Big Data Methods For Energy Systems --> [ DevCourseWeb ]
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| Torrent Hash : | 96C4C1CB220B40FAF2ACED6281EE49DB7FFD8353 |
| Torrent Added : | 1 Year+ in Other - Other |
| Torrent Size : | 1.27 GB |
Big Data Methods For Energy Systems --> [ DevCourseWeb ]
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Torrent File Content (34 files)
[ DevCourseWeb.com ] Udemy - Big Data Methods For Energy Systems
Get Bonus Downloads Here.url -
Get Bonus Downloads Here.url -
182 bytes
~Get Your Files Here !
1 - Summary.html -
1 - Summary.html -
1.93 KB
10 - Step4 Calculation of the minimum Load Factor Error.mp4 -
65.98 MB
10 - bigDataDemand-step4.xlsx -
3.78 MB
11 - Step4 using Python.mp4 -
173.8 MB
11 - bigDataDemand.xlsx -
916.15 KB
12 - Step5 Finding the day where the minimum error occurs.mp4 -
51.4 MB
12 - bigDataDemand-step5.xlsx -
4.75 MB
13 - Step5 using Python.mp4 -
159.9 MB
14 - Step6 Calculation of the small dataset that has the typical days.mp4 -
87.73 MB
14 - bigDataDemand-step6.xlsx -
5.74 MB
14 - slides.pdf -
81.06 KB
15 - Step6 using Python.mp4 -
224.94 MB
2 - Description of the Methodology & Associated risks.mp4 -
16.43 MB
2 - slides.pdf -
110.2 KB
3 - Structure of Big Data on Electricity Demand.mp4 -
43.61 MB
3 - bigDataDemand.xlsx -
914.19 KB
3 - slides.pdf -
91.63 KB
4 - Step1 Calculation of seasonal statistics for the load factor using EXCEL.mp4 -
41.75 MB
4 - bigDataDemand-step1.xlsx -
919.6 KB
4 - slides.pdf -
89.67 KB
5 - Big-Data-in-Energy-Step-1-course.ipynb -
7.3 MB
5 - Step 1 using Python.mp4 -
82.5 MB
5 - bigDataDemand-step1.xlsx -
919.6 KB
6 - Step2 Calculation of daily average Load Factor timeseries.mp4 -
40.53 MB
6 - bigDataDemand-step2.xlsx -
1.82 MB
7 - Big-Data-in-Energy-Step-2-course.ipynb -
8.24 MB
7 - Step 2 using Python.mp4 -
120.69 MB
8 - Step3 Finding the error of daily average from seasonal load factors.mp4 -
27.21 MB
8 - bigDataDemand-step3.xlsx -
2.8 MB
9 - Step3 using Python.mp4 -
126.28 MB
9 - bigDataDemand.xlsx -
916.15 KB
9 - notice.txt -
321 bytes
Bonus Resources.txt -
386 bytes
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