Anime Gan TensorflowThe BIGGAN based Anime generation implemented with tensorflow. All training data has been open sourced.
Stars: ✭ 180 (-25.93%)
Zoom Learn Zoomcomputational zoom from raw sensor data
Stars: ✭ 224 (-7.82%)
Andrew Ng NotesThis is Andrew NG Coursera Handwritten Notes.
Stars: ✭ 180 (-25.93%)
Deeplearning.ai该存储库包含由deeplearning.ai提供的相关课程的个人的笔记和实现代码。
Stars: ✭ 181 (-25.51%)
Mxnet The Straight DopeAn interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.
Stars: ✭ 2,551 (+949.79%)
Introduction To Data Science In PythonThis repository contains Ipython notebooks of assignments and tutorials used in the course introduction to data science in python, part of Applied Data Science using Python Specialization from University of Michigan offered by Coursera
Stars: ✭ 179 (-26.34%)
InfiniteboostInfiniteBoost: building infinite ensembles with gradient descent
Stars: ✭ 180 (-25.93%)
Gan steerabilityOn the "steerability" of generative adversarial networks
Stars: ✭ 225 (-7.41%)
Keraspp코딩셰프의 3분 딥러닝, 케라스맛
Stars: ✭ 178 (-26.75%)
Mlapp cn code《Machine Learning: A Probabilistic Perspective》(Kevin P. Murphy)中文翻译和书中算法的Python实现。
Stars: ✭ 204 (-16.05%)
Covid Chestxray DatasetWe are building an open database of COVID-19 cases with chest X-ray or CT images.
Stars: ✭ 2,759 (+1035.39%)
PapergraphAI/ML citation graph with postgres + graphql
Stars: ✭ 178 (-26.75%)
TutorialTutorial covering Open Source tools for Source Separation.
Stars: ✭ 223 (-8.23%)
Screenshot To CodeA neural network that transforms a design mock-up into a static website.
Stars: ✭ 13,561 (+5480.66%)
Awesome PandasA collection of resources for pandas (Python) and related subjects.
Stars: ✭ 232 (-4.53%)
CatdcganA DCGAN that generate Cat pictures 🐱💻
Stars: ✭ 177 (-27.16%)
ExamplesHome for Elasticsearch examples available to everyone. It's a great way to get started.
Stars: ✭ 2,427 (+898.77%)
DeeplearningcoursecodesNotes, Codes, and Tutorials for the Deep Learning Course <which I taught at ChinaHadoop>
Stars: ✭ 241 (-0.82%)
Notebook📒 notebook
Stars: ✭ 177 (-27.16%)
Yolo Digit DetectorImplemented digit detector in natural scene using resnet50 and Yolo-v2. I used SVHN as the training set, and implemented it using tensorflow and keras.
Stars: ✭ 205 (-15.64%)
Ocaml JupyterAn OCaml kernel for Jupyter (IPython) notebook
Stars: ✭ 177 (-27.16%)
Pytorch Vq VaePyTorch implementation of VQ-VAE by Aäron van den Oord et al.
Stars: ✭ 204 (-16.05%)
Tensorflow Ml Nlp텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)
Stars: ✭ 176 (-27.57%)
EggEGG: Emergence of lanGuage in Games
Stars: ✭ 175 (-27.98%)
DragonnA toolkit to learn how to model and interpret regulatory sequence data using deep learning.
Stars: ✭ 222 (-8.64%)
Cs1001.pyRecitation notebooks for Extended Introduction to Computer Science with Python as Tel-Aviv University
Stars: ✭ 176 (-27.57%)
Compact bilinear poolingMatConvNet and Caffe repo with compact bilinear and bilinear pooling functionality added
Stars: ✭ 176 (-27.57%)
Blogfor code created as part of http://studywolf.wordpress.com
Stars: ✭ 236 (-2.88%)
S3contentsA S3 backed ContentsManager implementation for Jupyter
Stars: ✭ 175 (-27.98%)
Aind NlpCoding exercises for the Natural Language Processing concentration, part of Udacity's AIND program.
Stars: ✭ 202 (-16.87%)
MozartAn optical music recognition (OMR) system. Converts sheet music to a machine-readable version.
Stars: ✭ 241 (-0.82%)
Pycon Nlp In 10 LinesRepository for PyCon 2016 workshop Natural Language Processing in 10 Lines of Code
Stars: ✭ 242 (-0.41%)
Loss toolbox PytorchPyTorch Implementation of Focal Loss and Lovasz-Softmax Loss
Stars: ✭ 240 (-1.23%)
Numerical Linear Algebra V2Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program
Stars: ✭ 241 (-0.82%)
R C3dcode for R-C3D
Stars: ✭ 238 (-2.06%)
Pydqcpython automatic data quality check toolkit
Stars: ✭ 233 (-4.12%)
Handson Ml2A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Stars: ✭ 18,554 (+7535.39%)
IridescentSolid data structure and algorithms
Stars: ✭ 188 (-22.63%)