4. Examining the Data Set 2.mp4 47MB
  80. 25. Element Selection Operations in DataFrame Structures/6. Element Selection with Conditional Operations in.mp4 46MB
  81. 61. Preparation For Exploratory Data Analysis (EDA) in Data Science/1. Examining Missing Values.mp4 46MB
  82. 20. Indexing, Slicing, and Assigning NumPy Arrays/7. Fancy Indexing of Two-Dimensional Arrrays.mp4 46MB
  83. 36. Evaluation Metrics in Machine Learning/3. Evaluating Performance Regression Error Metrics in Python.mp4 46MB
  84. 17. NumPy Library Introduction/1. Introduction to NumPy Library.mp4 45MB
  85. 61. Preparation For Exploratory Data Analysis (EDA) in Data Science/2. Examining Unique Values.mp4 45MB
  86. 64. Preparation for Modelling in Machine Learning/4. Dealing with Outliers – Trtbps Variable Lesson 2.mp4 44MB
  87. 52. First Contact with Kaggle/3. Registering on Kaggle and Member Login Procedures.mp4 43MB
  88. 18. Creating NumPy Array in Python/8. Creating NumPy Array with Random() Function.mp4 43MB
  89. 33. Seaborn/6. Multi-Plots in Seaborn.mp4 43MB
  90. 29. Functions That Can Be Applied on a DataFrame/2. Examining the Data Set 1.mp4 43MB
  91. 64. Preparation for Modelling in Machine Learning/3. Dealing with Outliers – Trtbps Variable Lesson 1.mp4 43MB
  92. 27. Multi-Indexed DataFrame Structures/1. Multi-Index and Index Hierarchy in Pandas DataFrames.mp4 43MB
  93. 15. Most Used Functions in Python Programming Language/9. Lambda Function.mp4 43MB
  94. 44. Decision Tree Algorithm in Machine Learning A-Z/5. Decision Tree Algorithm with Python Part 4.mp4 42MB
  95. 7. Tuple Data Structure in Python Programming Language/1. Creation of Tuple.mp4 42MB
  96. 5. String Data Type in Python Programming Language/3. Search Method In Strings Startswith(), Endswith().mp4 42MB
  97. 33. Seaborn/2. Controlling Figure Aesthetics in Seaborn.mp4 42MB
  98. 46. Support Vector Machine Algorithm in Machine Learning A-Z/3. Support Vector Machine Algorithm with Python Part 2.mp4 42MB
  99. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/9. Numerical - Categorical Variables (Analysis with Swarm Plot) Lesson 1.mp4 42MB
  100. 65. Modelling for Machine Learning/3. Roc Curve and Area Under Curve (AUC).mp4 42MB
  101. 29. Functions That Can Be Applied on a DataFrame/9. Advanced Aggregation Functions Apply() Function.mp4 41MB
  102. 57. Other Most Used Options on Kaggle/3. Blog and Documentation Sections.mp4 41MB
  103. 28. Structural Concatenation Operations in Pandas DataFrame/5. Merge Pandas Dataframes Merge() Function Lesson 4.mp4 41MB
  104. 56. Discussion Section on Kaggle/1. What is Discussion on Kaggle.mp4 41MB
  105. 10. Conditional Expressions in Python Programming Language/5. Structure of Nested “if-elif-else” Statements.mp4 41MB
  106. 26. Structural Operations on Pandas DataFrame/6. Setting Index in Pandas DataFrames.mp4 40MB
  107. 13. Functions in Python Programming Language/1. Getting know to the Functions.mp4 40MB
  108. 40. Logistic Regression Algorithm in Machine Learning A-Z/6. Logistic Regression Algorithm with Python Part 5.mp4 39MB
  109. 23. Series Structures in the Pandas Library/1. Creating a Pandas Series with a List.mp4 39MB
  110. 30. Pivot Tables in Pandas Library/1. Examining the Data Set 3.mp4 39MB
  111. 14. Arguments And Parameters in Python Programming Language/2. High Level Operations with Arguments.mp4 39MB
  112. 2. First Step to Coding/5. How Should the Coding Form and Style Be (Pep8).mp4 39MB
  113. 13. Functions in Python Programming Language/6. Using Functions and Conditional Expressions Together.mp4 39MB
  114. 34. Geoplotlib/2. Example - 1.mp4 39MB
  115. 45. Random Forest Algorithm in Machine Learning A-Z/3. Random Forest Algorithm with Pyhon Part 2.mp4 39MB
  116. 45. Random Forest Algorithm in Machine Learning A-Z/2. Random Forest Algorithm with Pyhon Part 1.mp4 39MB
  117. 19. Functions in the NumPy Library/4. Concatenating Numpy Arrays Concatenate() Functio.mp4 38MB
  118. 25. Element Selection Operations in DataFrame Structures/3. Top Level Element Selection in Pandas DataFramesLesson 1.mp4 38MB
  119. 58. Details on Kaggle/3. Publishing Notebooks on Kaggle.mp4 38MB
  120. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/11. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 1.mp4 38MB
  121. 50. Principal Component Analysis (PCA) in Machine Learning A-Z/1. Principal Component Analysis (PCA) Theory.mp4 38MB
  122. 3. Basic Operations with Python/2. Performing Assignment to Variables.mp4 38MB
  123. 29. Functions That Can Be Applied on a DataFrame/1. Loading a Dataset from the Seaborn Library.mp4 38MB
  124. 46. Support Vector Machine Algorithm in Machine Learning A-Z/5. Support Vector Machine Algorithm with Python Part 4.mp4 38MB
  125. 50. Principal Component Analysis (PCA) in Machine Learning A-Z/4. Principal Component Analysis (PCA) with Python Part 3.mp4 37MB
  126. 5. String Data Type in Python Programming Language/10. String Formatting With % Operator.mp4 37MB
  127. 4. Boolean Data Type in Python Programming Language/3. Practice with Python.mp4 37MB
  128. 11. For Loop in Python Programming Language/3. Using Conditional Expressions and For Loop Together.mp4 37MB
  129. 2. First Step to Coding/4. Using Quotation Marks in Python Coding.mp4 36MB
  130. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/13. Relationships between variables (Analysis with Heatmap) Lesson 1.mp4 36MB
  131. 64. Preparation for Modelling in Machine Learning/5. Dealing with Outliers – Thalach Variable.mp4 36MB
  132. 64. Preparation for Modelling in Machine Learning/6. Dealing with Outliers – Oldpeak Variable.mp4 36MB
  133. 6. List Data Structure in Python Programming Language/2. Reaching List Elements – Indexing and Slicing.mp4 36MB
  134. 44. Decision Tree Algorithm in Machine Learning A-Z/1. Decision Tree Algorithm Theory.mp4 36MB
  135. 19. Functions in the NumPy Library/6. Splitting Two-Dimensional Numpy Arrays Split(),.mp4 36MB
  136. 31. File Operations in Pandas Library/4. Outputting as an CSV Extension.mp4 36MB
  137. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/2. Numeric Variables – Target Variable (Analysis with FacetGrid) Lesson 2.mp4 36MB
  138. 46. Support Vector Machine Algorithm in Machine Learning A-Z/2. Support Vector Machine Algorithm with Python Part 1.mp4 36MB
  139. 16. Class Structure in Python Programming Language/6. Inheritance Structure.mp4 36MB
  140. 49. Hierarchical Clustering Algorithm in machine learning data science/2. Hierarchical Clustering Algorithm with Python Part 1.mp4 36MB
  141. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/12. Numerical - Categorical Variables (Analysis with Box Plot) Lesson 2.mp4 35MB
  142. 20. Indexing, Slicing, and Assigning NumPy Arrays/5. Assigning Value to Two-Dimensional Array.mp4 35MB
  143. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/7. Feature Scaling with the Robust Scaler Method.mp4 35MB
  144. 42. K Nearest Neighbors Algorithm in Machine Learning A-Z/2. K Nearest Neighbors Algorithm with Python Part 1.mp4 35MB
  145. 64. Preparation for Modelling in Machine Learning/2. Visualizing Outliers.mp4 35MB
  146. 40. Logistic Regression Algorithm in Machine Learning A-Z/4. Logistic Regression Algorithm with Python Part 3.mp4 35MB
  147. 41. K-fold Cross-Validation in Machine Learning A-Z/2. K-Fold Cross-Validation with Python.mp4 35MB
  148. 8. Dictionary Data Structure in Python Programming Language/4. Dictionary Methods.mp4 35MB
  149. 31. File Operations in Pandas Library/1. Accessing and Making Files Available.mp4 35MB
  150. 26. Structural Operations on Pandas DataFrame/4. Dropping Null Values Dropna() Function.mp4 35MB
  151. 20. Indexing, Slicing, and Assigning NumPy Arrays/3. Slicing Two-Dimensional Numpy Arrays.mp4 34MB
  152. 34. Geoplotlib/1. What is Geoplotlib.mp4 34MB
  153. 10. Conditional Expressions in Python Programming Language/4. Structure of “if-elif-else” Statements.mp4 34MB
  154. 38. Linear Regression Algorithm in Machine Learning A-Z/1. Linear Regression Algorithm Theory in Machine Learning A-Z.mp4 34MB
  155. 22. Pandas Library Introduction/1. Introduction to Pandas Library.mp4 34MB
  156. 6. List Data Structure in Python Programming Language/3. Adding & Modifying & Deleting Elements of List.mp4 34MB
  157. 26. Structural Operations on Pandas DataFrame/1. Adding Columns to Pandas Data Frames.mp4 34MB
  158. 5. String Data Type in Python Programming Language/1. Examining Strings Specifically.mp4 33MB
  159. 43. Hyperparameter Optimization/1. Hyperparameter Optimization Theory.mp4 33MB
  160. 5. String Data Type in Python Programming Language/8. Complex Indexing and Slicing Operations.mp4 33MB
  161. 9. Set Data Structure in Python Programming Language/1. Creation of Set.mp4 33MB
  162. 16. Class Structure in Python Programming Language/4. Attribute of Instantiation.mp4 33MB
  163. 3. Basic Operations with Python/4. Type Conversion.mp4 33MB
  164. 44. Decision Tree Algorithm in Machine Learning A-Z/6. Decision Tree Algorithm with Python Part 5.mp4 33MB
  165. 5. String Data Type in Python Programming Language/11. String Formatting With String.Format Method.mp4 32MB
  166. 21. Operations in Numpy Library/3. Statistical Operations in Numpy.mp4 32MB
  167. 25. Element Selection Operations in DataFrame Structures/2. Element Selection Operations in Pandas DataFrames Lesson 2.mp4 32MB
  168. 37. Supervised Learning with Machine Learning/1. What is Supervised Learning in Machine Learning.mp4 32MB
  169. 16. Class Structure in Python Programming Language/2. Features of Class.mp4 32MB
  170. 8. Dictionary Data Structure in Python Programming Language/2. Reaching Dictionary Elements.mp4 32MB
  171. 44. Decision Tree Algorithm in Machine Learning A-Z/2. Decision Tree Algorithm with Python Part 1.mp4 32MB
  172. 25. Element Selection Operations in DataFrame Structures/4. Top Level Element Selection in Pandas DataFramesLesson 2.mp4 31MB
  173. 42. K Nearest Neighbors Algorithm in Machine Learning A-Z/4. K Nearest Neighbors Algorithm with Python Part 3.mp4 31MB
  174. 27. Multi-Indexed DataFrame Structures/3. Selecting Elements Using the xs() Function in Multi-Indexed DataFrames.mp4 31MB
  175. 28. Structural Concatenation Operations in Pandas DataFrame/3. Merge Pandas Dataframes Merge() Function Lesson 2.mp4 31MB
  176. 3. Basic Operations with Python/5. Arithmetic Operations in Python.mp4 30MB
  177. 65. Modelling for Machine Learning/2. Cross Validation.mp4 30MB
  178. 3. Basic Operations with Python/7. Escape Sequence Operations.mp4 30MB
  179. 48. K Means Clustering Algorithm in Machine Learning A-Z/2. K Means Clustering Algorithm with Python Part 1.mp4 30MB
  180. 25. Element Selection Operations in DataFrame Structures/1. Element Selection Operations in Pandas DataFrames Lesson 1.mp4 30MB
  181. 23. Series Structures in the Pandas Library/7. Indexing and Slicing Pandas Series.mp4 30MB
  182. 65. Modelling for Machine Learning/7. Random Forest Algorithm.mp4 30MB
  183. 64. Preparation for Modelling in Machine Learning/11. Separating Data into Test and Training Set.mp4 30MB
  184. 48. K Means Clustering Algorithm in Machine Learning A-Z/3. K Means Clustering Algorithm with Python Part 2.mp4 30MB
  185. 18. Creating NumPy Array in Python/1. Creating NumPy Array with The Array() Function.mp4 29MB
  186. 65. Modelling for Machine Learning/1. Logistic Regression.mp4 29MB
  187. 3. Basic Operations with Python/6. Examining the Print Function in Depth.mp4 29MB
  188. 29. Functions That Can Be Applied on a DataFrame/6. Advanced Aggregation Functions Aggregate() Function.mp4 29MB
  189. 48. K Means Clustering Algorithm in Machine Learning A-Z/5. K Means Clustering Algorithm with Python Part 4.mp4 29MB
  190. 49. Hierarchical Clustering Algorithm in machine learning data science/3. Hierarchical Clustering Algorithm with Python Part 2.mp4 29MB
  191. 42. K Nearest Neighbors Algorithm in Machine Learning A-Z/1. K Nearest Neighbors Algorithm Theory.mp4 29MB
  192. 66. Conclusion/1. Project Conclusion and Sharing.mp4 29MB
  193. 49. Hierarchical Clustering Algorithm in machine learning data science/1. Hierarchical Clustering Algorithm Theory.mp4 29MB
  194. 32. Matplotlib/3. Pyplot – Pylab - Matplotlib.mp4 28MB
  195. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/5. Examining Numeric Variables Among Themselves (Analysis with Pair Plot) Lesson 1.mp4 28MB
  196. 32. Matplotlib/2. Using Pyplot.mp4 28MB
  197. 2. First Step to Coding/3. First Step to Coding.mp4 28MB
  198. 40. Logistic Regression Algorithm in Machine Learning A-Z/1. What is Logistic Regression Algorithm in Machine Learning.mp4 28MB
  199. 10. Conditional Expressions in Python Programming Language/2. Structure of “if” Statements.mp4 28MB
  200. 48. K Means Clustering Algorithm in Machine Learning A-Z/4. K Means Clustering Algorithm with Python Part 3.mp4 28MB
  201. 35. Intro to Machine Learning with Python/1. What is Machine Learning.mp4 28MB
  202. 15. Most Used Functions in Python Programming Language/1. all(), any() Functions.mp4 28MB
  203. 32. Matplotlib/6. Plot Customization.mp4 27MB
  204. 5. String Data Type in Python Programming Language/7. Indexing and Slicing Character String.mp4 27MB
  205. 64. Preparation for Modelling in Machine Learning/1. Dropping Columns with Low Correlation.mp4 27MB
  206. 20. Indexing, Slicing, and Assigning NumPy Arrays/1. Indexing Numpy Arrays.mp4 27MB
  207. 19. Functions in the NumPy Library/1. Reshaping a NumPy Array Reshape() Function.mp4 26MB
  208. 3. Basic Operations with Python/1. Introduction to Basic Data Structures in Python.mp4 26MB
  209. 50. Principal Component Analysis (PCA) in Machine Learning A-Z/2. Principal Component Analysis (PCA) with Python Part 1.mp4 26MB
  210. 24. DataFrame Structures in Pandas Library/4. Examining the Properties of Pandas DataFrames.mp4 26MB
  211. 11. For Loop in Python Programming Language/6. List Comprehension.mp4 26MB
  212. 65. Modelling for Machine Learning/5. Decision Tree Algorithm.mp4 26MB
  213. 2. First Step to Coding/1. Python Introduction.mp4 25MB
  214. 64. Preparation for Modelling in Machine Learning/7. Determining Distributions of Numeric Variables.mp4 25MB
  215. 10. Conditional Expressions in Python Programming Language/6. Coordinated Programming with “IF” and “INPUT”.mp4 25MB
  216. 6. List Data Structure in Python Programming Language/6. Other List Methods.mp4 25MB
  217. 27. Multi-Indexed DataFrame Structures/2. Element Selection in Multi-Indexed DataFrames.mp4 25MB
  218. 65. Modelling for Machine Learning/6. Support Vector Machine Algorithm.mp4 25MB
  219. 29. Functions That Can Be Applied on a DataFrame/7. Advanced Aggregation Functions Filter() Function.mp4 24MB
  220. 13. Functions in Python Programming Language/2. How to Write Function.mp4 24MB
  221. 5. String Data Type in Python Programming Language/6. Character Clipping Methods in String.mp4 24MB
  222. 21. Operations in Numpy Library/4. Solving Second-Degree Equations with NumPy.mp4 24MB
  223. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/3. Categoric Variables – Target Variable (Analysis with Count Plot) Lesson 1.mp4 24MB
  224. 64. Preparation for Modelling in Machine Learning/9. Applying One Hot Encoding Method to Categorical Variables.mp4 24MB
  225. 18. Creating NumPy Array in Python/2. Creating NumPy Array with Zeros() Function.mp4 24MB
  226. 64. Preparation for Modelling in Machine Learning/8. Transformation Operations on Unsymmetrical Data.mp4 24MB
  227. 16. Class Structure in Python Programming Language/5. Write Function in the Class.mp4 24MB
  228. 32. Matplotlib/7. Grid, Spines, Ticks.mp4 24MB
  229. 16. Class Structure in Python Programming Language/3. Instantiation of Class.mp4 23MB
  230. 11. For Loop in Python Programming Language/2. For Loop in Python(Reinforcing the Topic).mp4 23MB
  231. 51. Recommender System Algorithm in Machine Learning A-Z/1. What is the Recommender System Part 1.mp4 23MB
  232. 9. Set Data Structure in Python Programming Language/5. Asking Questions to Sets with Methods.mp4 23MB
  233. 45. Random Forest Algorithm in Machine Learning A-Z/1. Random Forest Algorithm Theory.mp4 23MB
  234. 11. For Loop in Python Programming Language/1. For Loop in Python.mp4 23MB
  235. 24. DataFrame Structures in Pandas Library/1. Creating Pandas DataFrame with List.mp4 23MB
  236. 20. Indexing, Slicing, and Assigning NumPy Arrays/2. Slicing One-Dimensional Numpy Arrays.mp4 22MB
  237. 25. Element Selection Operations in DataFrame Structures/5. Top Level Element Selection in Pandas DataFramesLesson 3.mp4 22MB
  238. 18. Creating NumPy Array in Python/9. Properties of NumPy Array.mp4 22MB
  239. 46. Support Vector Machine Algorithm in Machine Learning A-Z/1. Support Vector Machine Algorithm Theory.mp4 22MB
  240. 8. Dictionary Data Structure in Python Programming Language/1. Creation of Dictionary.mp4 22MB
  241. 31. File Operations in Pandas Library/3. Data Entry with Excel Files.mp4 22MB
  242. 6. List Data Structure in Python Programming Language/4. Adding and Deleting by Methods.mp4 21MB
  243. 21. Operations in Numpy Library/1. Operations with Comparison Operators.mp4 21MB
  244. 5. String Data Type in Python Programming Language/9. String Formatting with Arithmetic Operations.mp4 21MB
  245. 19. Functions in the NumPy Library/5. Splitting One-Dimensional Numpy Arrays The Split.mp4 21MB
  246. 11. For Loop in Python Programming Language/5. Break Command.mp4 21MB
  247. 5. String Data Type in Python Programming Language/12. String Formatting With f-string Method.mp4 21MB
  248. 10. Conditional Expressions in Python Programming Language/7. Ternary Condition.mp4 21MB
  249. 20. Indexing, Slicing, and Assigning NumPy Arrays/6. Fancy Indexing of One-Dimensional Arrrays.mp4 20MB
  250. 6. List Data Structure in Python Programming Language/5. Adding and Deleting by Index.mp4 20MB
  251. 13. Functions in Python Programming Language/5. Writing Docstring in Functions.mp4 20MB
  252. 10. Conditional Expressions in Python Programming Language/1. Comparison Operators.mp4 20MB
  253. 4. Boolean Data Type in Python Programming Language/1. Boolean Logic Expressions.mp4 20MB
  254. 9. Set Data Structure in Python Programming Language/3. Difference Operation Methods In Sets.mp4 20MB
  255. 36. Evaluation Metrics in Machine Learning/1. Classification vs Regression in Machine Learning.mp4 20MB
  256. 31. File Operations in Pandas Library/5. Outputting as an Excel File.mp4 20MB
  257. 7. Tuple Data Structure in Python Programming Language/2. Reaching Tuple Elements Indexing And Slicing.mp4 20MB
  258. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/2. Numeric Variables (Analysis with Distplot) Lesson 2.mp4 20MB
  259. 23. Series Structures in the Pandas Library/4. Object Types in Series.mp4 20MB
  260. 32. Matplotlib/1. What is Matplotlib.mp4 19MB
  261. 23. Series Structures in the Pandas Library/5. Examining the Primary Features of the Pandas Seri.mp4 19MB
  262. 9. Set Data Structure in Python Programming Language/2. Adding & Removing Elements Methods in Sets.mp4 19MB
  263. 23. Series Structures in the Pandas Library/2. Creating a Pandas Series with a Dictionary.mp4 18MB
  264. 20. Indexing, Slicing, and Assigning NumPy Arrays/4. Assigning Value to One-Dimensional Arrays.mp4 18MB
  265. 51. Recommender System Algorithm in Machine Learning A-Z/2. What is the Recommender System Part 2.mp4 18MB
  266. 13. Functions in Python Programming Language/3. Return Expression in Functions.mp4 18MB
  267. 5. String Data Type in Python Programming Language/4. Character Change Method In Strings Replace().mp4 18MB
  268. 41. K-fold Cross-Validation in Machine Learning A-Z/1. K-Fold Cross-Validation Theory.mp4 17MB
  269. 48. K Means Clustering Algorithm in Machine Learning A-Z/1. K Means Clustering Algorithm Theory.mp4 17MB
  270. 5. String Data Type in Python Programming Language/5. Spelling Substitution Methods in String.mp4 17MB
  271. 19. Functions in the NumPy Library/7. Sorting Numpy Arrays Sort() Function.mp4 17MB
  272. 12. While Loop in Python Programming Language/1. While Loop in Python.mp4 17MB
  273. 47. Unsupervised Learning with Machine Learning/1. Unsupervised Learning Overview.mp4 17MB
  274. 20. Indexing, Slicing, and Assigning NumPy Arrays/9. Combining Fancy Index with Normal Slicing.mp4 16MB
  275. 15. Most Used Functions in Python Programming Language/3. filter() Function.mp4 16MB
  276. 8. Dictionary Data Structure in Python Programming Language/3. Adding & Changing & Deleting Elements in Dictionary.mp4 16MB
  277. 15. Most Used Functions in Python Programming Language/2. map() Function.mp4 16MB
  278. 18. Creating NumPy Array in Python/3. Creating NumPy Array with Ones() Function.mp4 16MB
  279. 24. DataFrame Structures in Pandas Library/3. Creating Pandas DataFrame with Dictionary.mp4 16MB
  280. 61. Preparation For Exploratory Data Analysis (EDA) in Data Science/3. Separating variables (Numeric or Categorical).mp4 16MB
  281. 10. Conditional Expressions in Python Programming Language/3. Structure of “if-else” Statements.mp4 16MB
  282. 26. Structural Operations on Pandas DataFrame/2. Removing Rows and Columns from Pandas Data frames.mp4 16MB
  283. 19. Functions in the NumPy Library/2. Identifying the Largest Element of a Numpy Array.mp4 15MB
  284. 3. Basic Operations with Python/3. Performing Complex Assignment to Variables.mp4 15MB
  285. 44. Decision Tree Algorithm in Machine Learning A-Z/4. Decision Tree Algorithm with Python Part 3.mp4 15MB
  286. 15. Most Used Functions in Python Programming Language/4. zip() Function.mp4 14MB
  287. 35. Intro to Machine Learning with Python/2. Machine Learning Terminology.mp4 14MB
  288. 11. For Loop in Python Programming Language/4. Continue Command.mp4 14MB
  289. 33. Seaborn/1. What is Seaborn.mp4 14MB
  290. 15. Most Used Functions in Python Programming Language/8. round() Function.mp4 14MB
  291. 13. Functions in Python Programming Language/4. Writing Functions with Multiple Argument.mp4 14MB
  292. 16. Class Structure in Python Programming Language/1. Local and Global Variables.mp4 13MB
  293. 20. Indexing, Slicing, and Assigning NumPy Arrays/8. Combining Fancy Index with Normal Indexing.mp4 13MB
  294. 18. Creating NumPy Array in Python/6. Creating NumPy Array with Eye() Function.mp4 13MB
  295. 15. Most Used Functions in Python Programming Language/5. enumerate() Function.mp4 13MB
  296. 24. DataFrame Structures in Pandas Library/2. Creating Pandas DataFrame with NumPy Array.mp4 12MB
  297. 18. Creating NumPy Array in Python/5. Creating NumPy Array with Arange() Function.mp4 12MB
  298. 23. Series Structures in the Pandas Library/3. Creating Pandas Series with NumPy Array.mp4 12MB
  299. 64. Preparation for Modelling in Machine Learning/10. Feature Scaling with the Robust Scaler Method for Machine Learning Algorithms.mp4 11MB
  300. 18. Creating NumPy Array in Python/4. Creating NumPy Array with Full() Function.mp4 11MB
  301. 9. Set Data Structure in Python Programming Language/4. Intersection & Union Methods In Sets.mp4 11MB
  302. 19. Functions in the NumPy Library/3. Detecting Least Element of Numpy Array Min(), Ar.mp4 10MB
  303. 60. First Organization/2. Loading the Statistics Dataset in Data Science.mp4 10MB
  304. 5. String Data Type in Python Programming Language/2. Accessing Length Information (Len Method).mp4 9MB
  305. 50. Principal Component Analysis (PCA) in Machine Learning A-Z/3. Principal Component Analysis (PCA) with Python Part 2.mp4 8MB
  306. 15. Most Used Functions in Python Programming Language/6. max(), min() Functions.mp4 8MB
  307. 18. Creating NumPy Array in Python/7. Creating NumPy Array with Linspace() Function.mp4 7MB
  308. 15. Most Used Functions in Python Programming Language/7. sum() Function.mp4 6MB
  309. 4. Boolean Data Type in Python Programming Language/2. Order Of Operations In Boolean Operators.mp4 4MB
  310. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/2. FAQ about Machine Learning, Data Science.html 15KB
  311. 52. First Contact with Kaggle/2. FAQ about Kaggle.html 11KB
  312. 67. Extra/1. Complete Python for Data Science & Machine Learning from A-Z.html 266B
  313. 35. Intro to Machine Learning with Python/3. Machine Learning Project Files.html 254B
  314. 10. Conditional Expressions in Python Programming Language/8. Quiz.html 209B
  315. 11. For Loop in Python Programming Language/7. Quiz.html 209B
  316. 12. While Loop in Python Programming Language/3. Quiz.html 209B
  317. 13. Functions in Python Programming Language/7. Quiz.html 209B
  318. 14. Arguments And Parameters in Python Programming Language/3. Quiz.html 209B
  319. 15. Most Used Functions in Python Programming Language/10. Quiz.html 209B
  320. 17. NumPy Library Introduction/4. Quiz.html 209B
  321. 18. Creating NumPy Array in Python/10. Quiz.html 209B
  322. 19. Functions in the NumPy Library/8. Quiz.html 209B
  323. 2. First Step to Coding/6. Quiz.html 209B
  324. 3. Basic Operations with Python/8. Quiz.html 209B
  325. 35. Intro to Machine Learning with Python/4. Quiz.html 209B
  326. 36. Evaluation Metrics in Machine Learning/5. Quiz.html 209B
  327. 37. Supervised Learning with Machine Learning/2. Quiz.html 209B
  328. 39. Bias Variance Trade-Off in Machine Learning/2. Quiz.html 209B
  329. 4. Boolean Data Type in Python Programming Language/4. Quiz.html 209B
  330. 40. Logistic Regression Algorithm in Machine Learning A-Z/7. Quiz.html 209B
  331. 42. K Nearest Neighbors Algorithm in Machine Learning A-Z/5. Quiz.html 209B
  332. 44. Decision Tree Algorithm in Machine Learning A-Z/7. Quiz.html 209B
  333. 46. Support Vector Machine Algorithm in Machine Learning A-Z/6. Quiz.html 209B
  334. 47. Unsupervised Learning with Machine Learning/2. Quiz.html 209B
  335. 48. K Means Clustering Algorithm in Machine Learning A-Z/6. Quiz.html 209B
  336. 49. Hierarchical Clustering Algorithm in machine learning data science/4. Quiz.html 209B
  337. 5. String Data Type in Python Programming Language/13. Quiz.html 209B
  338. 51. Recommender System Algorithm in Machine Learning A-Z/3. Quiz.html 209B
  339. 52. First Contact with Kaggle/6. Quiz.html 209B
  340. 53. Competition Section on Kaggle/3. Quiz.html 209B
  341. 54. Dataset Section on Kaggle/2. Quiz.html 209B
  342. 55. Code Section on Kaggle/4. Quiz.html 209B
  343. 56. Discussion Section on Kaggle/2. Quiz.html 209B
  344. 57. Other Most Used Options on Kaggle/4. Quiz.html 209B
  345. 58. Details on Kaggle/5. Quiz.html 209B
  346. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/7. Quiz.html 209B
  347. 6. List Data Structure in Python Programming Language/7. Quiz.html 209B
  348. 60. First Organization/4. Quiz.html 209B
  349. 61. Preparation For Exploratory Data Analysis (EDA) in Data Science/5. Quiz.html 209B
  350. 62. Exploratory Data Analysis (EDA) - Uni-variate Analysis/6. Quiz.html 209B
  351. 63. Exploratory Data Analysis (EDA) - Bi-variate Analysis/15. Quiz.html 209B
  352. 64. Preparation for Modelling in Machine Learning/12. Quiz.html 209B
  353. 65. Modelling for Machine Learning/9. Quiz.html 209B
  354. 66. Conclusion/2. Quiz.html 209B
  355. 7. Tuple Data Structure in Python Programming Language/3. Quiz.html 209B
  356. 8. Dictionary Data Structure in Python Programming Language/5. Quiz.html 209B
  357. 9. Set Data Structure in Python Programming Language/6. Quiz.html 209B
  358. 22. Pandas Library Introduction/2. Pandas Project Files Link.html 180B
  359. 17. NumPy Library Introduction/2. Notebook Project Files Link regarding NumPy Python Programming Language Library.html 155B
  360. 0. Websites you may like/[FreeCourseSite.com].url 127B
  361. 13. Functions in Python Programming Language/0. Websites you may like/[FreeCourseSite.com].url 127B
  362. 23. Series Structures in the Pandas Library/0. Websites you may like/[FreeCourseSite.com].url 127B
  363. 0. Websites you may like/[CourseClub.Me].url 122B
  364. 13. Functions in Python Programming Language/0. Websites you may like/[CourseClub.Me].url 122B
  365. 23. Series Structures in the Pandas Library/0. Websites you may like/[CourseClub.Me].url 122B
  366. 59. Introduction to Machine Learning with Real Hearth Attack Prediction Project/4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html 108B
  367. 52. First Contact with Kaggle/4. Project Link File - Hearth Attack Prediction Project, Machine Learning.html 97B
  368. 2. First Step to Coding/2. Project Files.html 54B
  369. 0. Websites you may like/[GigaCourse.Com].url 49B
  370. 13. Functions in Python Programming Language/0. Websites you may like/[GigaCourse.Com].url 49B
  371. 23. Series Structures in the Pandas Library/0. Websites you may like/[GigaCourse.Com].url 49B