DevOops's repositories
pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
a-crash-course-on-serverless-auth
A short and easy boilerplate showcasing JWT auth with Nodejs, the Serverless framework, MongoDB and AWS Lambda.
amazon-ecs-mythicalmysfits-workshop
A tutorial for developers who want to learn about how to containerized applications on top of AWS using AWS Fargate. You will build a sample website that leverages infrastructure as code, containers, CI/CD, and more! If you're planning on running this, let us know @ aws-mythical-mysfits@amazon.com. At re:Invent 2018, these sessions were run as CON214/CON321/CON322.
Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
cardiel
A tool for portfolio managers: use the Black-Litterman model to view optimal portfolio allocations using several of the most popular optimization methods.
catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Cloud-DevOps-Learning-Resources
This repo includes Books and imp notes related to GCP, Azure, AWS, Docker, K8s, and DevOps. More, exam and interview prep notes.
devops-exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
eventsourcing
A library for event sourcing in Python.
Evolutionary-Algorithm
Evolutionary Algorithm using Python, 莫烦Python 中文AI教学
financial-machine-learning
A curated list of practical financial machine learning (FinML) tools and applications in Python (by @firmai)
Full-Stack-React-Projects
Full-Stack React Projects, published by Packt
fuzzywuzzy
Fuzzy String Matching in Python
gym
A toolkit for developing and comparing reinforcement learning algorithms.
gym-anytrading
The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
MicroservicesBooks
Microservices books
mlfinlab
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
neat-gym
Neuro-evolution for OpenAI Gym environments
neat-python
Python implementation of the NEAT neuroevolution algorithm
Neuroevolution_of_Augmenting_Topologies_Paper
Overview of the current state of 'Neuroevolution of Augmenting Topologies' as a seminar paper
ngboost
Natural Gradient Boosting for Probabilistic Prediction
odoo
Odoo. Open Source Apps To Grow Your Business.
PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
research_public
Quantitative research and educational materials
scikit-learn
scikit-learn: machine learning in Python
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow