CodeEmporium Courses

SQL You Need as a Data Scientist

Learn essential SQL skills for data science, including SELECT, JOIN, aggregations, CTEs, and window functions. Apply these techniques to time series forecasting and fraud prediction.

• YouTube
• 22 minutes
• On-Demand
• Free Video

How a Data Scientist Fights Fraud - With Code!

Explore data science techniques for fraud detection, including feature engineering, SQL querying, model creation, evaluation, and interpretation, with hands-on coding examples.

• YouTube
• 27 minutes
• On-Demand
• Free Video

A Guide to A/B Testing as a Data Scientist

Comprehensive guide to A/B testing for data scientists, covering experiment design, dataset creation, hypothesis testing, Bayesian methods, and result interpretation using practical examples and code.

• YouTube
• 29 minutes
• On-Demand
• Free Video

How to Run A-B Tests as a Data Scientist

Explore Bayesian A/B testing for data scientists, comparing it with frequentist methods using real data and code. Learn to define experiments, process data, and interpret results effectively.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Preprocessing Data for Machine Learning - Deep Dive

Comprehensive guide to preprocessing data for logistic regression, covering standardization, encoding, data imbalance, correlation, multicollinearity, and missing data handling techniques.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Let's Build a Music Recommender!

Build a music recommender using AudioSet dataset, embedding generation, and ANNOY for efficient similarity search. Learn to process audio data and create a recommendation engine.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Deep Dive into the Transformer Encoder Architecture

Detailed exploration of transformer encoder architecture, covering embeddings, positional encodings, self-attention mechanisms, and key components for effective natural language processing.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Decoder Flow in Transformer Model

Learn to code a Transformer Decoder from scratch, covering key concepts like masking, multi-head attention, and feed-forward networks in this comprehensive tutorial.

• YouTube
• 40 minutes
• On-Demand
• Free Video

The Complete Guide to Transformer Neural Networks

Comprehensive exploration of Transformer neural networks for language translation, covering architecture, key components, and practical implementation insights.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Transformer Encoder in 100 Lines of Code

Learn to implement a Transformer Encoder from scratch in Python. Explore key concepts like attention mechanisms, layer normalization, and feed-forward networks through hands-on coding.

• YouTube
• 50 minutes
• On-Demand
• Free Video

Blowing Up Transformer Decoder Architecture

Detailed exploration of Transformer Decoder architecture, covering key components like masked self-attention, cross-attention, and position encoding. Includes implementation insights and training considerations.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Transformers - From Zero to Hero

Comprehensive deep dive into transformer architecture, covering key concepts from self-attention to tokenization. Includes hands-on coding for both encoder and decoder implementations.

• YouTube
• 3 hours 35 minutes
• On-Demand
• Free Video

ChatGPT: From Zero to Hero - Understanding the Technology and Training Process

Comprehensive exploration of ChatGPT's architecture, from fundamental concepts to advanced fine-tuning techniques, covering GPT models, reward systems, and reinforcement learning applications.

• YouTube
• 49 minutes
• On-Demand
• Free Video

Self-Taught Reasoning: How Large Language Models Learn Arithmetic

Explore how Self-Taught Reasoning (STaR) enhances Large Language Models' arithmetic capabilities through step-by-step explanations and practical demonstrations of this innovative approach.

• YouTube
• 18 minutes
• On-Demand
• Free Video

LoRA - Low Rank Adaptation for Parameter Efficient Fine-Tuning

Dive into parameter-efficient fine-tuning with LoRA, exploring low-rank matrices, adapters, and techniques to optimize neural network storage and performance while maintaining accuracy.

• YouTube
• 29 minutes
• On-Demand
• Free Video