An Introduction to Natural Language Generation
Explore natural language generation through real-world examples, deep learning techniques, and transformer models. Learn about word embeddings, BERT, GPT, and practical applications in various domains.
Extending Spark Machine Learning - Beyond Linear Regression
Explore Spark's ML pipelines, learn to integrate custom tools, and understand how to build and customize advanced machine learning models for big data applications.
The Future of JS and You
Explore the future of JavaScript with insights on Harmony, compilers, and advanced programming patterns from industry experts.
Training With BertForPretraining
Explore BERT training techniques, focusing on NSP and MLM logic, with practical implementation steps and code examples for effective model fine-tuning.
Sentence Similarity With Transformers and PyTorch
Learn to measure semantic similarity between sentences using BERT and PyTorch. Explore tokenization, vector creation, and cosine similarity calculation for powerful NLP applications.
How to Learn NLP for Beginners
Comprehensive guide to self-learning NLP, covering foundational ML concepts, neural networks, modern NLP techniques, and practical projects. Includes curated resources and course recommendations for beginners.
Meet FLAVA: A Unified Vision and Language Foundation Model
Explore FLAVA, a unified vision and language model, its architecture, and performance across 35 tasks. Learn about the journey towards creating this holistic foundation model for multimodal AI applications.
Representation is King: The Journey to Quality Dialog Embeddings
Explore sentence embeddings in dialog systems, focusing on classification. Learn to fine-tune top-performing small-sized sentence transformers using SentenceTransformers framework with practical examples.
Topic Modeling with LeetTopic - Transformer Topic Modeling and Bokeh App Generation
Learn to implement transformer-based topic modeling using LeetTopic and create interactive Bokeh visualizations for text analysis in Python.
Beyond AI Vector Database - Neural Search Implementation with GPT-4 and ChatGPT
Discover how to build a cost-effective neural search system using tokenizers, embedders, and similarity calculations as an alternative to Azure Cognitive Search for domain-specific AI applications.
Desarrollos con Modelos de IA Generativa de Hugging Face
Descubre cómo implementar y utilizar los modelos de IA generativa de Hugging Face para crear aplicaciones innovadoras y soluciones tecnológicas avanzadas.
Moore's Law is Dead - Now What? The Future of AI Processing
Explore the future of AI processing beyond traditional CPUs and GPUs, focusing on innovative architectures designed for demanding ML workloads in retail and beyond.
The Hugging Face Transformers Library - Beginner's Guide and Chatbot UI with Gradio
Explore the Hugging Face Transformers library for easy, cost-free use of open-source language models. Learn sentiment analysis, summarization, and build a chatbot UI with Gradio.
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.
Transformer Models and BERT Model: Overview
Explore Transformer architecture and BERT model, understanding key components and applications in text classification, question answering, and natural language inference.
MLOps in the Era of Generative AI
Explore MLOps in the GenAI era, covering faster experimentation, evolving practices, and optimal LLM usage. Gain insights into data analytics and AI development trends.
Fine-Tuning Flan T5 Base for Document Summarization Using Multi-News Dataset
Fine-tune Flan T5 for document summarization using multi_news dataset. Learn practical implementation with provided notebook and explore variations with other models and datasets.
MLOps: Fine-tuning Mistral 7B with PEFT, QLora, and MLFlow
Fine-tune Mistral 7B using PEFT, QLora, and MLFlow techniques. Master advanced LLM optimization for improved performance and efficiency.
VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores
Explore VENOM, a vectorized N:M format for sparse tensor cores. Learn about high-performance sparse libraries and second-order pruning techniques for efficient deep learning model sparsification.
Deep Ontological Networks: Experimental Evaluation - Part 3
Explore experimental evaluations of Deep Ontological Networks, covering datasets, results, and comparisons with classical approaches. Gain insights into scaling, challenges, and visualizations.
Five Overlooked Neuro-Symbolic AI Papers from 2022
Explore five overlooked neuro-symbolic AI papers from 2022, covering topics like Logic Tensor Networks, knowledge base completion, symbolic regression, and neural ILP architectures.