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Imagecompletion DcganImage completion using deep convolutional generative adversarial nets in tensorflow
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Coms4995 S18COMS W4995 Applied Machine Learning - Spring 18
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Ml Hub🧰 Multi-user development platform for machine learning teams. Simple to setup within minutes.
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PracticaldlA Practical Guide to Deep Learning with TensorFlow 2.0 and Keras materials for Frontend Masters course
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Covid19Analyses about the COVID-19 virus
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Covid 19 Eda TutorialThis tutorial's purpose is to introduce people to the [2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE](https://github.com/CSSEGISandData/COVID-19) and how to explore it using some foundational packages in the Scientific Python Data Science stack.
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AnomaliesinoptionsIn this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
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Appearance FlowA deep learning framework for synthesizing novel views of objects and scenes
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CpndetCorner Proposal Network for Anchor-free, Two-stage Object Detection
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Fastai audio[DEPRECATED] 🔊️ Audio with fastaiv1
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ReferReferring Expression Datasets API
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CorusLinks to Russian corpora + Python functions for loading and parsing
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Nyc TransportA Unified Database of NYC transport (subway, taxi/Uber, and citibike) data.
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DatageneDataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)
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Data Science TemplateA starter template for Equinor data science / data engineering projects
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Stock Price PredictorThis project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
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VdeVariational Autoencoder for Dimensionality Reduction of Time-Series
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D6tstackQuickly ingest messy CSV and XLS files. Export to clean pandas, SQL, parquet
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HeckeldiffA fast Swift diffing library.
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DiffimgDifferentiate images in python - get a ratio or percentage difference, and generate a diff image
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Deeplearning ImageIntroduction to Deep Learning for Image Recognition
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Data structures and algorithms in python📖 Worked Solutions of "Data Structures & Algorithms in Python", written by Michael T. Goodrich, Roberto Tamassia and Michael H. Goldwasser. ✏️
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BasenjiSequential regulatory activity predictions with deep convolutional neural networks.
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Repo 2018Deep Learning Summer School + Tensorflow + OpenCV cascade training + YOLO + COCO + CycleGAN + AWS EC2 Setup + AWS IoT Project + AWS SageMaker + AWS API Gateway + Raspberry Pi3 Ubuntu Core
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