andromeda0505
Statistics, Causal Machine Learning, Reinforcement Learning, Structural Estimation, Causal Inference & Optimization
University of CalgaryHomosapien, Earth, Milky Way Galaxy
Pinned Repositories
alphazero
A reimplementation of the Google AlphaZero algorithm.
Deep-Learning
A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature.
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.
Econometrics-methods
Econometrics and causal inference plays an important role in technology, particularly in areas such as machine learning and artificial intelligence. In these fields, the goal is often to understand the causal relationships between variables in order to make predictions or decisions.
interpretable-ml-book
Book about interpretable machine learning
Machine-Learning-Projects-
Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.
Meta-heuristic-Optimization
Metaheuristic optimization deals with optimization problems using metaheuristic algorithms. Optimization is essentially everywhere, from engineering design to economics and from holiday planning to Internet routing. As money, resources and time are always limited, the optimal utility of these available resources is crucially important.
Modeling-an-inventory-routing-problem-for-perishable-products
A Python replication of an inventory routing problem article
nber_methods_lecture_slides
Slides from NBER Methods Lecture (extracted from the Wayback Machine)
Time-Series-Modeling-Techniques
Time series analysis is a statistical technique that is used to analyze and model time-based data. It involves identifying patterns, trends, and relationships in data that change over time, and using those patterns to make predictions about future observations.
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