magnet:?xt=urn:btih:42F3E1283060DE23236E319E113F7F6BCF88318D
~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/005 Stochastic gradient descent implementation I.mp4 111.0 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/008 ADAGrad implementation.mp4 67.1 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/017 Sorting.mp4 53.0 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/002 Gradient descent implementation.mp4 49.9 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/016 Sets in Python.mp4 49.4 MB~Get Your Files Here !/17 - Appendix #2 - Functions/003 Positional arguments and keyword arguments.mp4 48.4 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/011 ADAM optimizer implementation.mp4 45.1 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/005 DataFrame operations.mp4 43.3 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/006 Stochastic gradient descent implementation II.mp4 43.2 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/013 Comparing objects - overriding functions.mp4 42.1 MB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/002 Monte-Carlo integral implementation I.mp4 41.7 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/006 Lists in Python - advanced operations.mp4 41.2 MB~Get Your Files Here !/09 - Interpolation/001 What is interpolation.mp4 40.6 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/015 Dictionaries in Python.mp4 40.4 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/008 PageRank algorithm - the final formula.mp4 39.6 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/001 How to measure the running time of algorithms.mp4 39.1 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/004 Stochastic gradient descent introduction.mp4 38.2 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/003 Dimension of arrays.mp4 38.0 MB~Get Your Files Here !/05 - Gauss Elimination Implementation/001 Gaussian elimination implementation I.mp4 37.4 MB~Get Your Files Here !/17 - Appendix #2 - Functions/008 What is recursion.mp4 37.0 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/007 Reading CSV and text files.mp4 36.9 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/012 What are linked list data structures.mp4 36.2 MB~Get Your Files Here !/13 - Differential Equations/004 Euler's method example - pendulum.mp4 35.7 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/006 Reshape.mp4 35.5 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/002 Creating and updating arrays.mp4 35.4 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/003 Using the constructor.mp4 35.2 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/010 Polymorphism and abstraction example.mp4 34.9 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/008 Operations.mp4 34.5 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/004 Indexes and slicing.mp4 33.0 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/009 How to use multiple conditions.mp4 32.9 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/004 Class variables and instance variables.mp4 32.5 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/014 Hashing and O(1) running time complexity.mp4 32.5 MB~Get Your Files Here !/09 - Interpolation/004 Interpolation implementation II.mp4 32.4 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/010 Using the apply() function.mp4 32.3 MB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/001 What is the Monte-Carlo method.mp4 31.6 MB~Get Your Files Here !/05 - Gauss Elimination Implementation/002 Gaussian elimination implementation II.mp4 31.0 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/005 Matrix representation of the problem.mp4 30.5 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/006 Speed comparison - DataFrame operations.mp4 30.0 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/004 Strings.mp4 29.5 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/001 What is gradient descent.mp4 29.2 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/007 Stacking and merging arrays.mp4 29.0 MB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/004 Speed consideration - C, Java and Python.mp4 28.8 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/009 Data filtering.mp4 28.4 MB~Get Your Files Here !/03 - Linear Algebra/003 Running time analysis of matrix multiplication.mp4 28.4 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/003 Series.mp4 28.2 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/012 What is vectorization.mp4 27.7 MB~Get Your Files Here !/09 - Interpolation/003 Interpolation implementation I.mp4 27.4 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/002 Crawling the web with breadth-first search.mp4 27.1 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/001 What is Pandas.mp4 26.7 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/005 String slicing.mp4 26.3 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/001 Graph representation of the WWW.mp4 26.3 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/003 What are array data structures I.mp4 26.2 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/004 What are array data structures II.mp4 26.2 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/004 PageRank algorithm example.mp4 26.2 MB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/003 Monte-Carlo integral implementation II.mp4 25.7 MB~Get Your Files Here !/13 - Differential Equations/001 How to deal with differential equations.mp4 25.7 MB~Get Your Files Here !/13 - Differential Equations/007 Runge-Kutta method example I.mp4 25.7 MB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/001 Floating point numbers.mp4 25.7 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/013 Doubly linked list implementation in Python.mp4 25.6 MB~Get Your Files Here !/10 - Root Finding/003 Bisection method implementation.mp4 25.3 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/007 Lists in Python - list comprehension.mp4 24.0 MB~Get Your Files Here !/11 - Numerical Integration/003 Rectangle method implementation.mp4 23.5 MB~Get Your Files Here !/13 - Differential Equations/008 Runge-Kutta method example II.mp4 23.3 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/013 Vectorization example I.mp4 23.3 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/007 What is ADAGrad.mp4 23.2 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/011 Modules.mp4 22.8 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/005 Lists in Python.mp4 22.8 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/009 Power method.mp4 22.4 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/007 The super keyword.mp4 22.3 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/009 What is polymorphism.mp4 22.2 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/014 Vectorization example II.mp4 21.8 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/007 Operators.mp4 21.6 MB~Get Your Files Here !/03 - Linear Algebra/002 Matrix multiplication implementation.mp4 21.6 MB~Get Your Files Here !/11 - Numerical Integration/007 Simpson's method implementation.mp4 21.6 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/015 Break and continue.mp4 21.4 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/003 Gradient descent with momentum.mp4 21.0 MB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/003 What is pivoting.mp4 20.7 MB~Get Your Files Here !/13 - Differential Equations/003 Euler's method example.mp4 20.6 MB~Get Your Files Here !/03 - Linear Algebra/006 Lists and NumPy arrays.mp4 20.3 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/005 Types.mp4 20.2 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/005 Private variables and name mangling.mp4 20.1 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/009 What is RMSProp.mp4 20.0 MB~Get Your Files Here !/11 - Numerical Integration/004 Trapezoidal integral introduction.mp4 20.0 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/011 Loops - for loop.mp4 19.9 MB~Get Your Files Here !/17 - Appendix #2 - Functions/002 Defining functions.mp4 19.8 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/006 The random surfer model.mp4 19.7 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/011 Mutability and immutability.mp4 19.4 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/004 DataFrames.mp4 19.3 MB~Get Your Files Here !/17 - Appendix #2 - Functions/006 Yield operator.mp4 19.2 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/008 Function (method) override.mp4 19.1 MB~Get Your Files Here !/11 - Numerical Integration/002 Rectangle method introduction.mp4 18.9 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/006 What is inheritance in OOP.mp4 18.9 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/008 Conditional statements.mp4 18.7 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/003 The original formula.mp4 18.6 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/011 Speed comparison - loops and apply().mp4 18.6 MB~Get Your Files Here !/11 - Numerical Integration/005 Trapezoidal integral implementation.mp4 18.5 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/010 Logical operators.mp4 18.5 MB~Get Your Files Here !/17 - Appendix #2 - Functions/001 What are functions.mp4 18.1 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/001 What is the key advantage of NumPy.mp4 18.0 MB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/001 What is Gaussian elimination.mp4 17.6 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/006 Type casting.mp4 17.6 MB~Get Your Files Here !/03 - Linear Algebra/005 Inner product.mp4 17.4 MB~Get Your Files Here !/10 - Root Finding/004 Newton method introduction.mp4 17.2 MB~Get Your Files Here !/13 - Differential Equations/005 Euler's method example - pendulum with drag.mp4 16.9 MB~Get Your Files Here !/10 - Root Finding/005 Newton method implementation.mp4 16.6 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/002 What are the basic data types.mp4 16.5 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/012 The __str__ function.mp4 16.4 MB~Get Your Files Here !/17 - Appendix #2 - Functions/007 What are the most relevant built-in functions.mp4 16.1 MB~Get Your Files Here !/20 - Appendix #5 - NumPy/008 Filter.mp4 16.0 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/014 Enumerate.mp4 15.9 MB~Get Your Files Here !/09 - Interpolation/002 Interpolation illustration.mp4 15.8 MB~Get Your Files Here !/17 - Appendix #2 - Functions/009 Local vs global variables.mp4 15.7 MB~Get Your Files Here !/17 - Appendix #2 - Functions/010 The __main__ function.mp4 15.5 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/010 What are tuples.mp4 15.4 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/012 Loops - while loop.mp4 15.1 MB~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/001 What are eigenvalues and eigenvectors.mp4 15.1 MB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/004 Applications of Monte-Carlo simulations in finance.mp4 15.0 MB~Get Your Files Here !/13 - Differential Equations/006 Runge-Kutta method introduction.mp4 14.9 MB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/003 Rounding errors.mp4 14.8 MB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/002 Data structures introduction.mp4 14.5 MB~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/002 Portfolio optimization implementation.mp4 14.5 MB~Get Your Files Here !/03 - Linear Algebra/007 Matrix operations with NumPy.mp4 14.3 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/001 First steps in Python.mp4 14.3 MB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/002 Gaussian elimination illustration.mp4 14.3 MB~Get Your Files Here !/01 - Introduction/001 Introduction.mp4 14.3 MB~Get Your Files Here !/03 - Linear Algebra/004 Matrix vector multiplication.mp4 14.1 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/013 What are nested loops.mp4 13.8 MB~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/001 Portfolio optimization introduction.mp4 13.8 MB~Get Your Files Here !/13 - Differential Equations/002 Euler's method introduction.mp4 13.6 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/001 What is object oriented programming (OOP).mp4 13.1 MB~Get Your Files Here !/03 - Linear Algebra/001 Matrix multiplication introduction.mp4 13.1 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/010 ADAM optimizer introduction.mp4 12.9 MB~Get Your Files Here !/10 - Root Finding/001 Root of functions introduction.mp4 12.9 MB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/007 What are the problems with the random surfer model.mp4 12.9 MB~Get Your Files Here !/17 - Appendix #2 - Functions/005 Returning multiple values.mp4 12.8 MB~Get Your Files Here !/11 - Numerical Integration/006 Simpson's method introduction.mp4 12.6 MB~Get Your Files Here !/11 - Numerical Integration/001 Integration introduction.mp4 11.4 MB~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/002 Eigenvalues and eigenvectors implementation.mp4 11.4 MB~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/003 Applications of eigenvectors in machine learning.mp4 11.2 MB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/002 Class and objects basics.mp4 11.0 MB~Get Your Files Here !/21 - Appendix #6 - Pandas/002 First steps.mp4 10.9 MB~Get Your Files Here !/10 - Root Finding/002 Bisection method introduction.mp4 10.7 MB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/002 Precision and accuracy.mp4 9.9 MB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/004 Gaussian elimination and singular matrixes.mp4 9.1 MB~Get Your Files Here !/09 - Interpolation/005 Applications of interpolation.mp4 9.0 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/016 Calculating Fibonacci-numbers.mp4 8.8 MB~Get Your Files Here !/17 - Appendix #2 - Functions/004 Returning values.mp4 8.5 MB~Get Your Files Here !/16 - Appendix #1 - Python Basics/003 Booleans.mp4 7.1 MB
~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/numerical_methods.pptx 3.2 MB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/house_prices.csv 2.5 MB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/005 Stochastic gradient descent implementation I_en.vtt 25.0 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/008 ADAGrad implementation_en.vtt 14.0 kB~Get Your Files Here !/13 - Differential Equations/004 Euler's method example - pendulum_en.vtt 13.3 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/001 How to measure the running time of algorithms_en.vtt 12.9 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/004 Stochastic gradient descent introduction_en.vtt 12.1 kB~Get Your Files Here !/17 - Appendix #2 - Functions/003 Positional arguments and keyword arguments_en.vtt 12.0 kB~Get Your Files Here !/05 - Gauss Elimination Implementation/001 Gaussian elimination implementation I_en.vtt 11.8 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/017 Sorting_en.vtt 11.6 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/002 Gradient descent implementation_en.vtt 11.6 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/004 PageRank algorithm example_en.vtt 11.5 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/005 DataFrame operations_en.vtt 11.1 kB~Get Your Files Here !/09 - Interpolation/001 What is interpolation_en.vtt 11.1 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/015 Dictionaries in Python_en.vtt 10.9 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/003 Dimension of arrays_en.vtt 10.9 kB~Get Your Files Here !/17 - Appendix #2 - Functions/008 What is recursion_en.vtt 10.9 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/012 What are linked list data structures_en.vtt 10.5 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/011 ADAM optimizer implementation_en.vtt 10.4 kB~Get Your Files Here !/13 - Differential Equations/001 How to deal with differential equations_en.vtt 10.0 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/005 Matrix representation of the problem_en.vtt 10.0 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/014 Hashing and O(1) running time complexity_en.vtt 10.0 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/016 Sets in Python_en.vtt 9.8 kB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/002 Monte-Carlo integral implementation I_en.vtt 9.7 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/004 Indexes and slicing_en.vtt 9.6 kB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/001 Floating point numbers_en.vtt 9.4 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/013 Comparing objects - overriding functions_en.vtt 9.3 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/009 How to use multiple conditions_en.vtt 9.3 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/008 PageRank algorithm - the final formula_en.vtt 9.1 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/006 Reshape_en.vtt 9.1 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/004 Strings_en.vtt 9.0 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/006 Lists in Python - advanced operations_en.vtt 8.9 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/009 Data filtering_en.vtt 8.9 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/004 What are array data structures II_en.vtt 8.8 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/002 Creating and updating arrays_en.vtt 8.7 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/002 Crawling the web with breadth-first search_en.vtt 8.5 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/003 Series_en.vtt 8.4 kB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/001 What is the Monte-Carlo method_en.vtt 8.3 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/003 What are array data structures I_en.vtt 8.2 kB~Get Your Files Here !/05 - Gauss Elimination Implementation/002 Gaussian elimination implementation II_en.vtt 8.2 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/010 Using the apply() function_en.vtt 8.1 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/001 What is gradient descent_en.vtt 8.1 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/001 What is Pandas_en.vtt 8.1 kB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/002 Gaussian elimination illustration_en.vtt 8.0 kB~Get Your Files Here !/11 - Numerical Integration/004 Trapezoidal integral introduction_en.vtt 7.9 kB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/004 Speed consideration - C, Java and Python_en.vtt 7.8 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/007 What is ADAGrad_en.vtt 7.7 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/012 What is vectorization_en.vtt 7.7 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/005 String slicing_en.vtt 7.6 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/007 Stacking and merging arrays_en.vtt 7.5 kB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/003 What is pivoting_en.vtt 7.4 kB~Get Your Files Here !/09 - Interpolation/003 Interpolation implementation I_en.vtt 7.4 kB~Get Your Files Here !/13 - Differential Equations/002 Euler's method introduction_en.vtt 7.2 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/011 Loops - for loop_en.vtt 7.1 kB~Get Your Files Here !/13 - Differential Equations/007 Runge-Kutta method example I_en.vtt 7.1 kB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/001 What is Gaussian elimination_en.vtt 7.0 kB~Get Your Files Here !/11 - Numerical Integration/003 Rectangle method implementation_en.vtt 7.0 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/003 Using the constructor_en.vtt 7.0 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/011 Modules_en.vtt 6.9 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/003 The original formula_en.vtt 6.9 kB~Get Your Files Here !/09 - Interpolation/002 Interpolation illustration_en.vtt 6.8 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/008 Operations_en.vtt 6.8 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/001 Graph representation of the WWW_en.vtt 6.7 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/007 Reading CSV and text files_en.vtt 6.6 kB~Get Your Files Here !/10 - Root Finding/003 Bisection method implementation_en.vtt 6.6 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/001 First steps in Python_en.vtt 6.6 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/005 Lists in Python_en.vtt 6.6 kB~Get Your Files Here !/03 - Linear Algebra/002 Matrix multiplication implementation_en.vtt 6.6 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/006 Stochastic gradient descent implementation II_en.vtt 6.5 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/009 Power method_en.vtt 6.5 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/013 Doubly linked list implementation in Python_en.vtt 6.3 kB~Get Your Files Here !/17 - Appendix #2 - Functions/002 Defining functions_en.vtt 6.3 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/007 Lists in Python - list comprehension_en.vtt 6.3 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/015 Break and continue_en.vtt 6.3 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/004 DataFrames_en.vtt 6.2 kB~Get Your Files Here !/13 - Differential Equations/003 Euler's method example_en.vtt 6.2 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/010 Polymorphism and abstraction example_en.vtt 6.2 kB~Get Your Files Here !/11 - Numerical Integration/007 Simpson's method implementation_en.vtt 6.1 kB~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/001 What are eigenvalues and eigenvectors_en.vtt 6.1 kB~Get Your Files Here !/11 - Numerical Integration/002 Rectangle method introduction_en.vtt 6.1 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/007 Operators_en.vtt 6.0 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/013 Vectorization example I_en.vtt 5.9 kB~Get Your Files Here !/17 - Appendix #2 - Functions/006 Yield operator_en.vtt 5.9 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/006 The random surfer model_en.vtt 5.8 kB~Get Your Files Here !/11 - Numerical Integration/006 Simpson's method introduction_en.vtt 5.8 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/002 What are the basic data types_en.vtt 5.7 kB~Get Your Files Here !/03 - Linear Algebra/003 Running time analysis of matrix multiplication_en.vtt 5.7 kB~Get Your Files Here !/09 - Interpolation/004 Interpolation implementation II_en.vtt 5.6 kB~Get Your Files Here !/11 - Numerical Integration/005 Trapezoidal integral implementation_en.vtt 5.5 kB~Get Your Files Here !/10 - Root Finding/004 Newton method introduction_en.vtt 5.4 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/011 Mutability and immutability_en.vtt 5.4 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/009 What is polymorphism_en.vtt 5.4 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/010 ADAM optimizer introduction_en.vtt 5.4 kB~Get Your Files Here !/17 - Appendix #2 - Functions/001 What are functions_en.vtt 5.3 kB~Get Your Files Here !/03 - Linear Algebra/006 Lists and NumPy arrays_en.vtt 5.3 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/005 Private variables and name mangling_en.vtt 5.2 kB~Get Your Files Here !/03 - Linear Algebra/001 Matrix multiplication introduction_en.vtt 5.2 kB~Get Your Files Here !/13 - Differential Equations/006 Runge-Kutta method introduction_en.vtt 5.2 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/001 What is the key advantage of NumPy_en.vtt 5.1 kB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/003 Monte-Carlo integral implementation II_en.vtt 5.1 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/005 Types_en.vtt 5.1 kB~Get Your Files Here !/17 - Appendix #2 - Functions/007 What are the most relevant built-in functions_en.vtt 5.0 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/007 The super keyword_en.vtt 5.0 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/006 Speed comparison - DataFrame operations_en.vtt 5.0 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/004 Class variables and instance variables_en.vtt 5.0 kB~Get Your Files Here !/13 - Differential Equations/008 Runge-Kutta method example II_en.vtt 5.0 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/012 Loops - while loop_en.vtt 5.0 kB~Get Your Files Here !/03 - Linear Algebra/005 Inner product_en.vtt 5.0 kB~Get Your Files Here !/10 - Root Finding/002 Bisection method introduction_en.vtt 4.9 kB~Get Your Files Here !/17 - Appendix #2 - Functions/009 Local vs global variables_en.vtt 4.9 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/003 Gradient descent with momentum_en.vtt 4.8 kB~Get Your Files Here !/10 - Root Finding/005 Newton method implementation_en.vtt 4.8 kB~Get Your Files Here !/13 - Differential Equations/005 Euler's method example - pendulum with drag_en.vtt 4.8 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/006 Type casting_en.vtt 4.8 kB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/003 Rounding errors_en.vtt 4.8 kB~Get Your Files Here !/03 - Linear Algebra/004 Matrix vector multiplication_en.vtt 4.8 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/008 Conditional statements_en.vtt 4.7 kB~Get Your Files Here !/03 - Linear Algebra/007 Matrix operations with NumPy_en.vtt 4.6 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/014 Enumerate_en.vtt 4.4 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/010 What are tuples_en.vtt 4.4 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/009 What is RMSProp_en.vtt 4.4 kB~Get Your Files Here !/20 - Appendix #5 - NumPy/008 Filter_en.vtt 4.3 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/006 What is inheritance in OOP_en.vtt 4.2 kB~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/007 What are the problems with the random surfer model_en.vtt 4.2 kB~Get Your Files Here !/10 - Root Finding/001 Root of functions introduction_en.vtt 4.2 kB~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/001 Portfolio optimization introduction_en.vtt 4.1 kB~Get Your Files Here !/17 - Appendix #2 - Functions/010 The __main__ function_en.vtt 4.1 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/014 Vectorization example II_en.vtt 4.1 kB~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/004 Gaussian elimination and singular matrixes_en.vtt 4.1 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/002 Data structures introduction_en.vtt 4.1 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/010 Logical operators_en.vtt 4.1 kB~Get Your Files Here !/11 - Numerical Integration/001 Integration introduction_en.vtt 3.9 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/012 The __str__ function_en.vtt 3.6 kB~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/002 Eigenvalues and eigenvectors implementation_en.vtt 3.6 kB~Get Your Files Here !/02 - ### NUMERICAL METHODS ###/002 Precision and accuracy_en.vtt 3.5 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/002 First steps_en.vtt 3.5 kB~Get Your Files Here !/17 - Appendix #2 - Functions/005 Returning multiple values_en.vtt 3.4 kB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/004 Applications of Monte-Carlo simulations in finance_en.vtt 3.4 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/002 Class and objects basics_en.vtt 3.3 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/013 What are nested loops_en.vtt 3.1 kB~Get Your Files Here !/06 - #1 Challenge - Portfolio Optimization/002 Portfolio optimization implementation_en.vtt 3.1 kB~Get Your Files Here !/21 - Appendix #6 - Pandas/011 Speed comparison - loops and apply()_en.vtt 3.0 kB~Get Your Files Here !/09 - Interpolation/005 Applications of interpolation_en.vtt 3.0 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/016 Calculating Fibonacci-numbers_en.vtt 3.0 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/001 What is object oriented programming (OOP)_en.vtt 2.9 kB~Get Your Files Here !/19 - Appendix #4 - Object Oriented Programming (OOP)/008 Function (method) override_en.vtt 2.8 kB~Get Your Files Here !/17 - Appendix #2 - Functions/004 Returning values_en.vtt 2.8 kB~Get Your Files Here !/01 - Introduction/001 Introduction_en.vtt 2.5 kB~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/003 Applications of eigenvectors in machine learning_en.vtt 2.3 kB~Get Your Files Here !/16 - Appendix #1 - Python Basics/003 Booleans_en.vtt 2.3 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/006 StochasticGradientDescentRegression.py 2.2 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/StochasticGradientDescentRegression.py 2.2 kB~Get Your Files Here !/09 - Interpolation/004 LagrangeInterpolation.py 2.2 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/LagrangeInterpolation.py 2.2 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/005 StochasticGradientDescent.py 2.0 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/StochasticGradientDescent.py 2.0 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/008 GradientDescentAdaGrad.py 1.6 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GradientDescentAdaGrad.py 1.6 kB
~Get Your Files Here !/20 - Appendix #5 - NumPy/009 Running time comparison arrays and lists.html 1.4 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GradientDescentMomentum.py 1.3 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/002 GradientDescent.py 1.3 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GradientDescent.py 1.3 kB~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/009 Measuring running time of lists.html 1.3 kB~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/002 MonteCarloIntegral.py 1.2 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MonteCarloIntegral.py 1.2 kB~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/011 ADAM.py 1.1 kB~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/ADAM.py 1.1 kB~Get Your Files Here !/05 - Gauss Elimination Implementation/002 GaussElimination.py 838 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/GaussElimination.py 838 Bytes~Get Your Files Here !/12 - #3 Challenge - Monte-Carlo Integration/003 MonteCarloIntegral2.py 676 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MonteCarloIntegral2.py 676 Bytes~Get Your Files Here !/13 - Differential Equations/008 RungeKuttaExample2.py 663 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/RungeKuttaExample2.py 663 Bytes~Get Your Files Here !/13 - Differential Equations/007 RungeKuttaExample1.py 648 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/RungeKuttaExample1.py 648 Bytes~Get Your Files Here !/18 - Appendix #3 - Data Structures in Python/008 (!!!) Python lists and arrays.html 628 Bytes~Get Your Files Here !/11 - Numerical Integration/007 SimpsonMethod.py 511 Bytes~Get Your Files Here !/03 - Linear Algebra/002 MatrixMultiplication.py 496 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MatrixMultiplication.py 496 Bytes~Get Your Files Here !/11 - Numerical Integration/005 TrapezoidalIntegral.py 468 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/TrapezoidalIntegral.py 468 Bytes~Get Your Files Here !/13 - Differential Equations/003 EulerMethodExample1.py 449 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EulerMethodExample1.py 449 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EulerMethodExample3.py 449 Bytes~Get Your Files Here !/15 - ### APPENDIX - PYTHON PROGRAMMING CRASH COURSE ###/001 Python crash course introduction.html 441 Bytes~Get Your Files Here !/03 - Linear Algebra/004 MatrixVectorMultiplication.py 423 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/MatrixVectorMultiplication.py 423 Bytes~Get Your Files Here !/13 - Differential Equations/004 EulerMethodExample2.py 421 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EulerMethodExample2.py 421 Bytes~Get Your Files Here !/03 - Linear Algebra/005 InnerProduct.py 386 Bytes
~Get Your Files Here !/Bonus Resources.txt 386 Bytes~Get Your Files Here !/11 - Numerical Integration/003 RectangleIntegral.py 376 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/RectangleIntegral.py 376 Bytes~Get Your Files Here !/10 - Root Finding/003 BisectionMethod.py 360 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/BisectionMethod.py 360 Bytes~Get Your Files Here !/04 - Linear Systems and Gaussian Elimination/005 Mathematical formulation of Gaussian elimination.html 345 Bytes~Get Your Files Here !/10 - Root Finding/005 NewtonRaphsonMethod.py 294 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/NewtonRaphsonMethod.py 294 Bytes~Get Your Files Here !/14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/012 Mathematical formulation of optimization algorithms in machine learning.html 275 Bytes~Get Your Files Here !/10 - Root Finding/006 Mathematical formulation of root finding.html 271 Bytes~Get Your Files Here !/09 - Interpolation/006 Mathematical formulation of interpolation.html 265 Bytes~Get Your Files Here !/07 - Eigenvalues And Eigenvectors/004 Mathematical formulation of eigenvectors.html 261 Bytes~Get Your Files Here !/08 - #2 Challenge - Google's PageRank Algorithm/010 Original scientific paper of PageRank algorithm.html 254 Bytes~Get Your Files Here !/13 - Differential Equations/009 Mathematical formulation of numerical differentiation.html 251 Bytes~Get Your Files Here !/11 - Numerical Integration/008 Mathematical formulation of numerical integration.html 245 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/NumPyOperations.py 224 Bytes
Get Bonus Downloads Here.url 182 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/EigenvectorExample.py 117 Bytes~Get Your Files Here !/22 - Course Materials (DOWNLOADS)/001 Course material.html 58 Bytes
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