UDEMY.Time.Series.Analysis.and.Forecasting.using.Python.
Language: English
Files Type:mp4, nfo| Size:4.34 GB
Video:13:17:40 | 1280X720 | 713 Kbps
Audio:mp4a-40-2 | 128 Kbps | AAC
Genre:eLearning
About :
Videos Files :
1. Welcome to the course.mp4 (22.21 MB)
11. Opening Jupyter Notebook.mp4 (65.18 MB)
12. Introduction to Jupyter.mp4 (40.91 MB)
13. Arithmetic operators in Python Python Basics.mp4 (12.74 MB)
14. Strings in Python Python Basics.mp4 (64.43 MB)
15. Lists, Tuples and Directories Python Basics.mp4 (60.32 MB)
16. Working with Numpy Library of Python.mp4 (43.86 MB)
17. Working with Pandas Library of Python.mp4 (46.89 MB)
18. Working with Seaborn Library of Python.mp4 (40.36 MB)
19. Data Loading in Python.mp4 (108.88 MB)
2. What is Time Series Forecasting.mp4 (12.26 MB)
20. Time Series Feature Engineering Basics.mp4 (59.47 MB)
21. Time Series Feature Engineering in Python.mp4 (112.68 MB)
22. Time Series Upsampling and Downsampling.mp4 (16.95 MB)
23. Time Series Upsampling and Downsampling in Python.mp4 (100.67 MB)
24. Time Series Visualization Basics.mp4 (63.7 MB)
25. Time Series Visualization in Python.mp4 (165.21 MB)
26. Time Series Power Transformation.mp4 (14.84 MB)
27. Moving Average.mp4 (38.72 MB)
28. Exponential Smoothing.mp4 (8.38 MB)
29. White Noise.mp4 (11.37 MB)
30. Random Walk.mp4 (21.16 MB)
31. Decomposing Time Series in Python.mp4 (59.82 MB)
32. Differencing.mp4 (32.35 MB)
33. Differencing in Python.mp4 (112.98 MB)
34. Test Train Split in Python.mp4 (57.41 MB)
35. Naive (Persistence) model in Python.mp4 (43.37 MB)
36. Auto Regression Model Basics.mp4 (16.89 MB)
37. Auto Regression Model creation in Python.mp4 (53.49 MB)
38. Auto Regression with Walk Forward validation in Python.mp4 (49.63 MB)
39. Moving Average model Basics.mp4 (24.07 MB)
4. This is a milestone!.mp4 (20.66 MB)
40. Moving Average model in Python.mp4 (56.67 MB)
41. ACF and PACF.mp4 (41.21 MB)
42. ARIMA model Basics.mp4 (21.37 MB)
43. ARIMA model in Python.mp4 (74.42 MB)
44. ARIMA model with Walk Forward Validation in Python.mp4 (32.15 MB)
45. SARIMA model.mp4 (39.04 MB)
46. SARIMA model in Python.mp4 (66.23 MB)
47. Stationary Time Series.mp4 (5.58 MB)
48. Introduction.mp4 (9.25 MB)
5. Time Series Forecasting Use cases.mp4 (25.9 MB)
50. Gathering Business Knowledge.mp4 (14.53 MB)
51. Data Exploration.mp4 (20.13 MB)
52. The Dataset and the Data Dictionary.mp4 (69.3 MB)
53. Importing Data in Python.mp4 (27.83 MB)
54. Univariate analysis and EDD.mp4 (24.21 MB)
55. EDD in Python.mp4 (61.8 MB)
56. Outlier Treatment.mp4 (24.47 MB)
57. Outlier Treatment in Python.mp4 (70.25 MB)
58. Missing Value Imputation.mp4 (25 MB)
59. Missing Value Imputation in Python.mp4 (23.42 MB)
6. Forecasting model creation Steps.mp4 (10.11 MB)
60. Seasonality in Data.mp4 (17.03 MB)
61. Bi variate analysis and Variable transformation.mp4 (100.53 MB)
62. Variable transformation and deletion in Python.mp4 (44.11 MB)
63. Non usable variables.mp4 (20.24 MB)
64. Dummy variable creation Handling qualitative data.mp4 (36.8 MB)
65. Dummy variable creation in Python.mp4 (26.54 MB)
66. Correlation Analysis.mp4 (71.6 MB)
67. Correlation Analysis in Python.mp4 (55.31 MB)
68. The Problem Statement.mp4 (9.37 MB)
69. Basic Equations and Ordinary Least Squares (OLS) method.mp4 (43.37 MB)
7. Forecasting model creation Steps 1 (Goal).mp4 (34.48 MB)
70. Assessing accuracy of predicted coefficients.mp4 (92.09 MB)
71. Assessing Model Accuracy RSE and R squared.mp4 (43.64 MB)
72. Simple Linear Regression in Python.mp4 (63.43 MB)
73. Multiple Linear Regression.mp4 (34.31 MB)
74. The F statistic.mp4 (55.98 MB)
75. Interpreting results of Categorical variables.mp4 (22.5 MB)
76. Multiple Linear Regression in Python.mp4 (69.73 MB)
77. Test train split.mp4 (41.86 MB)
78. Bias Variance trade off.mp4 (25.1 MB)
8. Time Series Basic Notations.mp4 (62.45 MB)
80. Test train split in Python.mp4 (44.85 MB)
81. Introduction to Neural Networks and Course flow.mp4 (29.06 MB)
82. Perceptron.mp4 (44.76 MB)
83. Activation Functions.mp4 (34.62 MB)
84. Python Creating Perceptron model.mp4 (86.56 MB)
85. Basic Terminologies.mp4 (40.42 MB)
86. Gradient Descent.mp4 (60.32 MB)
87. Back Propagation.mp4 (122.18 MB)
88. Some Important Concepts.mp4 (62.16 MB)
89. Hyperparameters.mp4 (45.32 MB)
9. Installing Python and Anaconda.mp4 (16.27 MB)
90. Keras and Tensorflow.mp4 (14.91 MB)
91. Installing Tensorflow and Keras.mp4 (20.06 MB)
92. Dataset for classification.mp4 (56.13 MB)
93. Normalization and Test Train split.mp4 (44.18 MB)
94. Different ways to create ANN using Keras.mp4 (10.81 MB)
95. Building the Neural Network using Keras.mp4 (79.11 MB)
96. Compiling and Training the Neural Network model.mp4 (81.68 MB)
97. Evaluating performance and Predicting using Keras.mp4 (69.89 MB)
98. Building Neural Network for Regression Problem.mp4 (155.85 MB)
99. The final milestone!.mp4 (11.86 MB)
