Deeplearning深度学习入门教程, 优秀文章, Deep Learning Tutorial
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D2l VnMột cuốn sách tương tác về học sâu có mã nguồn, toán và thảo luận. Đề cập đến nhiều framework phổ biến (TensorFlow, Pytorch & MXNet) và được sử dụng tại 175 trường Đại học.
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D2l EnInteractive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
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D2l PytorchThis project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Stars: ✭ 3,810 (+3953.19%)
DjlAn Engine-Agnostic Deep Learning Framework in Java
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djlAn Engine-Agnostic Deep Learning Framework in Java
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deepspeech.mxnetA MXNet implementation of Baidu's DeepSpeech architecture
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kaggleKaggle solutions
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softmaxfocallossthe loss function in Aritcal ‘Focal Loss for Dense Object Detection‘’
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AIML-Human-Attributes-Detection-with-Facial-Feature-ExtractionThis is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.
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lux-ai-2021My published benchmark for a Kaggle Simulations Competition
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sfd.gluoncvReproduce SFD face detector using gluon-cv
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NonLocalandSEnetMXNet implementation of Non-Local and Squeeze-Excitation network
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data-visualization-deck-glA experiment to visualize Tree in NewYork and Flight record data. Using Deck.gl and Kaggle
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Apartment-Interest-PredictionPredict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.
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PracticalMachineLearningA collection of ML related stuff including notebooks, codes and a curated list of various useful resources such as books and softwares. Almost everything mentioned here is free (as speech not free food) or open-source.
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ml-workflow-automationPython Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.
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data-science-learning📊 All of courses, assignments, exercises, mini-projects and books that I've done so far in the process of learning by myself Machine Learning and Data Science.
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mloperatorMachine Learning Operator & Controller for Kubernetes
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dynamic-training-with-apache-mxnet-on-awsDynamic training with Apache MXNet reduces cost and time for training deep neural networks by leveraging AWS cloud elasticity and scale. The system reduces training cost and time by dynamically updating the training cluster size during training, with minimal impact on model training accuracy.
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capsnet.mxnetMXNet implementation of CapsNet
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MXNetDotNet.NET wrapper for Apache MXNet written in C#
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OpSummary.MXNetA tool to count operators and parameters of your MXNet-Gluon model.
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Algorithmml & dl & kaggle
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kuzushiji-recognitionKuzushiji Recognition Kaggle 2019. Build a DL model to transcribe ancient Kuzushiji into contemporary Japanese characters. Opening the door to a thousand years of Japanese culture.
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kaggle-toolsSome tools that I often find myself using in Kaggle challenges.
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rawrExtract raw R code directly from webpages, including Github, Kaggle, Stack Overflow, and sites made using Blogdown.
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AAAI 2019 EXAMOfficial implementation of "Explicit Interaction Model towards Text Classification"
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gluon2pytorchGluon to PyTorch deep neural network model converter
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Nest💡 A flexible tool for building and sharing deep learning modules.
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QuoraKaggle: Quora Insincere Questions Classification - detect toxic content to improve online conversations
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lipnetLipNet with gluon
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mtomoMultiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
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fastknnFast k-Nearest Neighbors Classifier for Large Datasets
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insightocrMXNet OCR implementation. Including text recognition and detection.
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intel-cervical-cancerTeam GuYuShiJie~'s 15th (top 2%) solution of cervix type classification in Kaggle 2017 competition, using PyTorch.
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kaggle-camera-model-identificationCode for reproducing 2nd place solution for Kaggle competition IEEE's Signal Processing Society - Camera Model Identification
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DLARMDLARM: Dissertation for Computer Science Masters Degree at UFRGS
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PyData-Pseudolabelling-KeynoteAccompanying notebook and sources to "A Guide to Pseudolabelling: How to get a Kaggle medal with only one model" (Dec. 2020 PyData Boston-Cambridge Keynote)
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