Pinned Repositories
affine
Affine term structure modeling Python package. See LICENSE for terms of use.
agents-aea
A framework for autonomous economic agent (AEA) development
AIND-NLP
Coding exercises for the Natural Language Processing concentration, part of Udacity's AIND program.
arch
ARCH models in Python
berkeley-stat-157
Homepage for STAT 157 at UC Berkeley
cloudml-samples
Cloud ML Engine is now a part of AI Platform
CythonGSL
Cython interface for the GNU Scientific Library (GSL).
deep-reinforcement-learning
Repo for the Deep Reinforcement Learning Nanodegree program
deep-rl-tensorflow
TensorFlow implementation of Deep Reinforcement Learning papers
DSGE_mod
A collection of Dynare models
yangjue-han's Repositories
yangjue-han/agents-aea
A framework for autonomous economic agent (AEA) development
yangjue-han/AIND-NLP
Coding exercises for the Natural Language Processing concentration, part of Udacity's AIND program.
yangjue-han/arch
ARCH models in Python
yangjue-han/berkeley-stat-157
Homepage for STAT 157 at UC Berkeley
yangjue-han/cloudml-samples
Cloud ML Engine is now a part of AI Platform
yangjue-han/CythonGSL
Cython interface for the GNU Scientific Library (GSL).
yangjue-han/deep-reinforcement-learning
Repo for the Deep Reinforcement Learning Nanodegree program
yangjue-han/deep-rl-tensorflow
TensorFlow implementation of Deep Reinforcement Learning papers
yangjue-han/DSGE_mod
A collection of Dynare models
yangjue-han/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
yangjue-han/Finance_Graph_Theory
Modelling Connectedness of Firms in Financial Markets with Heterogeneous Agents
yangjue-han/frbus
FRB/US Model packages and documents.
yangjue-han/gs-quant
Python toolkit for quantitative finance
yangjue-han/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
yangjue-han/HANK
Replication of Heterogeneous Agent New Keynesian (HANK) model in MATLAB
yangjue-han/hmmlearn
Hidden Markov Models in Python, with scikit-learn like API
yangjue-han/Nowcasting
Nowcasting
yangjue-han/Parallel_Computing
yangjue-han/phact
yangjue-han/probability
Probabilistic reasoning and statistical analysis in TensorFlow
yangjue-han/PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
yangjue-han/pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
yangjue-han/quantecon-notebooks-python
A Repository of Notebooks for the Python Lecture Site
yangjue-han/reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
yangjue-han/reinforcement-learning-examples
Minimal and Clean Reinforcement Learning Examples
yangjue-han/samplemod
yangjue-han/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
yangjue-han/TERS
A small project on a tax-efficient rebalancing strategy.
yangjue-han/tpu
Reference models and tools for Cloud TPUs.
yangjue-han/tutmom
Tutorial on "Modern Optimization Methods in Python"