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.

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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
Complete the code of prefix-tuning in low data setting

Prefix Tuning Note: 作者在论文中提到使用真实的word去初始化prefix的操作(Initializing the prefix with activations of real words,significantly improves generation)。我在使用作者提供的

Andrew Zeng 4 Jul 11, 2022
Immortal tracker

Immortal_tracker Prerequisite Our code is tested for Python 3.6. To install required liabraries: pip install -r requirements.txt Waymo Open Dataset P

74 Dec 03, 2022
Official implementation of "Accelerating Reinforcement Learning with Learned Skill Priors", Pertsch et al., CoRL 2020

Accelerating Reinforcement Learning with Learned Skill Priors [Project Website] [Paper] Karl Pertsch1, Youngwoon Lee1, Joseph Lim1 1CLVR Lab, Universi

Cognitive Learning for Vision and Robotics (CLVR) lab @ USC 134 Dec 06, 2022
Fuzzy Overclustering (FOC)

Fuzzy Overclustering (FOC) In real-world datasets, we need consistent annotations between annotators to give a certain ground-truth label. However, in

2 Nov 08, 2022
Official code for: A Probabilistic Hard Attention Model For Sequentially Observed Scenes

"A Probabilistic Hard Attention Model For Sequentially Observed Scenes" Authors: Samrudhdhi Rangrej, James Clark Accepted to: BMVC'21 A recurrent atte

5 Nov 19, 2022
Example of semantic segmentation in Keras

keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o

53 Mar 23, 2022
Using VideoBERT to tackle video prediction

VideoBERT This repo reproduces the results of VideoBERT (https://arxiv.org/pdf/1904.01766.pdf). Inspiration was taken from https://github.com/MDSKUL/M

75 Dec 14, 2022
Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021).

AA-RMVSNet Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021) in PyTorch. paper link: arXiv | CVF Change Log Ju

Qingtian Zhu 97 Dec 30, 2022
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders

PreSumm This code is for EMNLP 2019 paper Text Summarization with Pretrained Encoders Updates Jan 22 2020: Now you can Summarize Raw Text Input!. Swit

Yang Liu 1.2k Dec 28, 2022
Adversarial Autoencoders

Adversarial Autoencoders (with Pytorch) Dependencies argparse time torch torchvision numpy itertools matplotlib Create Datasets python create_datasets

Felipe Ducau 188 Jan 01, 2023
Fine-grained Post-training for Improving Retrieval-based Dialogue Systems - NAACL 2021

Fine-grained Post-training for Multi-turn Response Selection Implements the model described in the following paper Fine-grained Post-training for Impr

Janghoon Han 83 Dec 20, 2022
potpourri3d - An invigorating blend of 3D geometry tools in Python.

A Python library of various algorithms and utilities for 3D triangle meshes and point clouds. Managed by Nicholas Sharp, with new tools added lazily as needed. Currently, mainly bindings to C++ tools

Nicholas Sharp 295 Jan 05, 2023
Build a medical knowledge graph based on Unified Language Medical System (UMLS)

UMLS-Graph Build a medical knowledge graph based on Unified Language Medical System (UMLS) Requisite Install MySQL Server 5.6 and import UMLS data int

Donghua Chen 6 Dec 25, 2022
Smart edu-autobooking - Johnson @ DMI-UNICT study room self-booking system

smart_edu-autobooking Sistema di autoprenotazione per l'aula studio [email protected]

Davide Carnemolla 17 Jun 20, 2022
DanceTrack: Multiple Object Tracking in Uniform Appearance and Diverse Motion

DanceTrack DanceTrack is a benchmark for tracking multiple objects in uniform appearance and diverse motion. DanceTrack provides box and identity anno

260 Dec 28, 2022
Dynamic Bottleneck for Robust Self-Supervised Exploration

Dynamic Bottleneck Introduction This is a TensorFlow based implementation for our paper on "Dynamic Bottleneck for Robust Self-Supervised Exploration"

Bai Chenjia 4 Nov 14, 2022
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation

EFENet EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation Code is a bit messy now. I woud clean up soon. For training the EF

Yaping Zhao 19 Nov 05, 2022
An extremely simple, intuitive, hardware-friendly, and well-performing network structure for LiDAR semantic segmentation on 2D range image. IROS21

FIDNet_SemanticKITTI Motivation Implementing complicated network modules with only one or two points improvement on hardware is tedious. So here we pr

YimingZhao 54 Dec 12, 2022
UMT is a unified and flexible framework which can handle different input modality combinations, and output video moment retrieval and/or highlight detection results.

Unified Multi-modal Transformers This repository maintains the official implementation of the paper UMT: Unified Multi-modal Transformers for Joint Vi

Applied Research Center (ARC), Tencent PCG 84 Jan 04, 2023
Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweeper.

Minesweeper-AI Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweep

Beckham 0 Jul 20, 2022