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Title: GitHub - Fatty-Ricky/dl_tutorials: Deep learning tutorials (2nd ed.)

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X Title: GitHub - Fatty-Ricky/dl_tutorials: Deep learning tutorials (2nd ed.)

Description: Deep learning tutorials (2nd ed.). Contribute to Fatty-Ricky/dl_tutorials development by creating an account on GitHub.

Open Graph Description: Deep learning tutorials (2nd ed.). Contribute to Fatty-Ricky/dl_tutorials development by creating an account on GitHub.

X Description: Deep learning tutorials (2nd ed.). Contribute to Fatty-Ricky/dl_tutorials development by creating an account on GitHub.

Opengraph URL: https://github.com/Fatty-Ricky/dl_tutorials

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https://patch-diff.githubusercontent.com/Fatty-Ricky/dl_tutorials#deep-learning-tutorials
https://patch-diff.githubusercontent.com/Fatty-Ricky/dl_tutorials#week1
Deep learning intro.https://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week1-1b%20Deep%20learning%20intro.pptx
Python basicshttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week1-1c%20Python%20basic%20(basic_python).pptx
Let's play with images & MNISThttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week1-1d%20MNIST%20(basic_mnist)%20and%20image%20processing%20(basic_imgprocess).pptx
Terminologieshttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week1-2a%20Terminologies.pptx
https://patch-diff.githubusercontent.com/Fatty-Ricky/dl_tutorials#week2---do-you-know-deep-learning
CNN and AlexNethttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week1-2b%20CNN%20and%20AlexNet.pptx
TensorFlow basicshttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week1-2c%20TensorFlow%20basic%20(basic_tensorflow).pptx
Logistic regressionhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week1-2d%20Logistic%20regression%20(logistic_regression_mnist).pptx
GoogLeNethttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-1b%20GoogLeNet.pptx
AlphaGo: MCTS+CNNhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-1c%20AlphaGo.pptx
Let's implement MLP!https://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-1d%20Multi-layer%20perceptron%20(mlp_mnist_simple).pptx
Let's play with you OWN DATASEThttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-1e%20Generate%20your%20own%20dataset%20(basic_gendataset).pptx
Regularization methodshttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-1f%20Regulaziation.pptx
Optimization methodshttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-2a%20Optimizaiton%20methods.pptx
Restricted Boltzmann Machinehttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-2b%20Restricted%20Boltzmann%20machine.pptx
Let's implement denoising autoencoderhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week2-2c%20Denoising%20auto-encoder%20(dae_mnist).pptx
https://patch-diff.githubusercontent.com/Fatty-Ricky/dl_tutorials#week3---cnn-basics
Semantic segmentation: FCN, DeconvNet, DeepLab with atrous convhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week3-1b%20Semantic%20segmentation%20details%2BSOTA.pptx
Let's implement a simple CNNhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week3-1c%20What%20is%20CNN%20(cnn_mnist_simple).pptx
Let's implement a basic CNNhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week3-1d%20Powerful%20CNN%20(cnn_mnist_basic).pptx
Let's implement semantic segmentationhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week3-1e%20Implementing%20semantic%20segmentation%20(semseg_basic).pptx
Weakly supervised localization: Global average poolinghttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week3-2a%20Weakly%20supervised%20learning.pptx
Implement MLP and CNN on your OWN DATASEThttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week3-2b%20Use%20your%20own%20dataset%20(basic_gendataset%2C%20lr%2C%20mlp%2C%20cnn).pptx
Denoising deconvolutional neural networkhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week3-2c%20Denoising%20deconvolutional%20network.pptx
https://patch-diff.githubusercontent.com/Fatty-Ricky/dl_tutorials#week4---cnn-applications--rnn-basics
Image detection (RCNN, SPPnet, FastRCNN, FasterRCNN)https://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week4-1a%20Image%20detection%20(RCNN%2C%20SPPnet%2C%20FastRCNN%2C%20FasterRCNN).pptx
Other detections (YOLO, AttentionNet)https://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week4-1b%20Other%20dections%20(YOLO%2C%20AttentionNet).pptx
Let's use TensorBoardshttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week4-1c%20TensorBoard.pptx
RNN from Colah's bloghttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week4-2a%20RNN%20(colah%20blog).pptx
Visual QnA: DPPnet + MCBP!https://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week4-2b%20Visual%20QnA.pptx
Super resolutionhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week4-2c%20Super%20resolution.pptx
Deep reinforcement learninghttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week4-2d%20Deep%20reinforcement%20learning.pptx
https://patch-diff.githubusercontent.com/Fatty-Ricky/dl_tutorials#week5---rnn-applications
RNN basic + handwriting generationhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week5-1a%20RNN%20%2B%20LSTM%20%2B%20Handwrting%20Gen.pptx
Let's implement RNNshttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week5-1b%20Implementing%20RNN%20(rnn_mnist_simple).pptx
Let's implement Word2vechttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week5-2a%20Word2Vec%20again.pptx
Image captioning: Show and Tell + Show, attend and tellhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week5-2b%20Image%20Captioning.pptx
char-rnn + how can we use Hangul?https://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week5-2c%20Hangul-RNN.pptx
https://patch-diff.githubusercontent.com/Fatty-Ricky/dl_tutorials#week6---deep-learning-is-so-fun
Residual network and some analysishttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week6-1a%20Residual%20Networks%20and%20Analysis.pptx
Neural Style: Texture synsthesis+Inverting CNNhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week6-1b%20Neural%20Style.pptx
Let's implement neural stylehttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week6-1c%20Neural%20Style%20Code.pptx
Bayesian optimizationhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week6-2a%20Bayesian%20Optimization.pptx
Adversaral attack?https://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week6-2b%20Adversarial%20Attack.pptx
Generative adversarial networkhttps://github.com/sjchoi86/dl_tutorials/blob/master/presentations/Week6-2c%20Generative%20Adversarial%20Network.pptx
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