Pinned Repositories
a3c_trading
Trading with recurrent actor-critic reinforcement learning
aakinshin.net
My blog
adv-r
Advanced R: a book
Advanced-Machine-Learning-with-Python
Code repository for Advanced Machine Learning with Python, published by Packt
ai-journey-2019
Материалы соревнования AI Journey 2019
Credit-Risk-Modeling
Credit Risk Models for Scorecards, PD, LGD, EAD
hse-shad-ml
Введение в машинное обучение. Курс от ВШЭ и ШАД на coursera.org
Interest_Rate_Modelling
python, computational finance, interest rate modelling, pricing interest rate options
RiskPortfolios
Functions for the construction of risk-based portfolios
StephanKalika's Repositories
StephanKalika/Credit-Risk-Modeling
Credit Risk Models for Scorecards, PD, LGD, EAD
StephanKalika/a3c_trading
Trading with recurrent actor-critic reinforcement learning
StephanKalika/AlgoTradingSimulatedPaths
Mean-Variance Portfolio Optimisation and Algorithmic Trading Strategies in MATLAB
StephanKalika/awesome-dotnet
A collection of awesome .NET libraries, tools, frameworks and software
StephanKalika/awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
StephanKalika/awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
StephanKalika/books-2
useful books
StephanKalika/C-Plus-Plus
All Algorithms implemented in C++
StephanKalika/cracking-the-data-science-interview
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
StephanKalika/Credit-Risk-Analysis-of-Lending-Club-Debtors
Logistic regression and decision tree models to predict the probability of default (PD) and loss given default (LGD) of Lending Club clients.
StephanKalika/Credit-Risk-Models-PD-LGD-EAD-Expected-Loss
We calculate PD,LGD,EAD and Expected loss using logistic and beta regression.
StephanKalika/data-science-interviews
Data science interview questions and answers
StephanKalika/deep-learning-portfolio-optimization
StephanKalika/fastbook
Draft of the fastai book
StephanKalika/finmath-notebooks
StephanKalika/free-programming-books
:books: Freely available programming books
StephanKalika/GradBoost
GradBoost takes in a regression model with methods .fit(X, y) and .predict(X), a set of testing X data to be predicted, training X and y data to fit on, and returns a tuple of the predicted y-values for the training data and testing data. The boosting rounds and learning rate are adjustable. The flexibility of model choice allows custom loss functions for the weak learners.
StephanKalika/grokking_algorithms
Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)
StephanKalika/lessons
Блокноты Jupyter для различных образовательных ресурсов
StephanKalika/Machine-Learning-for-Asset-Managers
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
StephanKalika/nlp-systems-kma
StephanKalika/PD_modelling
StephanKalika/Portfolio-Optimization-using-Machine-Learning
This repository is the result of our work for the course CSCI-SHU 360 Machine Learning
StephanKalika/PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier and advanced methods.
StephanKalika/QLNet
QLNet C# Library
StephanKalika/QuantLibPython
Example Python scripts for interest rate modelling and QuantLib usage
StephanKalika/Self-Learning
Books Papers, Courses & more I have to learn soon
StephanKalika/ta-lib
Python wrapper for TA-Lib (http://ta-lib.org/).
StephanKalika/Test-Automation-Base-ProCamp
StephanKalika/tf-quant-finance
High-performance TensorFlow library for quantitative finance.