James Briggs Courses

Training and Testing an Italian BERT - Transformers From Scratch

Guida pratica per addestrare e testare un modello BERT italiano, dalla configurazione al training loop, gestendo errori CUDA e valutando i risultati con test reali.

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

Convolutional Neural Nets Explained and Implemented in Python - PyTorch

Comprehensive guide to Convolutional Neural Networks: theory, implementation, and practical applications using Python and PyTorch for computer vision tasks like image classification.

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

Advanced Sentiment Analysis with NLP Transformers and Vector Search

Learn advanced sentiment analysis techniques using NLP transformers and vector search. Apply these methods to large datasets, generate insights, and create queryable databases for understanding customer perceptions in the hotel industry.

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

Vision Transformers Explained + Fine-Tuning in Python

Explore Vision Transformers (ViT) for image classification, from theory to implementation. Learn about attention mechanisms, patch embeddings, and fine-tuning using Hugging Face in Python.

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

Fast Zero Shot Object Detection with OpenAI CLIP

Learn zero-shot object detection and localization using OpenAI CLIP, a multi-modal deep learning model. Implement practical techniques for efficient, domain-flexible computer vision tasks without fine-tuning.

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

How to Use OpenAI Whisper to Fix YouTube Search

Learn to enhance YouTube search using OpenAI Whisper, transformers, and vector search. Build a system for precise content retrieval, transcription, and question-answering from YouTube videos.

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

GUI-Based Few Shot Classification Model Trainer - Demo

Discover how to efficiently train classification models using vector search, enabling rapid fine-tuning with minimal labeled data for improved accuracy and targeted results.

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

AlexNet and ImageNet Explained

Explore the revolutionary AlexNet CNN and ImageNet dataset, their impact on deep learning, and practical implementation using PyTorch for image classification tasks.

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

How to Use Color Histograms for Image Retrieval

Learn to use color histograms for image retrieval, including building histograms, using OpenCV, and implementing retrieval techniques. Explore pros, cons, and practical applications of this content-based approach.

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

Evaluation Measures for Search and Recommender Systems

Learn popular offline metrics for evaluating search and recommender systems, including Recall@K, MRR, MAP@K, and NDCG@K, with Python demonstrations and practical insights for improving information retrieval systems.

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

Long Form Question Answering in Haystack

Explore long-form question answering using Haystack, covering setup, data indexing, and generating responses. Learn to implement QA systems for efficient information retrieval in organizations.

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

Spotify's Podcast Search Explained

Explore Spotify's innovative podcast search system using natural language processing and learn to implement a similar solution with transformer models and vector search techniques.

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

Is GPL the Future of Sentence Transformers - Generative Pseudo-Labeling Deep Dive

Explore Generative Pseudo-Labeling for training high-performance sentence transformers using unlabeled text data. Learn implementation techniques, potential applications, and future implications for NLP and semantic search.

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

Train Sentence Transformers by Generating Queries - GenQ

Learn to train sentence transformers using GenQ, a technique that generates synthetic queries for effective bi-encoder models in semantic search, with practical code walkthroughs and implementation insights.

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

Streamlit for ML - MUI Card Component Build

Learn to create custom Streamlit components using Material UI design elements, focusing on building an interactive card component for machine learning applications.

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