sharath k's repositories
awesome-java-books
Java开发者技术书籍大全 - Java入门书籍,Java基础及进阶书籍,框架与中间件,架构设计,设计模式,数学与算法,JVM周边语言,项目管理&领导力&流程,职业素养与个人成长,格局与视野,面试参考书等。
awesome-jmeter
A collection of resources covering different aspects of JMeter usage.
awesome-mlops
A curated list of references for MLOps
awesome-mlops-1
:sunglasses: A curated list of awesome MLOps tools
awesome-of-awesomes
Collection of best of everything and Best Practices in the tech world - aws, azure, googlecloud, machinelearning, web, mobile, backend, books/blogs/reusablerepos, recruitment/books, engineering/devops/ops ,architecture ,bestpractices ,personalbranding ,leadership ,techvision ,codingpractices
awesome-software-architecture
A curated list of resources on software architecture
AWS-SAA-C02-Course
Personal notes for SAA-C02 test from: https://learn.cantrill.io
Best-README-Template
An awesome README template to jumpstart your projects!
cheatsheets
Quick reference for developer tool commands
CKAD-exercises
A set of exercises to prepare for Certified Kubernetes Application Developer exam by Cloud Native Computing Foundation
design-resources-for-developers
Curated list of design and UI resources from stock photos, web templates, CSS frameworks, UI libraries, tools and much more
devops-basic
Practical place for basic DevOps toolchain
howtheytest
A collection of public resources about how software companies test their software
Leetcode-Solutions
A repository with over 7000 solutions to more than 1800 Leetcode problems written in C++, Python, Java, and Javascript.
MadeWithML
Learn how to responsibly deliver value with ML.
polyaxon-mlops
Machine Learning Platform for Kubernetes (MLOps tools for experimentation and automation)
proposals
Tracking ECMAScript Proposals
pyspark-cheatsheet
PySpark Cheat Sheet - example code to help you learn PySpark and develop apps faster
PythonCheatSheet
A Cheat Sheet 📜 to revise Python syntax. Particularly useful for solving Data Structure and Algorithmic problems with Python.
reading_notes
读书笔记
seldon-core-mlops
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
start-machine-learning
A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!