The 6 most useful Machine Learning projects of the past year (2018)

Such word vectors can be used for many tasks including text classification, summarisation, and translationAutoKerasAuto-Keras is an open source software library for automated machine learning (AutoML)..It was developed by DATA Lab at Texas A&M University and community contributors..The ultimate goal of AutoML is to provide easily accessible deep learning tools to domain experts with limited data science or machine learning background..Auto-Keras provides functions to automatically search for the best architecture and hyperparameters for deep learning models.DopamineDopamine is a research framework for fast prototyping of reinforcement learning algorithms, created by Google..It aims to be flexible yet easy to use, implementing standard RL algorithms, metrics, and benchmarks.According to Dopamine’s documentation, their design principles are:Easy experimentation:To help new users run benchmark experimentsFlexible development: To facilitate the generation of new and innovative ideas for new usersCompact and reliable: Provide implementations for some of the older and more popular algorithmsReproducible: Ensure results are reproduciblevid2vidThe vid2vid project is a public Pytorch implementation of Nvidia’s state-of-the-art video-to-video synthesis algorithm..The goal with video-to-video synthesis is to learn a mapping function from an input source video (e.g., a sequence of semantic segmentation masks) to an output photo-realistic video that precisely depicts the content of the source video.The great thing about this library is its options: it provides several different vid2vid applications including self-driving / urban scenes, faces, and human pose..It also comes with extensive instructions and capabilities including dataset loading, task evaluation, training functionality, and multi-gpu!Converting a segmentation map to a real imageHonourable mentionsChatterBot: machine learning for conversational dialog engine and creating chat botsKubeflow: machine learning toolkit for Kubernetesimgaug: image augmentation for deep learningimbalanced-learn: a python package under scikit learn specifically for tacking imbalanced datasetsmlflow: open source platform to manage the ML lifecycle, including experimentation, reproducibility and deployment.AirSim: simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & ResearchLike to learn?Follow me on twitter where I post all about the latest and greatest AI, Technology, and Science!. More details

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