Udacity Suse Cloud Native Foundations Scholarship Course Walkthrough

Overview

SUSE Cloud Native Foundations Scholarship

Udacity is collaborating with SUSE, a global leader in true open source solutions, to empower developers and operations specialists to meet today's high growth career challenges. We invite students 18 years of age or older who want to build new cloud native application development, deployment, and management skills to apply to the SUSE Cloud Native Foundations Scholarship Program.

Suse-Banner

Feeling stuck amidst the course? Feel free to refer this repository or reach out to me on Slack!

Udacity SUSE Cloud Native Fundamentals Scholarship Program Nanodegree Program Status
1 Introduction to Cloud Native Fundamentals
2 Architecture Consideration for Cloud Native Applications
3 Container Orchestration with Kubernetes
4 Open Source PaaS
5 CI/CD with Cloud Native Tooling

Status Definitions

☐ Means that the particular Chapter is not started yet 👍
☒ Means that the particular Chapter is under progress 👨‍💻
Means that the particular Chapter is completed 🎉

Tools Checklist

Make sure you have setup all the required tools to get started with this course as listed here.

Want to Contribute?

Fork the repo and send PRs.

Do this repository to keep a track of the course.

Made with ❤️ by Shivansh

Owner
Shivansh Srivastava
SDE Intern @paytm money | GSoC'21, GSoD'20 Mentor @CircuitVerse | OSH Mentor @anitab-org | Full Stack Web Developer | Django | Flask | GCP
Shivansh Srivastava
Hummingbird compiles trained ML models into tensor computation for faster inference.

Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se

Microsoft 3.1k Dec 30, 2022
Clustering with variational Bayes and population Monte Carlo

pypmc pypmc is a python package focusing on adaptive importance sampling. It can be used for integration and sampling from a user-defined target densi

45 Feb 06, 2022
BMVC 2021 Oral: code for BI-GCN: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation

BMVC 2021 BI-GConv: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation Necassary Dependencies: PyTorch 1.2.0 Python 3.

Yanda Meng 15 Nov 08, 2022
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur

Benedek Rozemberczki 1.2k Jan 02, 2023
NeuralDiff: Segmenting 3D objects that move in egocentric videos

NeuralDiff: Segmenting 3D objects that move in egocentric videos Project Page | Paper + Supplementary | Video About This repository contains the offic

Vadim Tschernezki 14 Dec 05, 2022
This repo contains the source code and a benchmark for predicting user's utilities with Machine Learning techniques for Computational Persuasion

Machine Learning for Argument-Based Computational Persuasion This repo contains the source code and a benchmark for predicting user's utilities with M

Ivan Donadello 4 Nov 07, 2022
An efficient and easy-to-use deep learning model compression framework

TinyNeuralNetwork 简体中文 TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neura

Alibaba 441 Dec 25, 2022
以孤立语假设和宽度优先搜索为基础,构建了一种多通道堆叠注意力Transformer结构的斗地主ai

ddz-ai 介绍 斗地主是一种扑克游戏。游戏最少由3个玩家进行,用一副54张牌(连鬼牌),其中一方为地主,其余两家为另一方,双方对战,先出完牌的一方获胜。 ddz-ai以孤立语假设和宽度优先搜索为基础,构建了一种多通道堆叠注意力Transformer结构的系统,使其经过大量训练后,能在实际游戏中获

freefuiiismyname 88 May 15, 2022
Implementation of ICCV2021(Oral) paper - VMNet: Voxel-Mesh Network for Geodesic-aware 3D Semantic Segmentation

VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation Created by Zeyu HU Introduction This work is based on our paper VMNet: Voxel-Mes

HU Zeyu 82 Dec 27, 2022
Running Google MoveNet Multipose Tracking models on OpenVINO.

MoveNet MultiPose Tracking on OpenVINO

60 Nov 17, 2022
3DIAS: 3D Shape Reconstruction with Implicit Algebraic Surfaces (ICCV 2021)

3DIAS_Pytorch This repository contains the official code to reproduce the results from the paper: 3DIAS: 3D Shape Reconstruction with Implicit Algebra

Mohsen Yavartanoo 21 Dec 12, 2022
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

Microsoft 12.4k Dec 31, 2022
Tweesent-back - Tweesent backend uses fastAPI as the web framework

TweeSent Backend Tweesent backend. This repo uses fastAPI as the web framework.

0 Mar 26, 2022
Python framework for Stochastic Differential Equations modeling

SDElearn: a Python package for SDE modeling This package implements functionalities for working with Stochastic Differential Equations models (SDEs fo

4 May 10, 2022
Unified learning approach for egocentric hand gesture recognition and fingertip detection

Unified Gesture Recognition and Fingertip Detection A unified convolutional neural network (CNN) algorithm for both hand gesture recognition and finge

Mohammad 227 Dec 25, 2022
Repository for open research on optimizers.

Open Optimizers Repository for open research on optimizers. This is a test in sharing research/exploration as it happens. If you use anything from thi

Ariel Ekgren 6 Jun 24, 2022
7th place solution of Human Protein Atlas - Single Cell Classification on Kaggle

kaggle-hpa-2021-7th-place-solution Code for 7th place solution of Human Protein Atlas - Single Cell Classification on Kaggle. A description of the met

8 Jul 09, 2021
A PyTorch Implementation of PGL-SUM from "Combining Global and Local Attention with Positional Encoding for Video Summarization", Proc. IEEE ISM 2021

PGL-SUM: Combining Global and Local Attention with Positional Encoding for Video Summarization PyTorch Implementation of PGL-SUM From "PGL-SUM: Combin

Evlampios Apostolidis 35 Dec 22, 2022
Back to Basics: Efficient Network Compression via IMP

Back to Basics: Efficient Network Compression via IMP Authors: Max Zimmer, Christoph Spiegel, Sebastian Pokutta This repository contains the code to r

IOL Lab @ ZIB 1 Nov 19, 2021
My implementation of Fully Convolutional Neural Networks in Keras

Keras-FCN This repository contains my implementation of Fully Convolutional Networks in Keras (Tensorflow backend). Currently, semantic segmentation c

The Duy Nguyen 15 Jan 13, 2020