mltest

17 rows where Animated/Interactive = "TRUE"

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Suggested facets: Author, Rating , Notes, Paper Link, Blog Link, Drive Link, Glitch Link, MNIST, ImageNet, CIFAR, TensorflowJS, ConvNetJS, Colab, Glitch, Python, JavaScript, CNN, Transformer, Image, NLP, Classification

Link rowid ▼ Accension Name Author Rating Notes Animated/Interactive Demo Link Paper Link Blog Link Drive Link Glitch Link MNIST ImageNet CIFAR Other Tensorflow TensorflowJS Torch ConvNetJS SciKit Numpy Colab Glitch Python JavaScript CNN MLP Transformer RNN Image NLP Classification
1 1 1 Classify MNIST digits with a Convolutional Neural Network Karpathy 5   TRUE https://cs.stanford.edu/people/karpathy/convnetjs/demo/mnist.html         TRUE             TRUE       TRUE   TRUE TRUE       TRUE    
2 2 2 Classify CIFAR-10 with Convolutional Neural Network Karpathy 5   TRUE https://cs.stanford.edu/people/karpathy/convnetjs/demo/cifar10.html             TRUE         TRUE       TRUE   TRUE TRUE       TRUE    
3 3 3 ConvNetJS Deep Learning in your browser Karpathy 5   TRUE https://cs.stanford.edu/people/karpathy/convnetjs/         TRUE TRUE           TRUE           TRUE         TRUE   TRUE
4 4 4 Tensorflow Playground   5 Stores a specific NN in the url TRUE https://playground.tensorflow.org/ https://arxiv.org/abs/1708.03788 https://cloud.google.com/blog/products/ai-machine-learning/understanding-neural-networks-with-tensorflow-playground                           TRUE   TRUE             TRUE
6 6 6 Softmax Demo   3 Google Sheet TRUE https://docs.google.com/spreadsheets/d/1A0jMJD4rw1it2S8s7Qv7VWADZnD18d8bs3KwPtyBPzg/edit?usp=sharing                                                 TRUE
7 7 7 Deep Visualization Toolbox Yosinski 4 I would like to use this since it takes realtime input from a camera but installing it is involved. The video is worth watching. It uses a pre-trained network similar to AlexNet TRUE https://yosinski.com/deepvis https://arxiv.org/abs/1506.06579                               TRUE           TRUE   TRUE
8 8 8 Teachable Machine   5   TRUE https://teachablemachine.withgoogle.com/ https://dl.acm.org/doi/10.1145/3334480.3382839         TRUE       TRUE           TRUE   TRUE TRUE       TRUE   TRUE
11 11 11 Word2Vec   4 JSON weights. This is fun because it's so easy to understand what it's doing. It's all JavaScript. The weights are in a JSON file. There's no training. That's already been done to create the weights. TRUE https://turbomaze.github.io/word2vecjson/ https://github.com/turbomaze/word2vecjson     https://glitch.com/edit/#!/word2vec-demo-no-libs                           TRUE              
12 12 12 MNIST Digit Recognizer Deotte 4 JSON weights. TRUE https://www.ccom.ucsd.edu/~cdeotte/programs/MNIST.html       https://glitch.com/edit/#!/mnist-digit-recognizer?path=MNIST.html%3A644%3A35 TRUE                     TRUE   TRUE         TRUE    
13 13 13 Neural Network Playground Deotte 5 Simpler than Tensorflow Playground TRUE https://www.ccom.ucsd.edu/~cdeotte/programs/neuralnetwork.html                                   TRUE             TRUE
14 14 14 Classifier Playground Deotte 3   TRUE https://www.ccom.ucsd.edu/~cdeotte/programs/classify.html                                   TRUE             TRUE
16 16 16 CNN Explainer   4 Learn Convolutional Neural Network (CNN) in your browser! TRUE https://poloclub.github.io/cnn-explainer/ https://arxiv.org/abs/2004.15004 https://github.com/poloclub/cnn-explainer         TRUE     TRUE               TRUE TRUE       TRUE   TRUE
17 17 17 Deep Convolustional Neural Net   4 In Google Sheets TRUE https://docs.google.com/spreadsheets/d/1SwfVctd4TjdN2S8BL09ktpQN_41sARYzD3NEHyr-8Z0/edit?usp=sharing   https://towardsdatascience.com/building-a-deep-neural-net-in-google-sheets-49cdaf466da0 https://docs.google.com/spreadsheets/d/1_0a6MkcGNvWOkI6hYqrm-ZAyxQD3e9xgzLdWgNp5a2E/edit?usp=sharing   TRUE                           TRUE       TRUE   TRUE
20 20 20 CS231n Convolutional Demo   5 Great demo! It helped me understand CNN details TRUE https://cs231n.github.io/convolutional-networks/#:~:text=architectures%20section%20below.-,Convolution%20Demo,-.%20Below%20is%20a   https://cs231n.github.io/convolutional-networks/                                 TRUE       TRUE    
22 22 22 ECCO readme.md examples.ipynb Alammar 4   TRUE https://colab.research.google.com/github/jalammar/ecco/blob/main/notebooks/readme.md%20examples.ipynb https://aclanthology.org/2021.acl-demo.30/   https://docs.google.com/spreadsheets/d/1KALWW9jxoicGoos-kAhDAsET94hY6Oo85EVsl_9StwI/edit?usp=sharing                       TRUE   TRUE       TRUE     TRUE TRUE
23 23 23 Interfaces for Explaining Transformer Language Models Alammar 5 Uses Ecco TRUE https://jalammar.github.io/explaining-transformers/ https://aclanthology.org/2021.acl-demo.30/                               TRUE TRUE     TRUE     TRUE TRUE
24 24 24 05- Neuron Factors.ipynb Alammar 5 Uses Ecco TRUE https://colab.research.google.com/github/jalammar/ecco/blob/main/notebooks/Ecco_Neuron_Factors.ipynb https://aclanthology.org/2021.acl-demo.30/                           TRUE   TRUE       TRUE     TRUE  

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CREATE TABLE [mltest] (
   [Accension] TEXT,
   [Name] TEXT,
   [Author] TEXT,
   [Rating ] TEXT,
   [Notes] TEXT,
   [Animated/Interactive] TEXT,
   [Demo Link] TEXT,
   [Paper Link] TEXT,
   [Blog Link] TEXT,
   [Drive Link] TEXT,
   [Glitch Link] TEXT,
   [MNIST] TEXT,
   [ImageNet] TEXT,
   [CIFAR] TEXT,
   [Other] TEXT,
   [Tensorflow] TEXT,
   [TensorflowJS] TEXT,
   [Torch] TEXT,
   [ConvNetJS] TEXT,
   [SciKit] TEXT,
   [Numpy] TEXT,
   [Colab] TEXT,
   [Glitch] TEXT,
   [Python] TEXT,
   [JavaScript] TEXT,
   [CNN] TEXT,
   [MLP] TEXT,
   [Transformer] TEXT,
   [RNN] TEXT,
   [Image] TEXT,
   [NLP] TEXT,
   [Classification] TEXT
);