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Please note that this page does not hosts or makes available any of the listed filenames. You
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| 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 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 |
| ADAM.py |
1.07KB |
| BisectionMethod.py |
360B |
| Bonus Resources.txt |
386B |
| EigenvectorExample.py |
117B |
| EulerMethodExample1.py |
449B |
| EulerMethodExample2.py |
421B |
| EulerMethodExample3.py |
449B |
| GaussElimination.py |
838B |
| Get Bonus Downloads Here.url |
182B |
| GradientDescent.py |
1.26KB |
| GradientDescentAdaGrad.py |
1.56KB |
| GradientDescentMomentum.py |
1.29KB |
| house_prices.csv |
2.40MB |
| LagrangeInterpolation.py |
2.12KB |
| MatrixMultiplication.py |
496B |
| MatrixVectorMultiplication.py |
423B |
| MonteCarloIntegral.py |
1.15KB |
| MonteCarloIntegral2.py |
676B |
| NewtonRaphsonMethod.py |
294B |
| numerical_methods.pptx |
3.03MB |
| NumPyOperations.py |
224B |
| RectangleIntegral.py |
376B |
| RungeKuttaExample1.py |
648B |
| RungeKuttaExample2.py |
663B |
| StochasticGradientDescent.py |
1.93KB |
| StochasticGradientDescentRegression.py |
2.17KB |
| TrapezoidalIntegral.py |
468B |