Javascript30 StimulusWes Bos π₯ Javascript30 converted to Stimulus JS πππ
Stars: β 37 (-63.37%)
Super Resolution cnn Implementation of 'Image Super-Resolution using Deep Convolutional Network'
Stars: β 27 (-73.27%)
D3This is the repository for my course, Learning Data Visualization with D3.js on LinkedIn Learning and Lynda.com.
Stars: β 64 (-36.63%)
IloOfficial implementation: Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Stars: β 71 (-29.7%)
Uc Davis Cs Exams Analysisπ Regression and Classification with UC Davis student quiz data and exam data
Stars: β 33 (-67.33%)
CfsrcnnCoarse-to-Fine CNN for Image Super-Resolution (IEEE Transactions on Multimedia,2020)
Stars: β 84 (-16.83%)
BootstrapRepository for my tutorial course: Bootstrap 3 Essential Training on LinkedIn Learning and Lynda.com.
Stars: β 14 (-86.14%)
VideosuperresolutionA collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.
Stars: β 1,118 (+1006.93%)
Rcan TensorflowImage Super-Resolution Using Very Deep Residual Channel Attention Networks Implementation in Tensorflow
Stars: β 43 (-57.43%)
Vuejs TrainingVueJS training including Vue ecosystem: HTTP (Axios), Vuex, Unit Testting (Jest)...
Stars: β 6 (-94.06%)
Torch Srgantorch implementation of srgan
Stars: β 76 (-24.75%)
Ml Classify Text JsMachine learning based text classification in JavaScript using n-grams and cosine similarity
Stars: β 38 (-62.38%)
TrainingdaysAzure Developer College's application development training days content.
Stars: β 86 (-14.85%)
ElectronThis is the repository for my course, Electron: Building Cross Platform Desktop Apps on LinkedIn Learning and Lynda.com.
Stars: β 69 (-31.68%)
Super ResolutionTensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
Stars: β 952 (+842.57%)
Super Resolution VideosApplying SRGAN technique implemented in https://github.com/zsdonghao/SRGAN on videos to super resolve them.
Stars: β 91 (-9.9%)
MaxibonkatajavaMaxibon kata for Java Developers. The main goal is to practice property based testing.
Stars: β 63 (-37.62%)
Docker WorkshopContenido de un workshop para aprender Docker totalmente en espaΓ±ol. Incluye varios ejercicios.
Stars: β 27 (-73.27%)
AshpyTensorFlow 2.0 library for distributed training, evaluation, model selection, and fast prototyping.
Stars: β 82 (-18.81%)
Python Zero To Hero Beginners CourseMaterials for a Python Beginner's Course. First given at the Royal Society of Biology. Designed and delivered by Chas Nelson and Mikolaj Kundegorski.
Stars: β 22 (-78.22%)
Tensorflow EspcnTensorFlow implementation of the Efficient Sub-Pixel Convolutional Neural Network
Stars: β 49 (-51.49%)
SrrescganCode repo for "Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution" (CVPRW NTIRE2020).
Stars: β 44 (-56.44%)
The Complete Guide To Modern JavascriptA comprehensive, easy-to-follow ebook to learn everything from the basics of JavaScript to ES2020. Read more on my blog https://inspiredwebdev.com or buy it here http://a-fwd.to/jHO6m9t. Get the course here https://www.educative.io/courses/complete-guide-to-modern-javascript?aff=BqmB
Stars: β 827 (+718.81%)
FacegrabA tool to collect public images from Facebook and create an image dataset for training computer vision applications like gender recognition, and face detection
Stars: β 76 (-24.75%)
Jsi GanOfficial repository of JSI-GAN (Accepted at AAAI 2020).
Stars: β 42 (-58.42%)
ExcelcyExcel Integration with spaCy. Training NER using Excel/XLSX from PDF, DOCX, PPT, PNG or JPG.
Stars: β 89 (-11.88%)
Advanced ROne day course covering functions, functional programming and tidy evaluation
Stars: β 38 (-62.38%)
Go Collectionπ· awesome awesome go, study golang from basic to proficient
Stars: β 1,193 (+1081.19%)
Latest Development Of Isr VsrLatest development of ISR/VSR. Papers and related resources, mainly state-of-the-art and novel works in ICCV, ECCV and CVPR about image super-resolution and video super-resolution.
Stars: β 93 (-7.92%)
Training JavaA 2-month fulltime java training around an incremental project. Java / JSP / Servlet / Maven / JUnit / Mockito / Selenium / Spring / Hibernate / JPA / Hikari CP / Jackson / Spring MVC / Spring Security / Gatling
Stars: β 36 (-64.36%)
Scn matlabMatlab reimplementation of SCNSR
Stars: β 70 (-30.69%)
Tensorflow SrganTensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)
Stars: β 33 (-67.33%)
PytoflowThe py version of toflow β https://github.com/anchen1011/toflow
Stars: β 83 (-17.82%)
TrainingVarious Plone Trainings
Stars: β 32 (-68.32%)
LearnyougitA self-guided workshop to learn the basics and some of the internals of Git
Stars: β 65 (-35.64%)
WorkshopsTraining Course for Ansible Automation Platform
Stars: β 951 (+841.58%)
DncnnBeyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
Stars: β 912 (+802.97%)
JavaJava Training
Stars: β 15 (-85.15%)
Yolo resnetImplementing YOLO using ResNet as the feature extraction network
Stars: β 82 (-18.81%)
Esrgan Tf2ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks, published in ECCV 2018) implemented in Tensorflow 2.0+. This is an unofficial implementation. With Colab.
Stars: β 61 (-39.6%)
ScnScale-wise Convolution for Image Restoration
Stars: β 26 (-74.26%)
ReactnativekatasThis is a project that lets you participate in a fully-immersive, hands-on, and fun learning experience for React Native.
Stars: β 917 (+807.92%)
NeuralsuperresolutionReal-time video quality improvement for applications such as video-chat using Perceptual Losses
Stars: β 18 (-82.18%)
SeranetSuper Resolution of picture images using deep learning
Stars: β 79 (-21.78%)
Hackerone LessonsTranscribed video lessons of HackerOne to pdf's
Stars: β 101 (+0%)
DiycodeA third-party Android client of DiyCode.
Stars: β 94 (-6.93%)
H4ckerThis repository is primarily maintained by Omar Santos and includes thousands of resources related to ethical hacking / penetration testing, digital forensics and incident response (DFIR), vulnerability research, exploit development, reverse engineering, and more.
Stars: β 10,451 (+10247.52%)
KatasuperheroeskotlinSuper Heroes Kata for Android Developers in Kotlin. The main goal is to practice UI Testing.
Stars: β 77 (-23.76%)