Reza Rahim's repositories
airflow-scheduler-failover-controller
A process that runs in unison with Apache Airflow to control the Scheduler process to ensure High Availability
bayes_course_2022
Probabilistic Programming and Bayesian Computing with PyMC
bayesian-machine-learning
Notebooks about Bayesian methods for machine learning
bayesian-stats-modelling-tutorial
How to do Bayesian statistical modelling using numpy and PyMC3
College_Statistics_with_Python
We use Python to get intuition on complex concepts, empirically test theoretical proofs, or build algorithms from scratch
educational-resources
Educational resources
Hands-On-Ensemble-Learning-with-Python
Hands-On Ensemble Learning with Python, published by packt publishing
Hands-On-Machine-Learning-with-scikit-learn-and-Scientific-Python-Toolkits
The accompanying code for the book "Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits". A practical guide to implementing supervised and unsupervised machine learning algorithms in Python by Tarek Amr
Hands-On-Reinforcement-Learning-with-Python
Hands-On Reinforcement Learning with Python, published by Packt
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.
Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
machine_learning_course_UofA_MECE610
This course was developed to teach ML from scratch up to TensorFlow and PyTorch implementation.
Probabilistic-Deep-Learning-with-TensorFlow
Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
pymc-resources
PyMC educational resources
python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Reinforcement-Learning-for-Market-Making
Using tabular and deep reinforcement learning methods to infer optimal market making strategies
tensor-house
A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain
tensorflow-deep-learning
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
terraform-google-gke
Terraform code and scripts for deploying a Google Kubernetes Engine (GKE) cluster.
xarray-tutorial
Xarray Tutorials