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LLMs & AGENTIC AI
⚡LLMs Core: Backpropagation, RNN, LSTM, BERT, Transformer, Tokenization, MoE, Distillation, RLHF
⚡ LLMs Specialization: RAG, Fine-Tuning, AI Crawling, Vector Databases, Contextual Embeddings, [HuggingFace, Langchain, Crawl4AI]
⚡LLM-powered Application: Prompt Engineering, Autonomous Agent, Workflow, AgenticRAG [PydanticAI, LangGraph, N8N]
DATA SCIENCE
Strong knowledge on Machine Learning techniques and predictive power of classic Machine Learning Model to ground breaking Deep Learning techniques that fuel the AI revolution
⚡ Data Analytics & Machine Learning: Wrangling, EDA, BI Analytics, Feature Engineering, ML/DL Modeling [SQL, Pandas, NumPy, PySpark]
DATA ENGINEER
Stacks:
⚡Data Engineering: ETL, Star Schema, Warehouse & Datalake, SparkSQL, SparkStreaming, RDD [ Foundry, ApacheSpark, Databricks, Azure]
MLOPs, LLMOps
I have fundamental knowledge and some working experiences regarding system design and software production.
⚡ MLOps & LLMOps: FastAPI, Model Packaging, MLFlow, Continuous Monitoring, Orchestration, Post Productionize
⚡ Software Production & Agile Method: Microservices, Docker, Kubernetes, CI/CD
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