Numerical Methods and Optimization in Python | F99AB3895B1AB1E294793F19BDC2EDF421C85ACD

Numerical Methods and Optimization in Python

Name	Numerical Methods and Optimization in Python	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	3.7 GB
Total Files	481
Last Seen	2025-07-17 23:40
Hash	F99AB3895B1AB1E294793F19BDC2EDF421C85ACD

/.../14 - ### NUMERICAL OPTIMIZATION (MACHINE LEARNING ALGORITHMS) ###/
005 Stochastic gradient descent implementation I.mp4	111.0 MB
005 Stochastic gradient descent implementation I_en.vtt	25.0 KB
008 ADAGrad implementation_en.vtt	14.0 KB
004 Stochastic gradient descent introduction_en.vtt	12.1 KB
002 Gradient descent implementation_en.vtt	11.6 KB
011 ADAM optimizer implementation_en.vtt	10.4 KB
001 What is gradient descent_en.vtt	8.1 KB
007 What is ADAGrad_en.vtt	7.7 KB
006 Stochastic gradient descent implementation II_en.vtt	6.5 KB
010 ADAM optimizer introduction_en.vtt	5.4 KB
003 Gradient descent with momentum_en.vtt	4.8 KB
009 What is RMSProp_en.vtt	4.4 KB
002 GradientDescent.py	1.3 KB
005 StochasticGradientDescent.py	2.0 KB
006 StochasticGradientDescentRegression.py	2.2 KB
008 GradientDescentAdaGrad.py	1.6 KB
011 ADAM.py	1.1 KB
012 Mathematical formulation of optimization algorithms in machine learning.html	0.3 KB
008 ADAGrad implementation.mp4	67.1 MB
002 Gradient descent implementation.mp4	49.9 MB
011 ADAM optimizer implementation.mp4	45.1 MB
006 Stochastic gradient descent implementation II.mp4	43.2 MB
004 Stochastic gradient descent introduction.mp4	38.2 MB
001 What is gradient descent.mp4	29.2 MB
007 What is ADAGrad.mp4	23.2 MB
003 Gradient descent with momentum.mp4	21.0 MB
009 What is RMSProp.mp4	20.0 MB
010 ADAM optimizer introduction.mp4	12.9 MB
/
TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/01 - Introduction/
001 Introduction_en.vtt	2.5 KB
001 Introduction.mp4	14.3 MB
/.../13 - Differential Equations/
004 Euler's method example - pendulum_en.vtt	13.3 KB
001 How to deal with differential equations_en.vtt	10.0 KB
002 Euler's method introduction_en.vtt	7.2 KB
007 Runge-Kutta method example I_en.vtt	7.1 KB
003 Euler's method example_en.vtt	6.2 KB
006 Runge-Kutta method introduction_en.vtt	5.2 KB
008 Runge-Kutta method example II_en.vtt	5.0 KB
003 EulerMethodExample1.py	0.4 KB
004 EulerMethodExample2.py	0.4 KB
005 Euler's method example - pendulum with drag_en.vtt	4.8 KB
007 RungeKuttaExample1.py	0.6 KB
008 RungeKuttaExample2.py	0.7 KB
009 Mathematical formulation of numerical differentiation.html	0.3 KB
004 Euler's method example - pendulum.mp4	35.7 MB
001 How to deal with differential equations.mp4	25.7 MB
007 Runge-Kutta method example I.mp4	25.7 MB
008 Runge-Kutta method example II.mp4	23.3 MB
003 Euler's method example.mp4	20.6 MB
005 Euler's method example - pendulum with drag.mp4	16.9 MB
006 Runge-Kutta method introduction.mp4	14.9 MB
002 Euler's method introduction.mp4	13.6 MB
/.../18 - Appendix #3 - Data Structures in Python/
001 How to measure the running time of algorithms_en.vtt	12.9 KB
017 Sorting_en.vtt	11.6 KB
015 Dictionaries in Python_en.vtt	10.9 KB
012 What are linked list data structures_en.vtt	10.5 KB
014 Hashing and O(1) running time complexity_en.vtt	10.0 KB
016 Sets in Python_en.vtt	9.8 KB
006 Lists in Python - advanced operations_en.vtt	8.9 KB
004 What are array data structures II_en.vtt	8.8 KB
003 What are array data structures I_en.vtt	8.2 KB
005 Lists in Python_en.vtt	6.6 KB
013 Doubly linked list implementation in Python_en.vtt	6.3 KB
007 Lists in Python - list comprehension_en.vtt	6.3 KB
011 Mutability and immutability_en.vtt	5.4 KB
010 What are tuples_en.vtt	4.4 KB
002 Data structures introduction_en.vtt	4.1 KB
009 Measuring running time of lists.html	1.3 KB
008 (!!!) Python lists and arrays.html	0.6 KB
017 Sorting.mp4	53.0 MB
016 Sets in Python.mp4	49.4 MB
006 Lists in Python - advanced operations.mp4	41.2 MB
015 Dictionaries in Python.mp4	40.4 MB
001 How to measure the running time of algorithms.mp4	39.1 MB
012 What are linked list data structures.mp4	36.2 MB
014 Hashing and O(1) running time complexity.mp4	32.5 MB
003 What are array data structures I.mp4	26.2 MB
004 What are array data structures II.mp4	26.2 MB
013 Doubly linked list implementation in Python.mp4	25.6 MB
007 Lists in Python - list comprehension.mp4	24.0 MB
005 Lists in Python.mp4	22.8 MB
011 Mutability and immutability.mp4	19.4 MB
010 What are tuples.mp4	15.4 MB
002 Data structures introduction.mp4	14.5 MB
/.../17 - Appendix #2 - Functions/
003 Positional arguments and keyword arguments_en.vtt	12.0 KB
008 What is recursion_en.vtt	10.9 KB
002 Defining functions_en.vtt	6.3 KB
006 Yield operator_en.vtt	5.9 KB
001 What are functions_en.vtt	5.3 KB
007 What are the most relevant built-in functions_en.vtt	5.0 KB
009 Local vs global variables_en.vtt	4.9 KB
010 The __main__ function_en.vtt	4.1 KB
005 Returning multiple values_en.vtt	3.4 KB
004 Returning values_en.vtt	2.8 KB
003 Positional arguments and keyword arguments.mp4	48.4 MB
008 What is recursion.mp4	37.0 MB
002 Defining functions.mp4	19.8 MB
006 Yield operator.mp4	19.2 MB
001 What are functions.mp4	18.1 MB
007 What are the most relevant built-in functions.mp4	16.1 MB
009 Local vs global variables.mp4	15.7 MB
010 The __main__ function.mp4	15.5 MB
005 Returning multiple values.mp4	12.8 MB
004 Returning values.mp4	8.5 MB
/.../05 - Gauss Elimination Implementation/
001 Gaussian elimination implementation I_en.vtt	11.8 KB
002 GaussElimination.py	0.8 KB
002 Gaussian elimination implementation II_en.vtt	8.2 KB
001 Gaussian elimination implementation I.mp4	37.4 MB
002 Gaussian elimination implementation II.mp4	31.0 MB
/.../08 - #2 Challenge - Google's PageRank Algorithm/
004 PageRank algorithm example_en.vtt	11.5 KB
005 Matrix representation of the problem_en.vtt	10.0 KB
008 PageRank algorithm - the final formula_en.vtt	9.1 KB
002 Crawling the web with breadth-first search_en.vtt	8.5 KB
003 The original formula_en.vtt	6.9 KB
010 Original scientific paper of PageRank algorithm.html	0.3 KB
001 Graph representation of the WWW_en.vtt	6.7 KB
009 Power method_en.vtt	6.5 KB
006 The random surfer model_en.vtt	5.8 KB
007 What are the problems with the random surfer model_en.vtt	4.2 KB
008 PageRank algorithm - the final formula.mp4	39.6 MB
005 Matrix representation of the problem.mp4	30.5 MB
002 Crawling the web with breadth-first search.mp4	27.1 MB
001 Graph representation of the WWW.mp4	26.3 MB
004 PageRank algorithm example.mp4	26.2 MB
009 Power method.mp4	22.4 MB
006 The random surfer model.mp4	19.7 MB
003 The original formula.mp4	18.6 MB
007 What are the problems with the random surfer model.mp4	12.9 MB
/.../21 - Appendix #6 - Pandas/
005 DataFrame operations_en.vtt	11.1 KB
009 Data filtering_en.vtt	8.9 KB
003 Series_en.vtt	8.4 KB
010 Using the apply() function_en.vtt	8.1 KB
001 What is Pandas_en.vtt	8.1 KB
012 What is vectorization_en.vtt	7.7 KB
008 Operations_en.vtt	6.8 KB
007 Reading CSV and text files_en.vtt	6.6 KB
004 DataFrames_en.vtt	6.2 KB
013 Vectorization example I_en.vtt	5.9 KB
006 Speed comparison - DataFrame operations_en.vtt	5.0 KB
014 Vectorization example II_en.vtt	4.1 KB
002 First steps_en.vtt	3.5 KB
011 Speed comparison - loops and apply()_en.vtt	3.0 KB
005 DataFrame operations.mp4	43.3 MB
007 Reading CSV and text files.mp4	36.9 MB
008 Operations.mp4	34.5 MB
010 Using the apply() function.mp4	32.3 MB
006 Speed comparison - DataFrame operations.mp4	30.0 MB
009 Data filtering.mp4	28.4 MB
003 Series.mp4	28.2 MB
012 What is vectorization.mp4	27.7 MB
001 What is Pandas.mp4	26.7 MB
013 Vectorization example I.mp4	23.3 MB
014 Vectorization example II.mp4	21.8 MB
004 DataFrames.mp4	19.3 MB
011 Speed comparison - loops and apply().mp4	18.6 MB
002 First steps.mp4	10.9 MB
/.../12 - #3 Challenge - Monte-Carlo Integration/
003 MonteCarloIntegral2.py	0.7 KB
002 Monte-Carlo integral implementation I_en.vtt	9.7 KB
001 What is the Monte-Carlo method_en.vtt	8.3 KB
002 MonteCarloIntegral.py	1.2 KB
003 Monte-Carlo integral implementation II_en.vtt	5.1 KB
004 Applications of Monte-Carlo simulations in finance_en.vtt	3.4 KB
002 Monte-Carlo integral implementation I.mp4	41.7 MB
001 What is the Monte-Carlo method.mp4	31.6 MB
003 Monte-Carlo integral implementation II.mp4	25.7 MB
004 Applications of Monte-Carlo simulations in finance.mp4	15.0 MB
/.../22 - Course Materials (DOWNLOADS)/
001 Course material.html	0.1 KB
001 numerical-methods.zip	3.5 MB
/.../03 - Linear Algebra/
002 MatrixMultiplication.py	0.5 KB
004 MatrixVectorMultiplication.py	0.4 KB
005 InnerProduct.py	0.4 KB
002 Matrix multiplication implementation_en.vtt	6.6 KB
003 Running time analysis of matrix multiplication_en.vtt	5.7 KB
006 Lists and NumPy arrays_en.vtt	5.3 KB
001 Matrix multiplication introduction_en.vtt	5.2 KB
005 Inner product_en.vtt	5.0 KB
004 Matrix vector multiplication_en.vtt	4.8 KB
007 Matrix operations with NumPy_en.vtt	4.6 KB
003 Running time analysis of matrix multiplication.mp4	28.4 MB
002 Matrix multiplication implementation.mp4	21.6 MB
006 Lists and NumPy arrays.mp4	20.3 MB
005 Inner product.mp4	17.4 MB
007 Matrix operations with NumPy.mp4	14.3 MB
004 Matrix vector multiplication.mp4	14.1 MB
001 Matrix multiplication introduction.mp4	13.1 MB
/09 - Interpolation/
001 What is interpolation_en.vtt	11.1 KB
003 Interpolation implementation I_en.vtt	7.4 KB
002 Interpolation illustration_en.vtt	6.8 KB
004 LagrangeInterpolation.py	2.2 KB
005 Applications of interpolation_en.vtt	3.0 KB
006 Mathematical formulation of interpolation.html	0.3 KB
004 Interpolation implementation II_en.vtt	5.6 KB
001 What is interpolation.mp4	40.6 MB
004 Interpolation implementation II.mp4	32.4 MB
003 Interpolation implementation I.mp4	27.4 MB
002 Interpolation illustration.mp4	15.8 MB
005 Applications of interpolation.mp4	9.0 MB
/.../20 - Appendix #5 - NumPy/
003 Dimension of arrays_en.vtt	10.9 KB
004 Indexes and slicing_en.vtt	9.6 KB
006 Reshape_en.vtt	9.1 KB
002 Creating and updating arrays_en.vtt	8.7 KB
007 Stacking and merging arrays_en.vtt	7.5 KB
001 What is the key advantage of NumPy_en.vtt	5.1 KB
005 Types_en.vtt	5.1 KB
008 Filter_en.vtt	4.3 KB
009 Running time comparison arrays and lists.html	1.4 KB
003 Dimension of arrays.mp4	38.0 MB
006 Reshape.mp4	35.5 MB
002 Creating and updating arrays.mp4	35.4 MB
004 Indexes and slicing.mp4	33.0 MB
007 Stacking and merging arrays.mp4	29.0 MB
005 Types.mp4	20.2 MB
001 What is the key advantage of NumPy.mp4	18.0 MB
008 Filter.mp4	16.0 MB
/.../02 - ### NUMERICAL METHODS ###/
001 Floating point numbers_en.vtt	9.4 KB
004 Speed consideration - C, Java and Python_en.vtt	7.8 KB
003 Rounding errors_en.vtt	4.8 KB
002 Precision and accuracy_en.vtt	3.5 KB
004 Speed consideration - C, Java and Python.mp4	28.8 MB
001 Floating point numbers.mp4	25.7 MB
003 Rounding errors.mp4	14.8 MB
002 Precision and accuracy.mp4	9.9 MB
/.../19 - Appendix #4 - Object Oriented Programming (OOP)/
013 Comparing objects - overriding functions_en.vtt	9.3 KB
003 Using the constructor_en.vtt	7.0 KB
011 Modules_en.vtt	6.9 KB
010 Polymorphism and abstraction example_en.vtt	6.2 KB
009 What is polymorphism_en.vtt	5.4 KB
005 Private variables and name mangling_en.vtt	5.2 KB
007 The super keyword_en.vtt	5.0 KB
004 Class variables and instance variables_en.vtt	5.0 KB
006 What is inheritance in OOP_en.vtt	4.2 KB
012 The __str__ function_en.vtt	3.6 KB
002 Class and objects basics_en.vtt	3.3 KB
001 What is object oriented programming (OOP)_en.vtt	2.9 KB
008 Function (method) override_en.vtt	2.8 KB
013 Comparing objects - overriding functions.mp4	42.1 MB
003 Using the constructor.mp4	35.2 MB
010 Polymorphism and abstraction example.mp4	34.9 MB
004 Class variables and instance variables.mp4	32.5 MB
011 Modules.mp4	22.8 MB
007 The super keyword.mp4	22.3 MB
009 What is polymorphism.mp4	22.2 MB
005 Private variables and name mangling.mp4	20.1 MB
008 Function (method) override.mp4	19.1 MB
006 What is inheritance in OOP.mp4	18.9 MB
012 The __str__ function.mp4	16.4 MB
001 What is object oriented programming (OOP).mp4	13.1 MB
002 Class and objects basics.mp4	11.0 MB
/.../16 - Appendix #1 - Python Basics/
009 How to use multiple conditions_en.vtt	9.3 KB
004 Strings_en.vtt	9.0 KB
005 String slicing_en.vtt	7.6 KB
011 Loops - for loop_en.vtt	7.1 KB
001 First steps in Python_en.vtt	6.6 KB
015 Break and continue_en.vtt	6.3 KB
007 Operators_en.vtt	6.0 KB
002 What are the basic data types_en.vtt	5.7 KB
012 Loops - while loop_en.vtt	5.0 KB
006 Type casting_en.vtt	4.8 KB
008 Conditional statements_en.vtt	4.7 KB
014 Enumerate_en.vtt	4.4 KB
010 Logical operators_en.vtt	4.1 KB
013 What are nested loops_en.vtt	3.1 KB
016 Calculating Fibonacci-numbers_en.vtt	3.0 KB
003 Booleans_en.vtt	2.3 KB
009 How to use multiple conditions.mp4	32.9 MB
004 Strings.mp4	29.5 MB
005 String slicing.mp4	26.3 MB
007 Operators.mp4	21.6 MB
015 Break and continue.mp4	21.4 MB
011 Loops - for loop.mp4	19.9 MB
008 Conditional statements.mp4	18.7 MB
010 Logical operators.mp4	18.5 MB
006 Type casting.mp4	17.6 MB
002 What are the basic data types.mp4	16.5 MB
014 Enumerate.mp4	15.9 MB
012 Loops - while loop.mp4	15.1 MB
001 First steps in Python.mp4	14.3 MB
013 What are nested loops.mp4	13.8 MB
016 Calculating Fibonacci-numbers.mp4	8.8 MB
003 Booleans.mp4	7.1 MB
/.../04 - Linear Systems and Gaussian Elimination/
005 Mathematical formulation of Gaussian elimination.html	0.3 KB
002 Gaussian elimination illustration_en.vtt	8.0 KB
003 What is pivoting_en.vtt	7.4 KB
001 What is Gaussian elimination_en.vtt	7.0 KB
004 Gaussian elimination and singular matrixes_en.vtt	4.1 KB
003 What is pivoting.mp4	20.7 MB
001 What is Gaussian elimination.mp4	17.6 MB
002 Gaussian elimination illustration.mp4	14.3 MB
004 Gaussian elimination and singular matrixes.mp4	9.1 MB
/.../07 - Eigenvalues And Eigenvectors/
003 Applications of eigenvectors in machine learning_en.vtt	2.3 KB
004 Mathematical formulation of eigenvectors.html	0.3 KB
001 What are eigenvalues and eigenvectors_en.vtt	6.1 KB
002 Eigenvalues and eigenvectors implementation_en.vtt	3.6 KB
001 What are eigenvalues and eigenvectors.mp4	15.1 MB
002 Eigenvalues and eigenvectors implementation.mp4	11.4 MB
003 Applications of eigenvectors in machine learning.mp4	11.2 MB
/.../11 - Numerical Integration/
004 Trapezoidal integral introduction_en.vtt	7.9 KB
003 Rectangle method implementation_en.vtt	7.0 KB
007 Simpson's method implementation_en.vtt	6.1 KB
002 Rectangle method introduction_en.vtt	6.1 KB
006 Simpson's method introduction_en.vtt	5.8 KB
003 RectangleIntegral.py	0.4 KB
005 Trapezoidal integral implementation_en.vtt	5.5 KB
005 TrapezoidalIntegral.py	0.5 KB
007 SimpsonMethod.py	0.5 KB
008 Mathematical formulation of numerical integration.html	0.2 KB
001 Integration introduction_en.vtt	3.9 KB
003 Rectangle method implementation.mp4	23.5 MB
007 Simpson's method implementation.mp4	21.6 MB
004 Trapezoidal integral introduction.mp4	20.0 MB
002 Rectangle method introduction.mp4	18.9 MB
005 Trapezoidal integral implementation.mp4	18.5 MB
006 Simpson's method introduction.mp4	12.6 MB
001 Integration introduction.mp4	11.4 MB
/.../10 - Root Finding/
003 Bisection method implementation_en.vtt	6.6 KB
003 BisectionMethod.py	0.4 KB
005 NewtonRaphsonMethod.py	0.3 KB
006 Mathematical formulation of root finding.html	0.3 KB
004 Newton method introduction_en.vtt	5.4 KB
002 Bisection method introduction_en.vtt	4.9 KB
005 Newton method implementation_en.vtt	4.8 KB
001 Root of functions introduction_en.vtt	4.2 KB
003 Bisection method implementation.mp4	25.3 MB
004 Newton method introduction.mp4	17.2 MB
005 Newton method implementation.mp4	16.6 MB
001 Root of functions introduction.mp4	12.9 MB
002 Bisection method introduction.mp4	10.7 MB
/.../06 - #1 Challenge - Portfolio Optimization/
001 Portfolio optimization introduction_en.vtt	4.1 KB
002 Portfolio optimization implementation_en.vtt	3.1 KB
002 Portfolio optimization implementation.mp4	14.5 MB
001 Portfolio optimization introduction.mp4	13.8 MB
/.../15 - ### APPENDIX - PYTHON PROGRAMMING CRASH COURSE ###/
001 Python crash course introduction.html	0.4 KB
/.pad/
0	181.7 KB
1	7.9 KB
2	449.9 KB
3	478.7 KB
4	897.2 KB
5	931.0 KB
6	1.0 MB
7	731.6 KB
8	811.6 KB
9	862.6 KB
10	244.4 KB
11	717.5 KB
12	290.3 KB
13	526.8 KB
14	275.9 KB
15	742.4 KB
16	578.8 KB
17	776.3 KB
18	341.5 KB
19	754.4 KB
20	810.5 KB
21	532.4 KB
22	1.4 KB
23	169.9 KB
24	255.9 KB
25	425.8 KB
26	763.2 KB
27	68.3 KB
28	519.9 KB
29	621.4 KB
30	1.0 MB
31	20.2 KB
32	153.7 KB
33	160.9 KB
34	930.5 KB
35	446.5 KB
36	980.4 KB
37	366.3 KB
38	883.9 KB
39	208.2 KB
40	329.9 KB
41	515.7 KB
42	988.9 KB
43	1.0 MB
44	61.7 KB
45	586.6 KB
46	916.8 KB
47	124.9 KB
48	599.6 KB
49	969.4 KB
50	990.0 KB
51	10.3 KB
52	49.6 KB
53	58.9 KB
54	503.5 KB
55	522.2 KB
56	536.4 KB
57	543.6 KB
58	569.3 KB
59	918.7 KB
60	122.1 KB
61	651.5 KB
62	835.2 KB
63	859.8 KB
64	913.6 KB
65	221.7 KB
66	277.2 KB
67	715.1 KB
68	805.7 KB
69	876.8 KB
70	195.4 KB
71	391.0 KB
72	450.5 KB
73	461.0 KB
74	603.0 KB
75	1.0 MB
76	253.2 KB
77	369.1 KB
78	624.5 KB
79	748.7 KB
80	910.1 KB
81	923.8 KB
82	990.0 KB
83	54.8 KB
84	156.9 KB
85	198.1 KB
86	530.4 KB
87	578.3 KB
88	756.1 KB
89	871.8 KB
90	994.4 KB
91	1.0 MB
92	200.1 KB
93	233.2 KB
94	242.9 KB
95	404.8 KB
96	421.2 KB
97	743.2 KB
98	864.3 KB
99	191.5 KB
100	274.5 KB
101	456.4 KB
102	625.1 KB
103	891.9 KB
104	221.6 KB
105	310.4 KB
106	351.1 KB
107	646.7 KB
108	793.8 KB
109	912.0 KB
110	938.3 KB
111	1.0 MB
112	196.7 KB
113	278.7 KB
114	617.4 KB
115	645.4 KB
116	740.9 KB
117	800.1 KB
118	918.8 KB
119	163.5 KB
120	170.7 KB
121	330.3 KB
122	342.3 KB
123	403.5 KB
124	422.5 KB
125	615.8 KB
126	879.9 KB
127	915.2 KB
128	67.0 KB
129	519.3 KB
130	562.3 KB
131	722.9 KB
132	754.6 KB
133	776.0 KB
134	874.6 KB
135	6.7 KB
136	90.6 KB
137	170.9 KB
138	370.2 KB
139	547.5 KB
140	590.3 KB
141	872.6 KB
142	584.2 KB
143	320.6 KB
144	406.9 KB
145	644.8 KB
146	899.5 KB
147	228.7 KB
Total files 481