data: mltest: 24 rows

24 rows

descending

Link	rowid ▼	Accension	Name	Author	Rating	Notes	Animated/Interactive	Demo Link	Paper Link	Blog Link	Drive Link	Glitch Link	MNIST	ImageNet	CIFAR	Tensorflow	TensorflowJS	ConvNetJS	Numpy	Colab	Glitch	Python	JavaScript	CNN	MLP	Transformer	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
5	5	5	Looking inside a digit recognizer		4	Demo of Tfjs-Vis		https://storage.googleapis.com/tfjs-vis/mnist_internals/dist/index.html				https://glitch.com/edit/#!/looking-inside-mnist-demo?path=README.md%3A7%3A73	TRUE				TRUE				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
9	9	9	A Neural Network in 11 lines of Python	Trask	4	A bare bones neural network implementation to describe the inner workings of backpropagation. Uses Numpy		https://glitch.com/edit/console.html?minimal-ml-nn-11-lines-python-code											TRUE	TRUE	TRUE	TRUE
10	10	10	No hidden layer MNIST	Shook	5	Show that a 10 neuron classifier can do pretty well on MNIST		https://colab.research.google.com/drive/1HlIyYxVI2qszE4P0siZ9w2-ALDORvtV6		https://hyp.is/BFsmSC1EEey18PemMVxPpA/cloud.google.com/blog/products/ai-machine-learning/understanding-neural-networks-with-tensorflow-playground	https://colab.research.google.com/drive/1HlIyYxVI2qszE4P0siZ9w2-ALDORvtV6		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
15	15	15	Universal Sentence Encoder		3	Minimal		https://hpssjellis.github.io/beginner-tensorflowjs-examples-in-javascript/tfjs-models/universal-sentence-encoder/index.html	https://arxiv.org/abs/1803.11175			https://glitch.com/edit/#!/universal-sentence-encoder-demo?path=README.md%3A1%3A0											TRUE			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
18	18	18	MLP-Mixer, gMLP, FNET	Khalid Salama	3	MLP-Mixer, FNet, and gMLP models for CIFAR-100 image classification., It is to show simple implementations of their main building blocks.		https://keras.io/examples/vision/mlp_image_classification/	https://arxiv.org/abs/2105.01601		https://colab.research.google.com/drive/1gJj2xAiexNj99po95uRFesc0ek-wZwER#scrollTo=czIFW9bQcj_M				TRUE	TRUE				TRUE		TRUE			TRUE		TRUE		TRUE
19	19	19	MLP-Mixer image classification		3	MLP-Mixer		https://colab.research.google.com/github/sayakpaul/MLPMixer-jax2tf/blob/main/classification.ipynb	https://arxiv.org/abs/2105.01601	https://tfhub.dev/sayakpaul/mixer_b16_i1k_classification/1	https://colab.research.google.com/drive/1I2-x_P0P9uFzF2NzhtQWho4dokIlD9F9?usp=sharing
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
21	21	21	Minimal Bert Q&A demo		3	Take quite a few seconds to get results		https://bert-qna.glitch.me/		https://github.com/tensorflow/tfjs-models/tree/master/qna		https://glitch.com/edit/#!/bert-qna					TRUE				TRUE		TRUE			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
);