Posts

<Deep Learning Basics> Model Compression/GPU Techniques
<RAG> 3. Setting Up Baseline LLM Prompt For Service
<RAG> 2. Collecting RAG Data Using LLM
<Deep Learning Intermediate> Optuna for Effective Hyperparameter Tuning
<RAG> 1. Tuning LLM Using Langchain + LM Studio
<LLM Fine Tuning> 1. Supervised Fine-Tuning Using QLoRA
<GPU Training> 1. Pytorch Distributed Training
<Deep Learning Basics> ML Basics - GPU Types and Performance
<C++ Server Programming> Troubleshooting - C++ Server and Unreal Engine
<Server> Understanding Game Servers(C++)
<LLM> Creating LLM Agents Using LangGraph 1. Basic Structure and State Transition
<C++> Implementing Unreal Plugin for whisper Model.
<C++> Implementing RAG Controlled Game NPC in Unreal
Python OOP Features
<Computer Vision> Implementing RTMDet-Ins 5. Pretraining Backbone on ImageNet
<Computer Vision> Implementing RTMDet-Ins 2. Making COCO Dataset Reader
<Computer Vision> Implementing RTMDet-Ins 1. Backbone/Neck/Head Implementation
<Analytics> Starting Spark Session in Azure Synapse Analytics