CodeEmporium Courses

Transformer Encoder in 100 Lines of Code

Implementa un encoder Transformer desde cero en aproximadamente 100 líneas de código, explicando la atención multi-cabeza y el flujo de tensores.

• YouTube
• 50 minutes
• Self-Paced
• Free Video

Deep Dive into the Transformer Encoder Architecture

A deep dive into the Transformer encoder, from embeddings and positional encodings through self-attention, normalization, and feed-forward layers.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

SQL You Need as a Data Scientist

Practical SQL for data scientists, from SELECT queries and joins to CTEs, window functions, and machine-learning datasets.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

How a Data Scientist Fights Fraud - With Code!

Use supervised machine learning, feature engineering, SQL, and model interpretation to predict transaction fraud from historical purchase data.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

A Guide to A/B Testing as a Data Scientist

Learn Bayesian A/B testing for binary conversions and continuous price metrics, including priors, posteriors, probability distributions, and interpreting lift.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

How to Run A-B Tests as a Data Scientist

Learn to design an e-commerce A/B test and compare frequentist and Bayesian analyses using real data, priors, posteriors, and interpretable conversion probabilities.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Preprocessing Data for Machine Learning - Deep Dive

Learn how preprocessing choices affect logistic regression, including scaling, encoding, imbalance, multicollinearity, and missing values.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

Let's Build a Music Recommender!

Build a music recommender that converts WAV audio into embeddings and retrieves similar tracks with approximate nearest-neighbor search.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

Decoder Flow in Transformer Model

Code a Transformer decoder from scratch, covering masking, self-attention, cross-attention, normalization, dropout, and feed-forward layers.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

The Complete Guide to Transformer Neural Networks

A concise deep dive into Transformer architecture for language translation, covering attention, positional encodings, encoder-decoder layers, tokenization, and inference.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Retrieval-Augmented Generation (RAG) - Explained

Explore RAG (Retrieval-Augmented Generation) to mitigate AI hallucinations. Learn key concepts, implementation details, and advanced techniques through multiple passes and quizzes.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

LLM Fine-Tuning - Explained

Explore parameter efficient fine-tuning techniques for large language models, including adapters, prefix-tuning, and LoRA. Learn their importance, implementation details, and performance evaluation.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

Informer: Training and Inference

Explore time series prediction using Informer, a transformer-based model. Learn to train and make predictions through hands-on coding, enhancing your skills in advanced forecasting techniques.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Informer: Complete Code from Scratch - Time Series Transformer Analysis

Line-by-line exploration of the time series transformer, focusing on implementation details and code structure for deep learning enthusiasts and practitioners.

• YouTube
• 1 hour 27 minutes
• Self-Paced
• Free Video

Informer Architecture Explained - Complete Guide

Comprehensive exploration of Informer encoder architecture, detailing its components and implementation for advanced time series forecasting and sequence modeling tasks.

• YouTube
• 38 minutes
• Self-Paced
• Free Video