|
Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
|
| [TGx]Downloaded from torrentgalaxy.to .txt |
585B |
| 0 |
177.41KB |
| 001 Course material.html |
58B |
| 001 First steps in Python_en.vtt |
6.43KB |
| 001 First steps in Python.mp4 |
13.67MB |
| 001 Floating point numbers_en.vtt |
9.14KB |
| 001 Floating point numbers.mp4 |
24.48MB |
| 001 Gaussian elimination implementation I_en.vtt |
11.52KB |
| 001 Gaussian elimination implementation I.mp4 |
35.67MB |
| 001 Graph representation of the WWW_en.vtt |
6.51KB |
| 001 Graph representation of the WWW.mp4 |
25.06MB |
| 001 How to deal with differential equations_en.vtt |
9.79KB |
| 001 How to deal with differential equations.mp4 |
24.50MB |
| 001 How to measure the running time of algorithms_en.vtt |
12.61KB |
| 001 How to measure the running time of algorithms.mp4 |
37.29MB |
| 001 Integration introduction_en.vtt |
3.81KB |
| 001 Integration introduction.mp4 |
10.91MB |
| 001 Introduction_en.vtt |
2.44KB |
| 001 Introduction.mp4 |
13.60MB |
| 001 Matrix multiplication introduction_en.vtt |
5.06KB |
| 001 Matrix multiplication introduction.mp4 |
12.46MB |
| 001 numerical-methods.zip |
3.32MB |
| 001 Portfolio optimization introduction_en.vtt |
4.03KB |
| 001 Portfolio optimization introduction.mp4 |
13.13MB |
| 001 Python crash course introduction.html |
441B |
| 001 Root of functions introduction_en.vtt |
4.06KB |
| 001 Root of functions introduction.mp4 |
12.28MB |
| 001 What are eigenvalues and eigenvectors_en.vtt |
5.95KB |
| 001 What are eigenvalues and eigenvectors.mp4 |
14.38MB |
| 001 What are functions_en.vtt |
5.22KB |
| 001 What are functions.mp4 |
17.29MB |
| 001 What is Gaussian elimination_en.vtt |
6.82KB |
| 001 What is Gaussian elimination.mp4 |
16.82MB |
| 001 What is gradient descent_en.vtt |
7.90KB |
| 001 What is gradient descent.mp4 |
27.80MB |
| 001 What is interpolation_en.vtt |
10.79KB |
| 001 What is interpolation.mp4 |
38.72MB |
| 001 What is object oriented programming (OOP)_en.vtt |
2.86KB |
| 001 What is object oriented programming (OOP).mp4 |
12.50MB |
| 001 What is Pandas_en.vtt |
7.88KB |
| 001 What is Pandas.mp4 |
25.43MB |
| 001 What is the key advantage of NumPy_en.vtt |
5.01KB |
| 001 What is the key advantage of NumPy.mp4 |
17.18MB |
| 001 What is the Monte-Carlo method_en.vtt |
8.15KB |
| 001 What is the Monte-Carlo method.mp4 |
30.11MB |
| 002 Bisection method introduction_en.vtt |
4.78KB |
| 002 Bisection method introduction.mp4 |
10.17MB |
| 002 Class and objects basics_en.vtt |
3.25KB |
| 002 Class and objects basics.mp4 |
10.48MB |
| 002 Crawling the web with breadth-first search_en.vtt |
8.30KB |
| 002 Crawling the web with breadth-first search.mp4 |
25.88MB |
| 002 Creating and updating arrays_en.vtt |
8.47KB |
| 002 Creating and updating arrays.mp4 |
33.76MB |
| 002 Data structures introduction_en.vtt |
3.98KB |
| 002 Data structures introduction.mp4 |
13.84MB |
| 002 Defining functions_en.vtt |
6.14KB |
| 002 Defining functions.mp4 |
18.85MB |
| 002 Eigenvalues and eigenvectors implementation_en.vtt |
3.51KB |
| 002 Eigenvalues and eigenvectors implementation.mp4 |
10.84MB |
| 002 Euler's method introduction_en.vtt |
7.02KB |
| 002 Euler's method introduction.mp4 |
12.94MB |
| 002 First steps_en.vtt |
3.40KB |
| 002 First steps.mp4 |
10.44MB |
| 002 GaussElimination.py |
838B |
| 002 Gaussian elimination illustration_en.vtt |
7.85KB |
| 002 Gaussian elimination illustration.mp4 |
13.62MB |
| 002 Gaussian elimination implementation II_en.vtt |
8.01KB |
| 002 Gaussian elimination implementation II.mp4 |
29.57MB |
| 002 GradientDescent.py |
1.26KB |
| 002 Gradient descent implementation_en.vtt |
11.30KB |
| 002 Gradient descent implementation.mp4 |
47.54MB |
| 002 Interpolation illustration_en.vtt |
6.65KB |
| 002 Interpolation illustration.mp4 |
15.11MB |
| 002 MatrixMultiplication.py |
496B |
| 002 Matrix multiplication implementation_en.vtt |
6.41KB |
| 002 Matrix multiplication implementation.mp4 |
20.57MB |
| 002 MonteCarloIntegral.py |
1.15KB |
| 002 Monte-Carlo integral implementation I_en.vtt |
9.51KB |
| 002 Monte-Carlo integral implementation I.mp4 |
39.77MB |
| 002 Portfolio optimization implementation_en.vtt |
3.01KB |
| 002 Portfolio optimization implementation.mp4 |
13.84MB |
| 002 Precision and accuracy_en.vtt |
3.46KB |
| 002 Precision and accuracy.mp4 |
9.44MB |
| 002 Rectangle method introduction_en.vtt |
5.92KB |
| 002 Rectangle method introduction.mp4 |
18.05MB |
| 002 What are the basic data types_en.vtt |
5.59KB |
| 002 What are the basic data types.mp4 |
15.70MB |
| 003 Applications of eigenvectors in machine learning_en.vtt |
2.22KB |
| 003 Applications of eigenvectors in machine learning.mp4 |
10.65MB |
| 003 BisectionMethod.py |
360B |
| 003 Bisection method implementation_en.vtt |
6.44KB |
| 003 Bisection method implementation.mp4 |
24.12MB |
| 003 Booleans_en.vtt |
2.21KB |
| 003 Booleans.mp4 |
6.78MB |
| 003 Dimension of arrays_en.vtt |
10.65KB |
| 003 Dimension of arrays.mp4 |
36.26MB |
| 003 Euler's method example_en.vtt |
6.06KB |
| 003 Euler's method example.mp4 |
19.65MB |
| 003 EulerMethodExample1.py |
449B |
| 003 Gradient descent with momentum_en.vtt |
4.71KB |
| 003 Gradient descent with momentum.mp4 |
20.02MB |
| 003 Interpolation implementation I_en.vtt |
7.22KB |
| 003 Interpolation implementation I.mp4 |
26.13MB |
| 003 MonteCarloIntegral2.py |
676B |
| 003 Monte-Carlo integral implementation II_en.vtt |
5.00KB |
| 003 Monte-Carlo integral implementation II.mp4 |
24.52MB |
| 003 Positional arguments and keyword arguments_en.vtt |
11.69KB |
| 003 Positional arguments and keyword arguments.mp4 |
46.11MB |
| 003 RectangleIntegral.py |
376B |
| 003 Rectangle method implementation_en.vtt |
6.82KB |
| 003 Rectangle method implementation.mp4 |
22.38MB |
| 003 Rounding errors_en.vtt |
4.65KB |
| 003 Rounding errors.mp4 |
14.12MB |
| 003 Running time analysis of matrix multiplication_en.vtt |
5.56KB |
| 003 Running time analysis of matrix multiplication.mp4 |
27.04MB |
| 003 Series_en.vtt |
8.16KB |
| 003 Series.mp4 |
26.94MB |
| 003 The original formula_en.vtt |
6.69KB |
| 003 The original formula.mp4 |
17.78MB |
| 003 Using the constructor_en.vtt |
6.79KB |
| 003 Using the constructor.mp4 |
33.59MB |
| 003 What are array data structures I_en.vtt |
8.05KB |
| 003 What are array data structures I.mp4 |
24.99MB |
| 003 What is pivoting_en.vtt |
7.25KB |
| 003 What is pivoting.mp4 |
19.76MB |
| 004 Applications of Monte-Carlo simulations in finance_en.vtt |
3.29KB |
| 004 Applications of Monte-Carlo simulations in finance.mp4 |
14.29MB |
| 004 Class variables and instance variables_en.vtt |
4.91KB |
| 004 Class variables and instance variables.mp4 |
31.01MB |
| 004 DataFrames_en.vtt |
6.08KB |
| 004 DataFrames.mp4 |
18.45MB |
| 004 Euler's method example - pendulum_en.vtt |
12.94KB |
| 004 Euler's method example - pendulum.mp4 |
34.00MB |
| 004 EulerMethodExample2.py |
421B |
| 004 Gaussian elimination and singular matrixes_en.vtt |
4.01KB |
| 004 Gaussian elimination and singular matrixes.mp4 |
8.69MB |
| 004 Indexes and slicing_en.vtt |
9.38KB |
| 004 Indexes and slicing.mp4 |
31.50MB |
| 004 Interpolation implementation II_en.vtt |
5.50KB |
| 004 Interpolation implementation II.mp4 |
30.85MB |
| 004 LagrangeInterpolation.py |
2.12KB |
| 004 Mathematical formulation of eigenvectors.html |
261B |
| 004 Matrix vector multiplication_en.vtt |
4.65KB |
| 004 Matrix vector multiplication.mp4 |
13.41MB |
| 004 MatrixVectorMultiplication.py |
423B |
| 004 Newton method introduction_en.vtt |
5.28KB |
| 004 Newton method introduction.mp4 |
16.40MB |
| 004 PageRank algorithm example_en.vtt |
11.20KB |
| 004 PageRank algorithm example.mp4 |
24.94MB |
| 004 Returning values_en.vtt |
2.71KB |
| 004 Returning values.mp4 |
8.14MB |
| 004 Speed consideration - C, Java and Python_en.vtt |
7.64KB |
| 004 Speed consideration - C, Java and Python.mp4 |
27.51MB |
| 004 Stochastic gradient descent introduction_en.vtt |
11.84KB |
| 004 Stochastic gradient descent introduction.mp4 |
36.45MB |
| 004 Strings_en.vtt |
8.77KB |
| 004 Strings.mp4 |
28.16MB |
| 004 Trapezoidal integral introduction_en.vtt |
7.74KB |
| 004 Trapezoidal integral introduction.mp4 |
19.06MB |
| 004 What are array data structures II_en.vtt |
8.60KB |
| 004 What are array data structures II.mp4 |
24.95MB |
| 005 Applications of interpolation_en.vtt |
2.90KB |
| 005 Applications of interpolation.mp4 |
8.61MB |
| 005 DataFrame operations_en.vtt |
10.85KB |
| 005 DataFrame operations.mp4 |
41.30MB |
| 005 Euler's method example - pendulum with drag_en.vtt |
4.67KB |
| 005 Euler's method example - pendulum with drag.mp4 |
16.15MB |
| 005 Inner product_en.vtt |
4.86KB |
| 005 Inner product.mp4 |
16.56MB |
| 005 InnerProduct.py |
386B |
| 005 Lists in Python_en.vtt |
6.42KB |
| 005 Lists in Python.mp4 |
21.74MB |
| 005 Mathematical formulation of Gaussian elimination.html |
345B |
| 005 Matrix representation of the problem_en.vtt |
9.77KB |
| 005 Matrix representation of the problem.mp4 |
29.07MB |
| 005 Newton method implementation_en.vtt |
4.70KB |
| 005 Newton method implementation.mp4 |
15.79MB |
| 005 NewtonRaphsonMethod.py |
294B |
| 005 Private variables and name mangling_en.vtt |
5.08KB |
| 005 Private variables and name mangling.mp4 |
19.13MB |
| 005 Returning multiple values_en.vtt |
3.37KB |
| 005 Returning multiple values.mp4 |
12.17MB |
| 005 StochasticGradientDescent.py |
1.93KB |
| 005 Stochastic gradient descent implementation I_en.vtt |
24.44KB |
| 005 Stochastic gradient descent implementation I.mp4 |
105.86MB |
| 005 String slicing_en.vtt |
7.44KB |
| 005 String slicing.mp4 |
25.08MB |
| 005 TrapezoidalIntegral.py |
468B |
| 005 Trapezoidal integral implementation_en.vtt |
5.33KB |
| 005 Trapezoidal integral implementation.mp4 |
17.61MB |
| 005 Types_en.vtt |
4.95KB |
| 005 Types.mp4 |
19.29MB |
| 006 Lists and NumPy arrays_en.vtt |
5.14KB |
| 006 Lists and NumPy arrays.mp4 |
19.40MB |
| 006 Lists in Python - advanced operations_en.vtt |
8.71KB |
| 006 Lists in Python - advanced operations.mp4 |
39.32MB |
| 006 Mathematical formulation of interpolation.html |
265B |
| 006 Mathematical formulation of root finding.html |
271B |
| 006 Reshape_en.vtt |
8.85KB |
| 006 Reshape.mp4 |
33.84MB |
| 006 Runge-Kutta method introduction_en.vtt |
5.03KB |
| 006 Runge-Kutta method introduction.mp4 |
14.24MB |
| 006 Simpson's method introduction_en.vtt |
5.64KB |
| 006 Simpson's method introduction.mp4 |
11.99MB |
| 006 Speed comparison - DataFrame operations_en.vtt |
4.91KB |
| 006 Speed comparison - DataFrame operations.mp4 |
28.65MB |
| 006 Stochastic gradient descent implementation II_en.vtt |
6.37KB |
| 006 Stochastic gradient descent implementation II.mp4 |
41.23MB |
| 006 StochasticGradientDescentRegression.py |
2.17KB |
| 006 The random surfer model_en.vtt |
5.66KB |
| 006 The random surfer model.mp4 |
18.81MB |
| 006 Type casting_en.vtt |
4.66KB |
| 006 Type casting.mp4 |
16.74MB |
| 006 What is inheritance in OOP_en.vtt |
4.14KB |
| 006 What is inheritance in OOP.mp4 |
18.03MB |
| 006 Yield operator_en.vtt |
5.77KB |
| 006 Yield operator.mp4 |
18.28MB |
| 007 Lists in Python - list comprehension_en.vtt |
6.12KB |
| 007 Lists in Python - list comprehension.mp4 |
22.88MB |
| 007 Matrix operations with NumPy_en.vtt |
4.54KB |
| 007 Matrix operations with NumPy.mp4 |
13.69MB |
| 007 Operators_en.vtt |
5.88KB |
| 007 Operators.mp4 |
20.63MB |
| 007 Reading CSV and text files_en.vtt |
6.45KB |
| 007 Reading CSV and text files.mp4 |
35.23MB |
| 007 RungeKuttaExample1.py |
648B |
| 007 Runge-Kutta method example I_en.vtt |
6.92KB |
| 007 Runge-Kutta method example I.mp4 |
24.49MB |
| 007 Simpson's method implementation_en.vtt |
5.99KB |
| 007 Simpson's method implementation.mp4 |
20.56MB |
| 007 SimpsonMethod.py |
511B |
| 007 Stacking and merging arrays_en.vtt |
7.34KB |
| 007 Stacking and merging arrays.mp4 |
27.69MB |
| 007 The super keyword_en.vtt |
4.91KB |
| 007 The super keyword.mp4 |
21.23MB |
| 007 What are the most relevant built-in functions_en.vtt |
4.92KB |
| 007 What are the most relevant built-in functions.mp4 |
15.38MB |
| 007 What are the problems with the random surfer model_en.vtt |
4.08KB |
| 007 What are the problems with the random surfer model.mp4 |
12.26MB |
| 007 What is ADAGrad_en.vtt |
7.54KB |
| 007 What is ADAGrad.mp4 |
22.13MB |
| 008 (!!!) Python lists and arrays.html |
628B |
| 008 ADAGrad implementation_en.vtt |
13.63KB |
| 008 ADAGrad implementation.mp4 |
63.99MB |
| 008 Conditional statements_en.vtt |
4.63KB |
| 008 Conditional statements.mp4 |
17.81MB |
| 008 Filter_en.vtt |
4.22KB |
| 008 Filter.mp4 |
15.24MB |
| 008 Function (method) override_en.vtt |
2.71KB |
| 008 Function (method) override.mp4 |
18.17MB |
| 008 GradientDescentAdaGrad.py |
1.56KB |
| 008 Mathematical formulation of numerical integration.html |
245B |
| 008 Operations_en.vtt |
6.61KB |
| 008 Operations.mp4 |
32.93MB |
| 008 PageRank algorithm - the final formula_en.vtt |
8.93KB |
| 008 PageRank algorithm - the final formula.mp4 |
37.74MB |
| 008 RungeKuttaExample2.py |
663B |
| 008 Runge-Kutta method example II_en.vtt |
4.88KB |
| 008 Runge-Kutta method example II.mp4 |
22.20MB |
| 008 What is recursion_en.vtt |
10.64KB |
| 008 What is recursion.mp4 |
35.28MB |
| 009 Data filtering_en.vtt |
8.67KB |
| 009 Data filtering.mp4 |
27.06MB |
| 009 How to use multiple conditions_en.vtt |
9.05KB |
| 009 How to use multiple conditions.mp4 |
31.41MB |
| 009 Local vs global variables_en.vtt |
4.77KB |
| 009 Local vs global variables.mp4 |
15.01MB |
| 009 Mathematical formulation of numerical differentiation.html |
251B |
| 009 Measuring running time of lists.html |
1.24KB |
| 009 Power method_en.vtt |
6.30KB |
| 009 Power method.mp4 |
21.32MB |
| 009 Running time comparison arrays and lists.html |
1.34KB |
| 009 What is polymorphism_en.vtt |
5.25KB |
| 009 What is polymorphism.mp4 |
21.16MB |
| 009 What is RMSProp_en.vtt |
4.31KB |
| 009 What is RMSProp.mp4 |
19.12MB |
| 010 ADAM optimizer introduction_en.vtt |
5.23KB |
| 010 ADAM optimizer introduction.mp4 |
12.31MB |
| 010 Logical operators_en.vtt |
3.97KB |
| 010 Logical operators.mp4 |
17.60MB |
| 010 Original scientific paper of PageRank algorithm.html |
254B |
| 010 Polymorphism and abstraction example_en.vtt |
6.03KB |
| 010 Polymorphism and abstraction example.mp4 |
33.27MB |
| 010 The __main__ function_en.vtt |
4.02KB |
| 010 The __main__ function.mp4 |
14.81MB |
| 010 Using the apply() function_en.vtt |
7.95KB |
| 010 Using the apply() function.mp4 |
30.85MB |
| 010 What are tuples_en.vtt |
4.32KB |
| 010 What are tuples.mp4 |
14.73MB |
| 011 ADAM.py |
1.07KB |
| 011 ADAM optimizer implementation_en.vtt |
10.18KB |
| 011 ADAM optimizer implementation.mp4 |
43.02MB |
| 011 Loops - for loop_en.vtt |
6.92KB |
| 011 Loops - for loop.mp4 |
18.95MB |
| 011 Modules_en.vtt |
6.71KB |
| 011 Modules.mp4 |
21.79MB |
| 011 Mutability and immutability_en.vtt |
5.25KB |
| 011 Mutability and immutability.mp4 |
18.49MB |
| 011 Speed comparison - loops and apply()_en.vtt |
2.97KB |
| 011 Speed comparison - loops and apply().mp4 |
17.77MB |
| 012 Loops - while loop_en.vtt |
4.88KB |
| 012 Loops - while loop.mp4 |
14.41MB |
| 012 Mathematical formulation of optimization algorithms in machine learning.html |
275B |
| 012 The __str__ function_en.vtt |
3.51KB |
| 012 The __str__ function.mp4 |
15.67MB |
| 012 What are linked list data structures_en.vtt |
10.30KB |
| 012 What are linked list data structures.mp4 |
34.49MB |
| 012 What is vectorization_en.vtt |
7.52KB |
| 012 What is vectorization.mp4 |
26.44MB |
| 013 Comparing objects - overriding functions_en.vtt |
9.05KB |
| 013 Comparing objects - overriding functions.mp4 |
40.18MB |
| 013 Doubly linked list implementation in Python_en.vtt |
6.19KB |
| 013 Doubly linked list implementation in Python.mp4 |
24.46MB |
| 013 Vectorization example I_en.vtt |
5.80KB |
| 013 Vectorization example I.mp4 |
22.18MB |
| 013 What are nested loops_en.vtt |
3.03KB |
| 013 What are nested loops.mp4 |
13.16MB |
| 014 Enumerate_en.vtt |
4.34KB |
| 014 Enumerate.mp4 |
15.13MB |
| 014 Hashing and O(1) running time complexity_en.vtt |
9.73KB |
| 014 Hashing and O(1) running time complexity.mp4 |
30.98MB |
| 014 Vectorization example II_en.vtt |
4.01KB |
| 014 Vectorization example II.mp4 |
20.81MB |
| 015 Break and continue_en.vtt |
6.12KB |
| 015 Break and continue.mp4 |
20.42MB |
| 015 Dictionaries in Python_en.vtt |
10.69KB |
| 015 Dictionaries in Python.mp4 |
38.50MB |
| 016 Calculating Fibonacci-numbers_en.vtt |
2.89KB |
| 016 Calculating Fibonacci-numbers.mp4 |
8.39MB |
| 016 Sets in Python_en.vtt |
9.56KB |
| 016 Sets in Python.mp4 |
47.14MB |
| 017 Sorting_en.vtt |
11.36KB |
| 017 Sorting.mp4 |
50.57MB |
| 1 |
7.68KB |
| 10 |
238.65KB |
| 100 |
268.04KB |
| 101 |
445.67KB |
| 102 |
610.49KB |
| 103 |
870.96KB |
| 104 |
216.45KB |
| 105 |
303.08KB |
| 106 |
342.87KB |
| 107 |
631.51KB |
| 108 |
775.21KB |
| 109 |
890.63KB |
| 11 |
700.64KB |
| 110 |
916.34KB |
| 111 |
1010.14KB |
| 112 |
192.06KB |
| 113 |
272.17KB |
| 114 |
602.90KB |
| 115 |
630.29KB |
| 116 |
723.50KB |
| 117 |
781.36KB |
| 118 |
897.22KB |
| 119 |
159.66KB |
| 12 |
283.49KB |
| 120 |
166.66KB |
| 121 |
322.53KB |
| 122 |
334.24KB |
| 123 |
394.00KB |
| 124 |
412.63KB |
| 125 |
601.41KB |
| 126 |
859.28KB |
| 127 |
893.74KB |
| 128 |
65.45KB |
| 129 |
507.11KB |
| 13 |
514.48KB |
| 130 |
549.13KB |
| 131 |
705.96KB |
| 132 |
736.87KB |
| 133 |
757.84KB |
| 134 |
854.11KB |
| 135 |
6.56KB |
| 136 |
88.44KB |
| 137 |
166.89KB |
| 138 |
361.49KB |
| 139 |
534.63KB |
| 14 |
269.43KB |
| 140 |
576.44KB |
| 141 |
852.17KB |
| 142 |
570.53KB |
| 143 |
313.11KB |
| 144 |
397.36KB |
| 145 |
629.68KB |
| 146 |
878.43KB |
| 147 |
223.38KB |
| 15 |
725.00KB |
| 16 |
565.20KB |
| 17 |
758.07KB |
| 18 |
333.49KB |
| 19 |
736.68KB |
| 2 |
439.31KB |
| 20 |
791.46KB |
| 21 |
519.93KB |
| 22 |
1.37KB |
| 23 |
165.90KB |
| 24 |
249.93KB |
| 25 |
415.81KB |
| 26 |
745.27KB |
| 27 |
66.72KB |
| 28 |
507.74KB |
| 29 |
606.87KB |
| 3 |
467.51KB |
| 30 |
1015.52KB |
| 31 |
19.76KB |
| 32 |
150.11KB |
| 33 |
157.08KB |
| 34 |
908.71KB |
| 35 |
436.03KB |
| 36 |
957.38KB |
| 37 |
357.73KB |
| 38 |
863.20KB |
| 39 |
203.33KB |
| 4 |
876.14KB |
| 40 |
322.18KB |
| 41 |
503.59KB |
| 42 |
965.72KB |
| 43 |
983.40KB |
| 44 |
60.21KB |
| 45 |
572.82KB |
| 46 |
895.28KB |
| 47 |
121.95KB |
| 48 |
585.57KB |
| 49 |
946.66KB |
| 5 |
909.18KB |
| 50 |
966.75KB |
| 51 |
10.02KB |
| 52 |
48.42KB |
| 53 |
57.50KB |
| 54 |
491.74KB |
| 55 |
509.96KB |
| 56 |
523.84KB |
| 57 |
530.85KB |
| 58 |
555.95KB |
| 59 |
897.20KB |
| 6 |
1002.90KB |
| 60 |
119.26KB |
| 61 |
636.26KB |
| 62 |
815.62KB |
| 63 |
839.65KB |
| 64 |
892.19KB |
| 65 |
216.54KB |
| 66 |
270.71KB |
| 67 |
698.37KB |
| 68 |
786.84KB |
| 69 |
856.26KB |
| 7 |
714.47KB |
| 70 |
190.86KB |
| 71 |
381.88KB |
| 72 |
439.97KB |
| 73 |
450.23KB |
| 74 |
588.91KB |
| 75 |
1004.94KB |
| 76 |
247.27KB |
| 77 |
360.47KB |
| 78 |
609.89KB |
| 79 |
731.14KB |
| 8 |
792.56KB |
| 80 |
888.75KB |
| 81 |
902.11KB |
| 82 |
966.77KB |
| 83 |
53.55KB |
| 84 |
153.19KB |
| 85 |
193.41KB |
| 86 |
517.95KB |
| 87 |
564.75KB |
| 88 |
738.38KB |
| 89 |
851.35KB |
| 9 |
842.42KB |
| 90 |
971.07KB |
| 91 |
992.17KB |
| 92 |
195.45KB |
| 93 |
227.69KB |
| 94 |
237.17KB |
| 95 |
395.27KB |
| 96 |
411.36KB |
| 97 |
725.74KB |
| 98 |
844.08KB |
| 99 |
187.01KB |
| TutsNode.com.txt |
63B |