Al Vinjamur's Projects
A beginner's guide to carry out extreme value analysis, which consists of basic steps, multiple distribution fitting, confidential intervals, IDF/DDF, and a simple application of IDF information for roof drainage design. The guide mainly focuses on extreme rainfall analysis. However, the basic steps are also suitable for other climatic or hydrologic variables such as temperature, wind speed or runoff.
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
Declarative statistical visualization library for Python
Web interface for browsing, search and filtering recent arxiv submissions
A curated list of deep learning resources for computer vision
A curated list of awesome Machine Learning frameworks, libraries and software.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
A curated list of awesome R packages, frameworks and software.
Random Forest - a curated list of resources regarding random forest
Reinforcement learning resources curated
Recurrent Neural Network - A curated list of resources dedicated to RNN
TensorFlow - A curated list of dedicated resources http://tensorflow.org
This curated list contains python packages for time series analysis
In which I try to demystify the fundamental concepts behind Bayesian deep learning.
A Python implementation of global optimization with gaussian processes.
A collection of questions and solutions to problems presented at Rasmus Bååth's Bayesian probabilities workshop.
A profitable cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym
for code created as part of http://studywolf.wordpress.com
catch-22: CAnonical Time-series CHaracteristics
An R package for causal inference in time series
Code for a workshop on statistical interference using computational methods in Python.
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
fast.ai Courses
a template....
Render some probabilistic graphical models using matplotlib
Materials for "Parallelizing Scientific Python with Dask"
Open Source Data Science Resources.
The Leek group guide to data sharing
Deep learning base image for Docker (Tensorflow, Caffe, MXNet, Torch, Openface, etc.)
Hands-on, practical knowledge of how to use neural networks and deep learning with Keras 2.0