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aac_anomaly

Streamlit dashboard for time series anomaly detection

amazon-bedrock-workshop

This is a workshop designed for Amazon Bedrock a foundational model service.

amazon-sagemaker-immersion-day

amazon-sagemaker-immersion-day-beginners-guide

This is the source code for How to move your on-prem machine learning models into Amazon SageMaker - A Beginners Guide. The guide demonstrates a step by step approach to migrate you machine learning (ML) models from any place into Amazon SageMaker

aws-cdk-project

aws_cdk_workshop

AWS CDK workshop resources

az-900t0x-microsoftazurefundamentals

Microsoft Azure Fundamentals - AZ-900T00 and AZ-900T01

bayes-linear

bayesian-optimization

Python code for bayesian optimization using Gaussian processes

bayesian_changepoint_detection

Methods to get the probability of a changepoint in a time series.

bayesian_unitroots

R code for paper 'Bayesian model selection for unit root testing with multiple structural breaks'

bayessets

Implementation of the Bayesian Sets algorithm and variants

bdabook_py_demos

Bayesian Data Analysis demos for Python

bhad

A Python library for Bayesian Anomaly Detection

bmm_mix

Python implementation for Bernoulli mixture model inference via EM + MCMC

causal_inference

Coursera course : "A Crash Course in Causality: Inferring Causal Effects from Observational Data"

concretedropout

Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832

course_genai

Material from Deeplearning.ai course: Generative AI with Large Language Models

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

coursera_short_courses

dash

deeplearning.ai-natural-language-processing-specialization

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

demand_forecast

dropout_tutorial_in_pytorch

Dropout as Regularization and Bayesian Approximation

edward

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

gans

Deeplearning.ai course on Generative Adversarial Networks

gauss_mix

Python code for Gaussian mixture model

gha-python-packaging-demo

Demo of a simple way to use GitHub Actions to build your Python package, bump the version number, and publish it to GitHub releases and PyPI.org all with a single click of a button in the web interface.

gluon-ts

Probabilistic time series modeling in Python

gpyopt

Gaussian Process Optimization using GPy