Triple H's repositories
cord19recommender
KDD 2020 hands-on tutorial of knowledge graph-based recommender for COVID-19 related research
CTGAN
Conditional GAN for generating synthetic tabular data.
gnn
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
KDD-2019-Hands-on
DGL tutorial in KDD 2019
KDD20-Hands-on-Tutorial
Scalable Graph Neural Networks with Deep Graph Library
kdd2020-calibration
How to calibrate your neural network classifier: Getting accurate probabilities from a classification model
Large-Language-Models-with-Semantic-Search
Explore from keyword search to dense retrieval and reranking, which injects the intelligence of LLMs into your search system, making it faster and more effective.
llms-in-prod-workshop-2023
Deploy and Scale LLM-based applications
ML-Papers-Explained
Explanation to key concepts in ML
probability
Probabilistic reasoning and statistical analysis in TensorFlow
recommenders
Best Practices on Recommendation Systems
synthetic_time_series_forecasting
Generating synthetic time-series from DoppelGANger model and testing forecasting performance
system-design
Preparing for system design interview questions
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
TimeGAN
Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019
timeVAE
TimeVAE implementation in keras/tensorflow
tsa-notebooks
Jupyter notebooks on time series econometrics topics.
TSAGen
A time series generation tool for KPI anomaly detection
tsBNgen
tsBNgen is a python package to generate time series data from an arbitrary Bayesian network structure
wikipedia-data-science
Working with and analyzing Wikipedia Data
ydata-synthetic
Synthetic data generators for tabular and time-series data