log

data.json

{"strongartificialintelligence": {"A post mortem analysis of a Data Science approach for determining the existence and decay patterns of the Higgs boson.\nhttps://kasperfred.com/posts/post-mortem-analysis-of-my-final-year-project": true}, "MLNgCourseraUnoff": {"We examine how the popular framework sklearn can be used with the iris dataset to classify species of flowers. We go through all the steps required to make a machine learning model from start to end.\nhttps://kasperfred.com/posts/creating-your-first-machine-learning-classification-model-in-sklearn": true}, "DeepAI": {"A practical application of convolutional neural networks.\nhttps://kasperfred.com/posts/looking-at-german-traffic-signs": true}, "BigDataPakistan": {"Why are neural networks so slow?\nhttps://kasperfred.com/posts/computational-complexity-of-neural-networks": true}, "DataMining": {"We examine 'genius' internet memes and consider how we might apply techniques from statistical learning to build an abstract solver.\nhttps://kasperfred.com/posts/solving-only-1-can-answer-this-problems-with-machine-learning": true}, "DeepNetGroup": {"\nhttps://kasperfred.com/posts/how-learning-to-program-is-like-being-alone-on-mars": true}, "DataScienceGroup": {"\nhttps://kasperfred.com/posts/the-future-of-deep-learning": true}, "102192946621778": {"A collection of commonly used machine learning terms, and what they mean.\nhttps://kasperfred.com/posts/machine-learning-glossary": true}, "213717218645110": {"We examine Google's open source library Tensorflow, and go through its components to understand how it can be used to create scalable machine learning models.\nhttps://kasperfred.com/posts/introduction-to-tensorflow-as-a-computational-library": true}, "big.data.egypt": {"Deriving the mathematics behind backpropagation.\nhttps://kasperfred.com/posts/how-does-backpropagation-work": true}, "machinelearningforum": {"Translation: I answer your machine learning questions\nhttps://kasperfred.com/posts/an-unheard-serenade-of-cyanidic-thoughts": true}, "142114343040195": {"Overview and introduction to feed forward neural networks. Forward propagation is discussed in detail, and we see how we might train a network.\nhttps://kasperfred.com/posts/what-is-a-neural-network": true}, "AnalyticsEdge": {"All fields have myths, and data science is no different.\nhttps://kasperfred.com/posts/the-machine-learning-myth": true}, "DeepLearnng": {"Methods of analysing the run-time complexity of algorithms.\nhttps://kasperfred.com/posts/just-how-fast-is-your-algorithm": true}}