Enforcing Distributed Rate Limiting with Hazelcast and Bucket4j
Hands-on guide on enforcing distributed rate limiting for multiple instances with Bucket4J and Hazelcast.
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The Transformer Architecture
Diving deep into the Transformer architecture and its mathematical underpinnings, covering scaled dot-product attention, multi-head attention, and positional encodings, ... .
Exploring how encoder-decoder, encoder-only, and decoder-only models work for NLP, translation and generative AI.
Enhancing HumSet: Improving Humanitarian Crisis Response with AdapterFusion
Exploring ways to leverage NLP and the hierarchical classification framework of HumSet to enhance responses to humanitarian crises beyond baseline results.
Language Models are Few Shot Learners - Meta Learning with GPT-3
Analyzing the paper "Language Models are Few-Shot Learners", exploring GPT-3's meta-learning abilities in Zero, One, and Few-Shot scenarios.
Graph-Based Recommender Systems
Boost recommendations with graph-based recommender systems - from user-item matrices, to social networks and knowledge graphs.
Testcontainers for Spring Boot Integration-Tests with Redis, MariaDB and Gitlab CI/CD
Smooth Spring Boot Integration Tests for MariaDB and Redis Caching, utilizing Testcontainers to bring Integration Tests to a new level of flexibility.
Running PyTorch Models for Inference at Scale using FastAPI, RabbitMQ and Redis
Exploring the architectural setup of how to host GPU intensive PyTorch deep learning models utilizing FastAPI, RabbitMQ and Redis in a scalable way.
Deploying sklearn Models via FastAPI and Docker
Deploying machine learning models to production via FastAPI and containerizing them along the way with docker.
Experimenting with FreeGBDT for NLI Fine-Tuning
Experimenting with "Enhancing Transformers with Gradient Boosted Decision Trees for NLI Fine-Tuning". A deep dive into the FreeGBDT paper.
Disaster Tweet Classification with RoBERTa and PyTorch
Approaching the Disaster Tweet Classification Kaggle challenge with NLP deep learning.