Yulian Manchev's repositories
alpaca-py
The Official Python SDK for Alpaca API
AnimationsWithManim
Animation course with Manim
awesome-public-datasets
A topic-centric list of HQ open datasets.
bayesian-machine-learning
Notebooks about Bayesian methods for machine learning
bayesian-optimization-in-action
Source code for Bayesian Optimization in Action, published by Manning
cclib
Parsers and algorithms for computational chemistry logfiles
console-menu
A simple Python menu system for building terminal user interfaces.
cs50_final
cs50x final project
emoncms
Web-app for processing, logging and visualising energy, temperature and other environmental data
FinanceToolkit
Transparent and Efficient Financial Analysis
gpytorch
A highly efficient implementation of Gaussian Processes in PyTorch
ichor
Package for computational chemistry
IoTaWatt
IoTaWatt Open WiFi Electric Energy Monitor
ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
jekyll-now
Build a Jekyll blog in minutes, without touching the command line.
lanyon
A content-first, sliding sidebar theme for Jekyll.
linear_operator
A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
m-julian.github.io
Github Pages of m-julian
machine-learning-interview
Minimum Viable Study Plan for Machine Learning Interviews from FAAG, Snapchat, LinkedIn.
minima
Minima is a one-size-fits-all Jekyll theme for writers.
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
peterroelants
Blog
PLAMS
Python Library for Automating Molecular Simulations
pmtk3
Probabilistic Modeling Toolkit for Matlab/Octave.
ProgrammingProjects
C++ Programming Tutorial in Chemistry
Pygame_Functions
A set of functions that make working with Pygame and Python much easier.
pygame_tutorials
Code to go along with lessons at http://kidscancode.org/lessons
RPi-Photometer-Experiment
DIY photometer experiment using a Raspberry Pi.
rpi-power-monitor
Power Monitor (for Raspberry Pi)
sGDML
sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model