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[ ] Udemy - Numerical Methods and Optimization in Python

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  1. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/005 Stochastic gradient descent implementation I.mp4 106MB
  2. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/008 ADAGrad implementation.mp4 64MB
  3. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/017 Sorting.mp4 51MB
  4. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/002 Gradient descent implementation.mp4 48MB
  5. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/016 Sets in Python.mp4 47MB
  6. ~Get Your Files Here !/17 - Appendix #2 - Functions/003 Positional arguments and keyword arguments.mp4 46MB
  7. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/011 ADAM optimizer implementation.mp4 43MB
  8. ~Get Your Files Here !/21 - Appendix #6 - Pandas/005 DataFrame operations.mp4 41MB
  9. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/006 Stochastic gradient descent implementation II.mp4 41MB
  10. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/013 Comparing objects - overriding functions.mp4 40MB
  11. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/002 Monte-Carlo integral implementation I.mp4 40MB
  12. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/006 Lists in Python - advanced operations.mp4 39MB
  13. ~Get Your Files Here !/09 - Interpolation/001 What is interpolation.mp4 39MB
  14. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/015 Dictionaries in Python.mp4 38MB
  15. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/008 PageRank algorithm - the final formula.mp4 38MB
  16. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/001 How to measure the running time of algorithms.mp4 37MB
  17. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/004 Stochastic gradient descent introduction.mp4 36MB
  18. ~Get Your Files Here !/20 - Appendix #5 - NumPy/003 Dimension of arrays.mp4 36MB
  19. ~Get Your Files Here !/05 - Gauss Elimination Implementation/001 Gaussian elimination implementation I.mp4 36MB
  20. ~Get Your Files Here !/17 - Appendix #2 - Functions/008 What is recursion.mp4 35MB
  21. ~Get Your Files Here !/21 - Appendix #6 - Pandas/007 Reading CSV and text files.mp4 35MB
  22. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/012 What are linked list data structures.mp4 34MB
  23. ~Get Your Files Here !/13 - Differential Equations/004 Euler's method example - pendulum.mp4 34MB
  24. ~Get Your Files Here !/20 - Appendix #5 - NumPy/006 Reshape.mp4 34MB
  25. ~Get Your Files Here !/20 - Appendix #5 - NumPy/002 Creating and updating arrays.mp4 34MB
  26. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/003 Using the constructor.mp4 34MB
  27. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/010 Polymorphism and abstraction example.mp4 33MB
  28. ~Get Your Files Here !/21 - Appendix #6 - Pandas/008 Operations.mp4 33MB
  29. ~Get Your Files Here !/20 - Appendix #5 - NumPy/004 Indexes and slicing.mp4 32MB
  30. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/009 How to use multiple conditions.mp4 31MB
  31. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/004 Class variables and instance variables.mp4 31MB
  32. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/014 Hashing and O(1) running time complexity.mp4 31MB
  33. ~Get Your Files Here !/09 - Interpolation/004 Interpolation implementation II.mp4 31MB
  34. ~Get Your Files Here !/21 - Appendix #6 - Pandas/010 Using the apply() function.mp4 31MB
  35. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/001 What is the Monte-Carlo method.mp4 30MB
  36. ~Get Your Files Here !/05 - Gauss Elimination Implementation/002 Gaussian elimination implementation II.mp4 30MB
  37. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/005 Matrix representation of the problem.mp4 29MB
  38. ~Get Your Files Here !/21 - Appendix #6 - Pandas/006 Speed comparison - DataFrame operations.mp4 29MB
  39. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/004 Strings.mp4 28MB
  40. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/001 What is gradient descent.mp4 28MB
  41. ~Get Your Files Here !/20 - Appendix #5 - NumPy/007 Stacking and merging arrays.mp4 28MB
  42. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/004 Speed consideration - C, Java and Python.mp4 28MB
  43. ~Get Your Files Here !/21 - Appendix #6 - Pandas/009 Data filtering.mp4 27MB
  44. ~Get Your Files Here !/03 - Linear Algebra/003 Running time analysis of matrix multiplication.mp4 27MB
  45. ~Get Your Files Here !/21 - Appendix #6 - Pandas/003 Series.mp4 27MB
  46. ~Get Your Files Here !/21 - Appendix #6 - Pandas/012 What is vectorization.mp4 26MB
  47. ~Get Your Files Here !/09 - Interpolation/003 Interpolation implementation I.mp4 26MB
  48. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/002 Crawling the web with breadth-first search.mp4 26MB
  49. ~Get Your Files Here !/21 - Appendix #6 - Pandas/001 What is Pandas.mp4 25MB
  50. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/005 String slicing.mp4 25MB
  51. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/001 Graph representation of the WWW.mp4 25MB
  52. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/003 What are array data structures I.mp4 25MB
  53. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/004 What are array data structures II.mp4 25MB
  54. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/004 PageRank algorithm example.mp4 25MB
  55. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/003 Monte-Carlo integral implementation II.mp4 25MB
  56. ~Get Your Files Here !/13 - Differential Equations/001 How to deal with differential equations.mp4 25MB
  57. ~Get Your Files Here !/13 - Differential Equations/007 Runge-Kutta method example I.mp4 24MB
  58. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/001 Floating point numbers.mp4 24MB
  59. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/013 Doubly linked list implementation in Python.mp4 24MB
  60. ~Get Your Files Here !/10 - Root Finding/003 Bisection method implementation.mp4 24MB
  61. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/007 Lists in Python - list comprehension.mp4 23MB
  62. ~Get Your Files Here !/11 - Numerical Integration/003 Rectangle method implementation.mp4 22MB
  63. ~Get Your Files Here !/13 - Differential Equations/008 Runge-Kutta method example II.mp4 22MB
  64. ~Get Your Files Here !/21 - Appendix #6 - Pandas/013 Vectorization example I.mp4 22MB
  65. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/007 What is ADAGrad.mp4 22MB
  66. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/011 Modules.mp4 22MB
  67. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/005 Lists in Python.mp4 22MB
  68. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/009 Power method.mp4 21MB
  69. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/007 The super keyword.mp4 21MB
  70. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/009 What is polymorphism.mp4 21MB
  71. ~Get Your Files Here !/21 - Appendix #6 - Pandas/014 Vectorization example II.mp4 21MB
  72. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/007 Operators.mp4 21MB
  73. ~Get Your Files Here !/03 - Linear Algebra/002 Matrix multiplication implementation.mp4 21MB
  74. ~Get Your Files Here !/11 - Numerical Integration/007 Simpson's method implementation.mp4 21MB
  75. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/015 Break and continue.mp4 20MB
  76. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/003 Gradient descent with momentum.mp4 20MB
  77. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/003 What is pivoting.mp4 20MB
  78. ~Get Your Files Here !/13 - Differential Equations/003 Euler's method example.mp4 20MB
  79. ~Get Your Files Here !/03 - Linear Algebra/006 Lists and NumPy arrays.mp4 19MB
  80. ~Get Your Files Here !/20 - Appendix #5 - NumPy/005 Types.mp4 19MB
  81. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/005 Private variables and name mangling.mp4 19MB
  82. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/009 What is RMSProp.mp4 19MB
  83. ~Get Your Files Here !/11 - Numerical Integration/004 Trapezoidal integral introduction.mp4 19MB
  84. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/011 Loops - for loop.mp4 19MB
  85. ~Get Your Files Here !/17 - Appendix #2 - Functions/002 Defining functions.mp4 19MB
  86. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/006 The random surfer model.mp4 19MB
  87. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/011 Mutability and immutability.mp4 18MB
  88. ~Get Your Files Here !/21 - Appendix #6 - Pandas/004 DataFrames.mp4 18MB
  89. ~Get Your Files Here !/17 - Appendix #2 - Functions/006 Yield operator.mp4 18MB
  90. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/008 Function (method) override.mp4 18MB
  91. ~Get Your Files Here !/11 - Numerical Integration/002 Rectangle method introduction.mp4 18MB
  92. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/006 What is inheritance in OOP.mp4 18MB
  93. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/008 Conditional statements.mp4 18MB
  94. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/003 The original formula.mp4 18MB
  95. ~Get Your Files Here !/21 - Appendix #6 - Pandas/011 Speed comparison - loops and apply().mp4 18MB
  96. ~Get Your Files Here !/11 - Numerical Integration/005 Trapezoidal integral implementation.mp4 18MB
  97. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/010 Logical operators.mp4 18MB
  98. ~Get Your Files Here !/17 - Appendix #2 - Functions/001 What are functions.mp4 17MB
  99. ~Get Your Files Here !/20 - Appendix #5 - NumPy/001 What is the key advantage of NumPy.mp4 17MB
  100. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/001 What is Gaussian elimination.mp4 17MB
  101. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/006 Type casting.mp4 17MB
  102. ~Get Your Files Here !/03 - Linear Algebra/005 Inner product.mp4 17MB
  103. ~Get Your Files Here !/10 - Root Finding/004 Newton method introduction.mp4 16MB
  104. ~Get Your Files Here !/13 - Differential Equations/005 Euler's method example - pendulum with drag.mp4 16MB
  105. ~Get Your Files Here !/10 - Root Finding/005 Newton method implementation.mp4 16MB
  106. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/002 What are the basic data types.mp4 16MB
  107. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/012 The __str__ function.mp4 16MB
  108. ~Get Your Files Here !/17 - Appendix #2 - Functions/007 What are the most relevant built-in functions.mp4 15MB
  109. ~Get Your Files Here !/20 - Appendix #5 - NumPy/008 Filter.mp4 15MB
  110. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/014 Enumerate.mp4 15MB
  111. ~Get Your Files Here !/09 - Interpolation/002 Interpolation illustration.mp4 15MB
  112. ~Get Your Files Here !/17 - Appendix #2 - Functions/009 Local vs global variables.mp4 15MB
  113. ~Get Your Files Here !/17 - Appendix #2 - Functions/010 The __main__ function.mp4 15MB
  114. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/010 What are tuples.mp4 15MB
  115. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/012 Loops - while loop.mp4 14MB
  116. ~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/001 What are eigenvalues and eigenvectors.mp4 14MB
  117. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/004 Applications of Monte-Carlo simulations in finance.mp4 14MB
  118. ~Get Your Files Here !/13 - Differential Equations/006 Runge-Kutta method introduction.mp4 14MB
  119. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/003 Rounding errors.mp4 14MB
  120. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/002 Data structures introduction.mp4 14MB
  121. ~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/002 Portfolio optimization implementation.mp4 14MB
  122. ~Get Your Files Here !/03 - Linear Algebra/007 Matrix operations with NumPy.mp4 14MB
  123. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/001 First steps in Python.mp4 14MB
  124. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/002 Gaussian elimination illustration.mp4 14MB
  125. ~Get Your Files Here !/01 - Introduction/001 Introduction.mp4 14MB
  126. ~Get Your Files Here !/03 - Linear Algebra/004 Matrix vector multiplication.mp4 13MB
  127. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/013 What are nested loops.mp4 13MB
  128. ~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/001 Portfolio optimization introduction.mp4 13MB
  129. ~Get Your Files Here !/13 - Differential Equations/002 Euler's method introduction.mp4 13MB
  130. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/001 What is object oriented programming (OOP).mp4 13MB
  131. ~Get Your Files Here !/03 - Linear Algebra/001 Matrix multiplication introduction.mp4 12MB
  132. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/010 ADAM optimizer introduction.mp4 12MB
  133. ~Get Your Files Here !/10 - Root Finding/001 Root of functions introduction.mp4 12MB
  134. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/007 What are the problems with the random surfer model.mp4 12MB
  135. ~Get Your Files Here !/17 - Appendix #2 - Functions/005 Returning multiple values.mp4 12MB
  136. ~Get Your Files Here !/11 - Numerical Integration/006 Simpson's method introduction.mp4 12MB
  137. ~Get Your Files Here !/11 - Numerical Integration/001 Integration introduction.mp4 11MB
  138. ~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/002 Eigenvalues and eigenvectors implementation.mp4 11MB
  139. ~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/003 Applications of eigenvectors in machine learning.mp4 11MB
  140. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/002 Class and objects basics.mp4 10MB
  141. ~Get Your Files Here !/21 - Appendix #6 - Pandas/002 First steps.mp4 10MB
  142. ~Get Your Files Here !/10 - Root Finding/002 Bisection method introduction.mp4 10MB
  143. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/002 Precision and accuracy.mp4 9MB
  144. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/004 Gaussian elimination and singular matrixes.mp4 9MB
  145. ~Get Your Files Here !/09 - Interpolation/005 Applications of interpolation.mp4 9MB
  146. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/016 Calculating Fibonacci-numbers.mp4 8MB
  147. ~Get Your Files Here !/17 - Appendix #2 - Functions/004 Returning values.mp4 8MB
  148. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/003 Booleans.mp4 7MB
  149. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/numerical_methods.pptx 3MB
  150. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/house_prices.csv 2MB
  151. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/005 Stochastic gradient descent implementation I_en.vtt 24KB
  152. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/008 ADAGrad implementation_en.vtt 14KB
  153. ~Get Your Files Here !/13 - Differential Equations/004 Euler's method example - pendulum_en.vtt 13KB
  154. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/001 How to measure the running time of algorithms_en.vtt 13KB
  155. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/004 Stochastic gradient descent introduction_en.vtt 12KB
  156. ~Get Your Files Here !/17 - Appendix #2 - Functions/003 Positional arguments and keyword arguments_en.vtt 12KB
  157. ~Get Your Files Here !/05 - Gauss Elimination Implementation/001 Gaussian elimination implementation I_en.vtt 12KB
  158. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/017 Sorting_en.vtt 11KB
  159. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/002 Gradient descent implementation_en.vtt 11KB
  160. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/004 PageRank algorithm example_en.vtt 11KB
  161. ~Get Your Files Here !/21 - Appendix #6 - Pandas/005 DataFrame operations_en.vtt 11KB
  162. ~Get Your Files Here !/09 - Interpolation/001 What is interpolation_en.vtt 11KB
  163. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/015 Dictionaries in Python_en.vtt 11KB
  164. ~Get Your Files Here !/20 - Appendix #5 - NumPy/003 Dimension of arrays_en.vtt 11KB
  165. ~Get Your Files Here !/17 - Appendix #2 - Functions/008 What is recursion_en.vtt 11KB
  166. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/012 What are linked list data structures_en.vtt 10KB
  167. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/011 ADAM optimizer implementation_en.vtt 10KB
  168. ~Get Your Files Here !/13 - Differential Equations/001 How to deal with differential equations_en.vtt 10KB
  169. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/005 Matrix representation of the problem_en.vtt 10KB
  170. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/014 Hashing and O(1) running time complexity_en.vtt 10KB
  171. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/016 Sets in Python_en.vtt 10KB
  172. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/002 Monte-Carlo integral implementation I_en.vtt 10KB
  173. ~Get Your Files Here !/20 - Appendix #5 - NumPy/004 Indexes and slicing_en.vtt 9KB
  174. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/001 Floating point numbers_en.vtt 9KB
  175. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/013 Comparing objects - overriding functions_en.vtt 9KB
  176. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/009 How to use multiple conditions_en.vtt 9KB
  177. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/008 PageRank algorithm - the final formula_en.vtt 9KB
  178. ~Get Your Files Here !/20 - Appendix #5 - NumPy/006 Reshape_en.vtt 9KB
  179. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/004 Strings_en.vtt 9KB
  180. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/006 Lists in Python - advanced operations_en.vtt 9KB
  181. ~Get Your Files Here !/21 - Appendix #6 - Pandas/009 Data filtering_en.vtt 9KB
  182. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/004 What are array data structures II_en.vtt 9KB
  183. ~Get Your Files Here !/20 - Appendix #5 - NumPy/002 Creating and updating arrays_en.vtt 8KB
  184. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/002 Crawling the web with breadth-first search_en.vtt 8KB
  185. ~Get Your Files Here !/21 - Appendix #6 - Pandas/003 Series_en.vtt 8KB
  186. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/001 What is the Monte-Carlo method_en.vtt 8KB
  187. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/003 What are array data structures I_en.vtt 8KB
  188. ~Get Your Files Here !/05 - Gauss Elimination Implementation/002 Gaussian elimination implementation II_en.vtt 8KB
  189. ~Get Your Files Here !/21 - Appendix #6 - Pandas/010 Using the apply() function_en.vtt 8KB
  190. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/001 What is gradient descent_en.vtt 8KB
  191. ~Get Your Files Here !/21 - Appendix #6 - Pandas/001 What is Pandas_en.vtt 8KB
  192. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/002 Gaussian elimination illustration_en.vtt 8KB
  193. ~Get Your Files Here !/11 - Numerical Integration/004 Trapezoidal integral introduction_en.vtt 8KB
  194. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/004 Speed consideration - C, Java and Python_en.vtt 8KB
  195. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/007 What is ADAGrad_en.vtt 8KB
  196. ~Get Your Files Here !/21 - Appendix #6 - Pandas/012 What is vectorization_en.vtt 8KB
  197. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/005 String slicing_en.vtt 7KB
  198. ~Get Your Files Here !/20 - Appendix #5 - NumPy/007 Stacking and merging arrays_en.vtt 7KB
  199. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/003 What is pivoting_en.vtt 7KB
  200. ~Get Your Files Here !/09 - Interpolation/003 Interpolation implementation I_en.vtt 7KB
  201. ~Get Your Files Here !/13 - Differential Equations/002 Euler's method introduction_en.vtt 7KB
  202. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/011 Loops - for loop_en.vtt 7KB
  203. ~Get Your Files Here !/13 - Differential Equations/007 Runge-Kutta method example I_en.vtt 7KB
  204. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/001 What is Gaussian elimination_en.vtt 7KB
  205. ~Get Your Files Here !/11 - Numerical Integration/003 Rectangle method implementation_en.vtt 7KB
  206. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/003 Using the constructor_en.vtt 7KB
  207. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/011 Modules_en.vtt 7KB
  208. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/003 The original formula_en.vtt 7KB
  209. ~Get Your Files Here !/09 - Interpolation/002 Interpolation illustration_en.vtt 7KB
  210. ~Get Your Files Here !/21 - Appendix #6 - Pandas/008 Operations_en.vtt 7KB
  211. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/001 Graph representation of the WWW_en.vtt 7KB
  212. ~Get Your Files Here !/21 - Appendix #6 - Pandas/007 Reading CSV and text files_en.vtt 6KB
  213. ~Get Your Files Here !/10 - Root Finding/003 Bisection method implementation_en.vtt 6KB
  214. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/001 First steps in Python_en.vtt 6KB
  215. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/005 Lists in Python_en.vtt 6KB
  216. ~Get Your Files Here !/03 - Linear Algebra/002 Matrix multiplication implementation_en.vtt 6KB
  217. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/006 Stochastic gradient descent implementation II_en.vtt 6KB
  218. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/009 Power method_en.vtt 6KB
  219. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/013 Doubly linked list implementation in Python_en.vtt 6KB
  220. ~Get Your Files Here !/17 - Appendix #2 - Functions/002 Defining functions_en.vtt 6KB
  221. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/007 Lists in Python - list comprehension_en.vtt 6KB
  222. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/015 Break and continue_en.vtt 6KB
  223. ~Get Your Files Here !/21 - Appendix #6 - Pandas/004 DataFrames_en.vtt 6KB
  224. ~Get Your Files Here !/13 - Differential Equations/003 Euler's method example_en.vtt 6KB
  225. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/010 Polymorphism and abstraction example_en.vtt 6KB
  226. ~Get Your Files Here !/11 - Numerical Integration/007 Simpson's method implementation_en.vtt 6KB
  227. ~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/001 What are eigenvalues and eigenvectors_en.vtt 6KB
  228. ~Get Your Files Here !/11 - Numerical Integration/002 Rectangle method introduction_en.vtt 6KB
  229. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/007 Operators_en.vtt 6KB
  230. ~Get Your Files Here !/21 - Appendix #6 - Pandas/013 Vectorization example I_en.vtt 6KB
  231. ~Get Your Files Here !/17 - Appendix #2 - Functions/006 Yield operator_en.vtt 6KB
  232. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/006 The random surfer model_en.vtt 6KB
  233. ~Get Your Files Here !/11 - Numerical Integration/006 Simpson's method introduction_en.vtt 6KB
  234. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/002 What are the basic data types_en.vtt 6KB
  235. ~Get Your Files Here !/03 - Linear Algebra/003 Running time analysis of matrix multiplication_en.vtt 6KB
  236. ~Get Your Files Here !/09 - Interpolation/004 Interpolation implementation II_en.vtt 5KB
  237. ~Get Your Files Here !/11 - Numerical Integration/005 Trapezoidal integral implementation_en.vtt 5KB
  238. ~Get Your Files Here !/10 - Root Finding/004 Newton method introduction_en.vtt 5KB
  239. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/011 Mutability and immutability_en.vtt 5KB
  240. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/009 What is polymorphism_en.vtt 5KB
  241. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/010 ADAM optimizer introduction_en.vtt 5KB
  242. ~Get Your Files Here !/17 - Appendix #2 - Functions/001 What are functions_en.vtt 5KB
  243. ~Get Your Files Here !/03 - Linear Algebra/006 Lists and NumPy arrays_en.vtt 5KB
  244. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/005 Private variables and name mangling_en.vtt 5KB
  245. ~Get Your Files Here !/03 - Linear Algebra/001 Matrix multiplication introduction_en.vtt 5KB
  246. ~Get Your Files Here !/13 - Differential Equations/006 Runge-Kutta method introduction_en.vtt 5KB
  247. ~Get Your Files Here !/20 - Appendix #5 - NumPy/001 What is the key advantage of NumPy_en.vtt 5KB
  248. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/003 Monte-Carlo integral implementation II_en.vtt 5KB
  249. ~Get Your Files Here !/20 - Appendix #5 - NumPy/005 Types_en.vtt 5KB
  250. ~Get Your Files Here !/17 - Appendix #2 - Functions/007 What are the most relevant built-in functions_en.vtt 5KB
  251. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/007 The super keyword_en.vtt 5KB
  252. ~Get Your Files Here !/21 - Appendix #6 - Pandas/006 Speed comparison - DataFrame operations_en.vtt 5KB
  253. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/004 Class variables and instance variables_en.vtt 5KB
  254. ~Get Your Files Here !/13 - Differential Equations/008 Runge-Kutta method example II_en.vtt 5KB
  255. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/012 Loops - while loop_en.vtt 5KB
  256. ~Get Your Files Here !/03 - Linear Algebra/005 Inner product_en.vtt 5KB
  257. ~Get Your Files Here !/10 - Root Finding/002 Bisection method introduction_en.vtt 5KB
  258. ~Get Your Files Here !/17 - Appendix #2 - Functions/009 Local vs global variables_en.vtt 5KB
  259. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/003 Gradient descent with momentum_en.vtt 5KB
  260. ~Get Your Files Here !/10 - Root Finding/005 Newton method implementation_en.vtt 5KB
  261. ~Get Your Files Here !/13 - Differential Equations/005 Euler's method example - pendulum with drag_en.vtt 5KB
  262. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/006 Type casting_en.vtt 5KB
  263. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/003 Rounding errors_en.vtt 5KB
  264. ~Get Your Files Here !/03 - Linear Algebra/004 Matrix vector multiplication_en.vtt 5KB
  265. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/008 Conditional statements_en.vtt 5KB
  266. ~Get Your Files Here !/03 - Linear Algebra/007 Matrix operations with NumPy_en.vtt 5KB
  267. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/014 Enumerate_en.vtt 4KB
  268. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/010 What are tuples_en.vtt 4KB
  269. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/009 What is RMSProp_en.vtt 4KB
  270. ~Get Your Files Here !/20 - Appendix #5 - NumPy/008 Filter_en.vtt 4KB
  271. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/006 What is inheritance in OOP_en.vtt 4KB
  272. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/007 What are the problems with the random surfer model_en.vtt 4KB
  273. ~Get Your Files Here !/10 - Root Finding/001 Root of functions introduction_en.vtt 4KB
  274. ~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/001 Portfolio optimization introduction_en.vtt 4KB
  275. ~Get Your Files Here !/17 - Appendix #2 - Functions/010 The __main__ function_en.vtt 4KB
  276. ~Get Your Files Here !/21 - Appendix #6 - Pandas/014 Vectorization example II_en.vtt 4KB
  277. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/004 Gaussian elimination and singular matrixes_en.vtt 4KB
  278. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/002 Data structures introduction_en.vtt 4KB
  279. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/010 Logical operators_en.vtt 4KB
  280. ~Get Your Files Here !/11 - Numerical Integration/001 Integration introduction_en.vtt 4KB
  281. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/012 The __str__ function_en.vtt 4KB
  282. ~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/002 Eigenvalues and eigenvectors implementation_en.vtt 4KB
  283. ~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/002 Precision and accuracy_en.vtt 3KB
  284. ~Get Your Files Here !/21 - Appendix #6 - Pandas/002 First steps_en.vtt 3KB
  285. ~Get Your Files Here !/17 - Appendix #2 - Functions/005 Returning multiple values_en.vtt 3KB
  286. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/004 Applications of Monte-Carlo simulations in finance_en.vtt 3KB
  287. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/002 Class and objects basics_en.vtt 3KB
  288. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/013 What are nested loops_en.vtt 3KB
  289. ~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/002 Portfolio optimization implementation_en.vtt 3KB
  290. ~Get Your Files Here !/21 - Appendix #6 - Pandas/011 Speed comparison - loops and apply()_en.vtt 3KB
  291. ~Get Your Files Here !/09 - Interpolation/005 Applications of interpolation_en.vtt 3KB
  292. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/016 Calculating Fibonacci-numbers_en.vtt 3KB
  293. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/001 What is object oriented programming (OOP)_en.vtt 3KB
  294. ~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/008 Function (method) override_en.vtt 3KB
  295. ~Get Your Files Here !/17 - Appendix #2 - Functions/004 Returning values_en.vtt 3KB
  296. ~Get Your Files Here !/01 - Introduction/001 Introduction_en.vtt 2KB
  297. ~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/003 Applications of eigenvectors in machine learning_en.vtt 2KB
  298. ~Get Your Files Here !/16 - Appendix #1 - Python Basics/003 Booleans_en.vtt 2KB
  299. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/006 StochasticGradientDescentRegression.py 2KB
  300. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/StochasticGradientDescentRegression.py 2KB
  301. ~Get Your Files Here !/09 - Interpolation/004 LagrangeInterpolation.py 2KB
  302. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/LagrangeInterpolation.py 2KB
  303. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/005 StochasticGradientDescent.py 2KB
  304. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/StochasticGradientDescent.py 2KB
  305. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/008 GradientDescentAdaGrad.py 2KB
  306. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GradientDescentAdaGrad.py 2KB
  307. ~Get Your Files Here !/20 - Appendix #5 - NumPy/009 Running time comparison arrays and lists.html 1KB
  308. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GradientDescentMomentum.py 1KB
  309. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/002 GradientDescent.py 1KB
  310. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GradientDescent.py 1KB
  311. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/009 Measuring running time of lists.html 1KB
  312. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/002 MonteCarloIntegral.py 1KB
  313. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MonteCarloIntegral.py 1KB
  314. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/011 ADAM.py 1KB
  315. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/ADAM.py 1KB
  316. ~Get Your Files Here !/05 - Gauss Elimination Implementation/002 GaussElimination.py 838B
  317. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GaussElimination.py 838B
  318. ~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/003 MonteCarloIntegral2.py 676B
  319. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MonteCarloIntegral2.py 676B
  320. ~Get Your Files Here !/13 - Differential Equations/008 RungeKuttaExample2.py 663B
  321. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/RungeKuttaExample2.py 663B
  322. ~Get Your Files Here !/13 - Differential Equations/007 RungeKuttaExample1.py 648B
  323. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/RungeKuttaExample1.py 648B
  324. ~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/008 (!!!) Python lists and arrays.html 628B
  325. ~Get Your Files Here !/11 - Numerical Integration/007 SimpsonMethod.py 511B
  326. ~Get Your Files Here !/03 - Linear Algebra/002 MatrixMultiplication.py 496B
  327. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MatrixMultiplication.py 496B
  328. ~Get Your Files Here !/11 - Numerical Integration/005 TrapezoidalIntegral.py 468B
  329. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/TrapezoidalIntegral.py 468B
  330. ~Get Your Files Here !/13 - Differential Equations/003 EulerMethodExample1.py 449B
  331. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EulerMethodExample1.py 449B
  332. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EulerMethodExample3.py 449B
  333. ~Get Your Files Here !/15 - ### APPENDIX - PYTHON PROGRAMMING CRASH COURSE ###/001 Python crash course introduction.html 441B
  334. ~Get Your Files Here !/03 - Linear Algebra/004 MatrixVectorMultiplication.py 423B
  335. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MatrixVectorMultiplication.py 423B
  336. ~Get Your Files Here !/13 - Differential Equations/004 EulerMethodExample2.py 421B
  337. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EulerMethodExample2.py 421B
  338. ~Get Your Files Here !/03 - Linear Algebra/005 InnerProduct.py 386B
  339. ~Get Your Files Here !/Bonus Resources.txt 386B
  340. ~Get Your Files Here !/11 - Numerical Integration/003 RectangleIntegral.py 376B
  341. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/RectangleIntegral.py 376B
  342. ~Get Your Files Here !/10 - Root Finding/003 BisectionMethod.py 360B
  343. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/BisectionMethod.py 360B
  344. ~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/005 Mathematical formulation of Gaussian elimination.html 345B
  345. ~Get Your Files Here !/10 - Root Finding/005 NewtonRaphsonMethod.py 294B
  346. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/NewtonRaphsonMethod.py 294B
  347. ~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/012 Mathematical formulation of optimization algorithms in machine learning.html 275B
  348. ~Get Your Files Here !/10 - Root Finding/006 Mathematical formulation of root finding.html 271B
  349. ~Get Your Files Here !/09 - Interpolation/006 Mathematical formulation of interpolation.html 265B
  350. ~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/004 Mathematical formulation of eigenvectors.html 261B
  351. ~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/010 Original scientific paper of PageRank algorithm.html 254B
  352. ~Get Your Files Here !/13 - Differential Equations/009 Mathematical formulation of numerical differentiation.html 251B
  353. ~Get Your Files Here !/11 - Numerical Integration/008 Mathematical formulation of numerical integration.html 245B
  354. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/NumPyOperations.py 224B
  355. Get Bonus Downloads Here.url 182B
  356. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EigenvectorExample.py 117B
  357. ~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/001 Course material.html 58B