LLM Chronicles #1: Introduction

(3:42)

LLM Chronicles #4.3: Language Modelling

(9:44)

LLM Chronicles #6.4: LLM Agents with ReAct (Reason + Act)

(15:46)

LLM Chronicles #5.6: Limitations \u0026 Challenges of LLMs

(15:13)

LLM Chronicles #6.3: Multi-Modal LLMs for Image, Sound and Video

(23:52)

The Limits of LLMs (and where traditional ML / data science comes in)

(1:26)

LLM Chronicles #6.1: RAG (Retrieval Augmented Generation) - Part 1

(24:27)

LangChain vs LangGraph: A Tale of Two Frameworks

(9:55)

Self-Driving Car with JavaScript Course – Neural Networks and Machine Learning

(2:32:40)

LLM Course – Build a Semantic Book Recommender (Python, OpenAI, LangChain, Gradio)

(2:15:4)

I Built an AI Agent That Does EVERYTHING for You! (100% Automated)

(48:35)

Create a Large Language Model from Scratch with Python – Tutorial

(5:43:41)

Large Language Models (LLMs) - Everything You NEED To Know

(25:20)

How to Fine-Tune and Train LLMs With Your Own Data EASILY and FAST- GPT-LLM-Trainer

(10:41)

Hugging Face + Langchain in 5 mins | Access 200k+ FREE AI models for your AI apps

(9:48)

LangSmith Tutorial - LLM Evaluation for Beginners

(36:10)

Unlock AI Agent real power?! Long term memory \u0026 Self improving

(22:10)

LLM Chronicles #4.5: Encoder / Decoder RNN for Language Translation

(9:47)

LLM Chronicles #5.1: The Transformer Architecture

(14:54)

LLM Chronicles #3.3: Training with Gradient Descent, Mini-batch Updates, momentum, SGD, ADAM)

(8:49)

LLM Chronicles #5.4: GPT, Instruction Fine-Tuning, RLHF

(18:28)

LLM Chronicles #3.5: Evaluation, Overfitting and Underfitting + Bonus Lab

(16:29)

LLM Chronicles #2.1: Neural Networks and Multi-Layer Perceptrons

(13:14)

LLM Chronicles #:6.2 RAG (Self-Query/Parent Document/HyDE) - Part 2

(26:12)

LLM Chronicles: #5.2: Making LLMs from Transformers Part 1: BERT, Encoder-based

(19:25)

LLM Chronicles #6.6: Hallucination Detection and Evaluation for RAG systems (RAGAS, Lynx)

(12:43)

llm chronicles 5 1 the transformer architecture

(14:38)