About Gist https://www.labnol.org/internet/github-gist-tutorial/28499/ (blog)SVMs http://blog.hackerearth.com/simple-tutorial-svm-parameter-tuning-python-r Background subtraction https://github.com/stgstg27/Background-Subtraction ==Visualizaion== Basic data visualization maps https://mubaris.com/2017/09/26/introduction-to-data-visualizations-using-python/ More visualisation https://github.com/ContextLab/storytelling-with-data/blob/master/data-stories/education/tutorial.ipynb Visualisation with pandas https://www.kaggle.com/residentmario/univariate-plotting-with-pandas/notebook Average Precision as AU-PR curve https://sanchom.wordpress.com/tag/average-precision/ https://medium.com/@jonathan_hui/map-mean-average-precision-for-object-detection-45c121a31173 ==TSNE== Misreading TSNE plots https://distill.pub/2016/misread-tsne/ ==CNN/DL== SGD >> Adam for Generalisation: https://arxiv.org/abs/1705.08292 https://shaoanlu.wordpress.com/2017/05/29/sgd-all-which-one-is-the-best-optimizer-dogs-vs-cats-toy-experiment/ CS231n Gradient check http://cs231n.github.io/neural-networks-3/#gradcheck Open Images dataset maker https://github.com/aferriss/openImageDownloader DL Mistakes http://ppwwyyxx.com/2017/Unawareness-Of-Deep-Learning-Mistakes/#more Training classification network- kaggle10th https://towardsdatascience.com/image-classification-challenge-using-transfer-learning-and-deep-learning-studio-2e89c3189fcf Kaggle4th classification tips https://www.kaggle.com/c/cdiscount-image-classification-challenge/discussion/45733 Kaggle #1 classification tips https://medium.com/neuralspace/kaggle-1-winning-approach-for-image-classification-challenge-9c1188157a86 Warm restarts paper https://arxiv.org/pdf/1608.03983.pdf Optimal Learning rate https://towardsdatascience.com/estimating-optimal-learning-rate-for-a-deep-neural-network-ce32f2556ce0 Hyperparams https://towardsdatascience.com/artificial-intelligence-hyperparameters-48fa29daa516 On Convolutional NN (blog)About CNN developments through the years- https://adeshpande3.github.io/adeshpande3.github.io/The-9-Deep-Learning-Papers-You-Need-To-Know-About.html Understanding Convolutional operation in CNN- https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/ VIsualising MNIST & understanding Dimensionality Reduction http://colah.github.io/posts/2014-10-Visualizing-MNIST/ Lao ML notes http://claoudml.strikingly.com Tfrecords https://planspace.org/20170323-tfrecords_for_humans/ https://planspace.org/20170403-images_and_tfrecords/ Google ML crash course https://developers.google.com/machine-learning/crash-course/ml-intro (blog)R-CNN to Mask R-CNN https://blog.athelas.com/a-brief-history-of-cnns-in-image-segmentation-from-r-cnn-to-mask-r-cnn-34ea83205de4 (blog)Fast, Faster R-CNN https://tryolabs.com/blog/2018/01/18/faster-r-cnn-down-the-rabbit-hole-of-modern-object-detection/ https://jhui.github.io/2017/03/15/Fast-R-CNN-and-Faster-R-CNN/ (blog)RoI pooling https://blog.deepsense.ai/region-of-interest-pooling-explained/ (blog)Receptive field arithmetic https://medium.com/mlreview/a-guide-to-receptive-field-arithmetic-for-convolutional-neural-networks-e0f514068807 (SO answer) Anchors and faster-RCNN https://stats.stackexchange.com/questions/265875/anchoring-faster-rcnn (SO Answer) Cnn filter weights initialization https://stats.stackexchange.com/questions/200513/how-to-initialize-the-elements-of-the-filter-matrix (blog)cross entropy http://rdipietro.github.io/friendly-intro-to-cross-entropy-loss/ (article)Cross Entropy losses - categorical, focal https://gombru.github.io/2018/05/23/cross_entropy_loss/ (article)Transfer Learning/Fine tune CNN http://cs231n.github.io/transfer-learning/ (coursera)CNN/NMS/Object Detection https://www.coursera.org/learn/convolutional-neural-networks/lecture/dvrjH/non-max-suppression (medium article)Image augmentation with tf https://medium.com/ymedialabs-innovation/data-augmentation-techniques-in-cnn-using-tensorflow-371ae43d5be9 https://towardsdatascience.com/image-augmentation-for-deep-learning-using-keras-and-histogram-equalization-9329f6ae5085 Also an augmentor library https://github.com/mdbloice/Augmentor On Bounding Box Regression https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=4949&context=open_access_etds Siamese Network Image similarity Tensorflow series https://blog.metaflow.fr/tensorflow-a-primer-4b3fa0978be3 ==PYTHON== Python Tutorial https://www.python-course.eu/ Guide to import https://chrisyeh96.github.io/2017/08/08/definitive-guide-python-imports.html Amazing things about python https://nedbatchelder.com/text/names.html https://stackoverflow.com/questions/5131538/slicing-a-list-in-python-without-generating-a-copy Why self is here to stay http://neopythonic.blogspot.in/2008/10/why-explicit-self-has-to-stay.html The init self confusion https://stackoverflow.com/questions/625083/python-init-and-self-what-do-they-do (website)Learn Python http://python.net/~goodger/projects/pycon/2007/idiomatic/handout.html ==KAGGLE== kaggle ensemble guide https://mlwave.com/kaggle-ensembling-guide/ (blog)Kaggle Zoo Solution http://benanne.github.io/2014/04/05/galaxy-zoo.html Setting up the computer https://www.kaggle.com/c/allstate-claims-severity/discussion/26423#150025