srrDB

907
Uploads today
92% Bitcoin logo
Completed daily pres
You can use shift-click to select all checkboxes in between.

NAVIGATION

INFORMATION

  • U: Anonymous
  • D: 2022-03-10 14:30:27
  • C: Unknown

RELEASE >

ReScene version pyReScene Auto 0.7 UDUMMY File size CRC
Download
23,860
Stored files
6,297 A7C927C0
810 07D430B7
RAR-files
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.rar 700,000,000 A6AF490E
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r00 700,000,000 1250DAD6
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r01 700,000,000 45F3DE08
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r02 700,000,000 7C6BF2EE
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r03 700,000,000 2D97D61D
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r04 700,000,000 118E9CEE
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r05 700,000,000 7211C6E9
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r06 700,000,000 FC9523D0
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r07 700,000,000 2C1A81A3
udemy.python.for.financial.analysis.and.algorithmic.trading-udummy.r08 604,682,293 7C42EF03
Total size: 6,904,682,293
Archived files
023-Series.mkv [9823b68daa42fda3] 26,720,026 E2B35515
022-Introduction_to_Pandas.mkv [f23364ce4c7cb707] 7,922,143 2D829227
071-ARIMA_with_Statsmodels.mkv [9ebbdfa3adbcca7c] 40,810,697 4662B906
055-Welcome_to_the_Capstone_Project.mkv [d15ecd2f08bb87c0] 2,773,227 4E876433
024-DataFrames.mkv [c7735db257216821] 140,330,875 80377AFA
057-Stock_Market_Analysis_Project_Solutions_Part_One.mkv [1fe6cfeb5f617350] 261,319,462 AA4BC9DC
049-Welcome_to_Pandas_for_Time_Series.mkv [f4f4552becc880f5] 1,103,311 A61B4CBE
080-Portfolio_Allocation_Code_Along_Part_One.mkv [ffecb78bb435803b] 137,378,188 69E97732
068-ETS_Code_Along.mkv [d2a7941a630213e1] 39,984,420 3B6BC784
078-Introduction_to_Python_Finance_Fundamentals.mkv [6aca5f2c7dce81e] 2,334,247 A137C383
029-Merging_Joining_and_Concatenating_DataFrames.mkv [3942fd67b0d0d0d3] 92,526,910 0CBBCFAF
032-General_Pandas_Review_Exercises.mkv [57e359afdfb128a3] 23,776,776 2D27E1A7
081-Portfolio_Allocation_Code_Along_Part_Two.mkv [febbbe4d428ebed5] 40,689,867 B2DB4706
001-Introduction_to_Course.mkv [ab4b0bd3862f5ca0] 10,528,015 54C9194B
037-Matplotlib_Basics-Part_Two.mkv [df2a1b94be065389] 53,391,802 0B85BC9F
034-Welcome_to_Visualization.mkv [61cdae8b35a72eee] 2,004,620 6DCD2EAE
088-Order_Books.mkv [20631ff1b7d7be0c] 68,581,963 82E9C785
103-Trading_Algorithm_Exercise_Solutions_Part_Two.mkv [eda5fcdbd40ace28] 14,014,688 A14D1CFE
063-Time_Series_Basics.mkv [a35adf3e2124964e] 10,254,997 B1A68522
074-ARIMA_Code_Part_Three.mkv [83f1b88eaae82249] 40,101,616 3311D546
017-Numpy_Operations.mkv [a1a97f2c4c00a23e] 28,312,424 2E92D70C
093-EMH.mkv [f7af68981c4395d6] 6,298,096 FDC61BA5
028-Group_By_with_Pandas.mkv [610002f1c563f55c] 40,089,305 774D3813
009-Python_Crash_Course_Part_One.mkv [9498c7fc0c1ad4a1] 83,225,676 51C76D0C
025-DataFrames_Part_Two.mkv [bfbeee0e2041986e] 166,444,317 A3743839
091-CAPM_Code_Along.mkv [da8842cab53ca7fb] 89,536,558 D410EC2A
054-Pandas_Rolling_and_Expanding.mkv [9972e9e43a800f1b] 136,014,778 DFE3463A
058-Python_Stock_Market_Analysis_Solutions-Part_Two.mkv [426a335b4f031f8f] 104,506,691 F7616931
002-Course_Overview_Lecture_(DONT_SKIP_THIS).mkv [255e36f83bab8d33] 23,602,795 D03B32C4
087-Types_of_Funds.mkv [53831ed068c24dc7] 18,663,137 C30E4D06
077-Welcome_to_Finance_Fundamentals.mkv [5882565c9af33fcf] 3,220,307 A41F4C79
100-First_Trading_Algorithm-Part_Two.mkv [e7ad0964bd39d044] 89,572,575 A4F3C286
019-NumPy_Review_Exercise.mkv [24df1efc8f15c049] 39,498,853 7FD9F782
035-Introduction_to_Visualization_in_Python.mkv [38b5a06f6192f83] 5,447,288 367801F0
084-Portfolio_Optimization_Code_Along_Two.mkv [83f4738c054ea0d2] 58,492,774 724BB799
083-Portfolio_Optimization_Code_Along_One.mkv [6bb768616e79e95] 98,214,503 9FB7BA08
033-General_Pandas_Exercise_Solutions.mkv [f4cb45392d7954a6] 123,305,133 68A338D2
079-Sharpe_Ratio_Slides.mkv [80f10246027de204] 37,878,612 0609A901
050-Introduction_to_Time_Series_with_Pandas.mkv [64d6036aa402cab6] 2,720,769 6292A0C7
111-Pipeline_Trading_Algorithm_Code_along_Part_Three.mkv [de7c6e12b8acb5ac] 203,955,912 84913698
118-Futures_on_Quantopian.mkv [86f5c2633792c7bb] 143,565,285 9D0CE11E
026-DataFrames_Part_Three.mkv [f72efe9e89376ea3] 40,714,532 39939DEF
039-Matplotlib_Exercise.mkv [ad5b9b51f55d2732] 30,634,456 B00D16F7
107-Welcome_to_Trading_Algorithms.mkv [3be4a10f73b78efa] 2,172,731 C8492408
102-Trading_Algorithm_Exercise_Solutions_Part_One.mkv [39b60366f705c91a] 60,317,921 51C1C874
031-Data_Input_and_Output.mkv [256f70565affcead] 106,765,351 8C9FE3C1
069-ARIMA_Theory.mkv [a1d0d9477280d768] 45,970,198 4CFF3772
040-Matplotlib_Exercise_Solutions.mkv [de2548f4d38b2ed4] 78,308,225 01A260F1
105-Quantopian_Pipelines_Filters.mkv [91c3facf78462c9f] 33,803,881 008871AE
006-Course_Installation_Guide.mkv [7d644672800b4d1b] 38,324,131 F0A7383B
092-Stock_Splits_and_Dividends.mkv [4371471c6c7c505e] 18,114,982 BFD95004
030-Pandas_Common_Operations.mkv [7cfdc4befb7f9f5d] 63,853,477 0EF4CE79
073-ARIMA_Code_Part_Two.mkv [8a8eca6b97acc955] 127,448,346 5B6CC86D
042-Pandas_Time_Series_Visualization.mkv [93a2702fa6f5a5b7] 107,768,742 314073D6
supplemental_assets\SPY.csv 143,810 05164AC4
supplemental_assets\Python-for-Finance-Repo-master.zip 13,140,619 4A8F877E
045-Introduction_to_Data_Sources.mkv [da0e6d649e9dcb7b] 4,072,636 F358960C
027-Missing_Data.mkv [bcec6b6a7f22eff2] 22,233,214 D0695F60
007-Welcome_to_the_Python_Crash_Course.mkv [d63bcc233ec3f105] 1,618,181 4D525344
056-Stock_Market_Analysis_Project.mkv [fdb65cee9836c777] 81,254,469 5E104273
117-What_are_Futures.mkv [b8be92f777ae0ade] 33,476,301 1262016B
090-CAPM-Capital_Asset_Pricing_Model.mkv [80d3793d11dd3a52] 25,993,530 AB3FC25E
051-Datetime_Index.mkv [458389cfb9a1fdac] 58,243,481 46577530
115-Portfolio_Analysis_with_PyFolio.mkv [e54104f1f63074a5] 122,126,955 C4D43909
109-Pipeline_Trading_Algorithm-Code_Along-Part_Two.mkv [7d4bfb2f774761c4] 82,659,537 087F31A0
020-Numpy_Exercise_Solutions.mkv [b7f3ce668084c4f8] 81,617,000 1057C5FE
108-Pipeline_Trading_Algorithm_Example-Code_Along-Part_One.mkv [6d8595273b8c2597] 86,067,993 19F7C8A5
016-NumPy_Arrays.mkv [b3b39ef3516f4255] 76,182,140 6EAE9121
062-Introduction_to_Time_Series.mkv [6bea5beacab86545] 14,163,271 EBEF80D0
060-Stock_Market_Analysis_Project_Solutions_Part_Four.mkv [f7728c34f7a49fa4] 61,300,277 FDA23C30
099-First_Trading_Algorithm-Part_One.mkv [7de42551d7ca953f] 95,788,472 52277B31
052-Time_Resampling.mkv [2b923ef9fb1884d3] 112,739,206 202BD7B8
089-Short_Selling.mkv [778b7b57633f4d72] 7,344,522 563B17EC
041-Pandas_Visualization_Overview.mkv [b25d8425632bbb55] 88,539,257 1CCCEC0E
067-EWMA_Code_Along.mkv [5d479eaf446d0744] 98,763,113 5CC06B4D
065-ETS_Theory.mkv [fab94f27e5a8148d] 12,318,009 1D9BDA3A
082-Portfolio_Optimization.mkv [f7bb0f0d4ade3c40] 25,704,932 19A65856
038-Matplotlib_Part_Three.mkv [75c4387b1ba9d04f] 85,179,359 8BCA03B9
097-Quantopian_Algorithms_Basics_Part_One.mkv [a747956532936a2f] 77,282,498 31374311
047-Pandas_DataReader.mkv [cdbe36bf5e59ca39] 16,119,543 0A46C991
075-ARIMA_Code_Part_Four.mkv [5fb4874174ed3d14] 115,517,319 A9D93067
114-Hedging-Part_Two.mkv [9b3a8f2576ec6c8] 106,475,849 420B6025
044-Pandas_Visualization_Exercise_Solutions.mkv [c6d2d20bcac6248f] 91,075,467 BC24135B
086-Key_Financial_Topics.mkv [1f762cfa9a4515f6] 2,716,778 A995B94B
095-Welcome_to_the_Quantopian_Section.mkv [15c35311cbe01612] 2,195,469 DF91DC46
119-Futures_on_Quantopian_Part_Two.mkv [66beb61c38b4ae01] 209,924,261 DB064DAA
113-Hedging.mkv [ae38a448b69e31d7] 78,473,020 BC69026A
015-Introduction_to_NumPy.mkv [5275d9c2ba1d113a] 6,202,441 C399C895
106-Quantopian_Pipeline-Masking_and_Classifiers.mkv [5f321d7dce012378] 87,828,315 CD92C693
104-Quantopian_Pipelines_Factors.mkv [3a06fe7adf25f305] 110,302,777 6C538301
048-Quandl.mkv [f28d1136ad5b269f] 123,103,026 4EB5503E
008-Introduction_to_Crash_Course.mkv [1891eedbf2a998ee] 3,680,921 EE854157
059-Stock_Market_Analysis_Project_Solutions_Part_Three.mkv [d01648a2378d0bd1] 211,124,574 2D69B820
012-Python_Crash_Course_Exercises.mkv [cc791bf365a150e5] 33,313,167 EB44F143
053-Time_Shifts.mkv [4f55056ad17ecb8b] 76,248,499 6BB2C8D0
061-Welcome_to_Time_Series_Analysis.mkv [94ee64efcdee2ef4] 2,956,138 E2D8669D
014-Welcome_to_NumPy.mkv [8b73b2f3dc52f62] 2,006,153 1D6E3930
098-Quantopian_Algorithms_Basics_Part_Two.mkv [128c88896e3103a7] 76,222,596 E2AF301B
070-ACF_and_PACF.mkv [efd83c5e5394d8df] 29,832,399 62CCB301
010-Python_Crash_Course_Part_Two.mkv [f3f4bd748484b384] 37,944,607 77DAC855
064-Introduction_to_Statsmodels.mkv [a49c113bc9cc077a] 123,599,664 7F0FF1E5
101-Trading_Algorithm_Exercise.mkv [e55ec19aea653a6c] 14,797,802 D1376479
018-Numpy_Indexing.mkv [70669f07f7df61ee] 42,213,566 AC85F48F
096-Introduction_to_Quantopian.mkv [8040c254ebf9a244] 85,320,825 1FA69201
043-Pandas_Visualization_Exercise_Overview.mkv [2aceee9c1779ae60] 15,172,211 153A930B
036-Matplotlib_Basics-Part_One.mkv [cb545cc7334a6986] 75,914,437 B9ABD297
013-Python_Crash_Course_Exercise_Solutions.mkv [76be0a89e0ab66a0] 74,981,838 141626DC
112-Leverage.mkv [903b5c5615297edc] 97,663,142 17A86A93
085-Portfolio_Optimization_Code_Along_Three.mkv [a08b8a7d39c58ec0] 158,801,751 CEB24E83
066-EWMA_Theory.mkv [bc8d517cb63270a4] 7,819,049 9E8C7436
021-Welcome_to_Pandas.mkv [313f6ce6492d37cd] 1,907,149 466A2F75
116-Stock_Sentiment_Analysis_Project.mkv [71eeb439514fbbab] 78,241,973 F627A694
011-Python_Crash_Course_Part_Three.mkv [9a1ea0f406d0c9d4] 63,712,991 711672E4
supplemental_assets 0 00000000
Total size: 6,904,673,110
RAR Recovery
Not Present
Labels UNKNOWN
RSS | IRC | API | Wiki | Help | Contact | srrDB © 2011-2024 (1668)
Execution time: 0.0378 - Memory usage: 0.78MB
Design and development: srrDB Team
srrDB is an historical record of the warez scene. We do not offer illegal downloads nor links to these works. All meta data gets added by our awesome users. Photographs or pictures can be part of these historical records, deemed fair use (news reporting and research) and are only a part of the complete work, but copyrights are owned by their respective creators or right holders.