Pytorch Neural Network Example
Step-by-step guide to building a simple neural network using PyTorch, covering network creation, data handling, loss calculation, and accuracy evaluation.
Hugging Face Datasets - Dataset Builder Scripts for Beginners
Learn to create and manage dataset builder scripts for Hugging Face, including download management, Apache Arrow datatypes, and integration with popular machine learning frameworks for efficient model training and fine-tuning.
Log Softmax Explained with Python
Explore log softmax implementation in Python, enhancing numerical stability for machine learning. Gain insights into softmax limitations and practical coding solutions.
MLOps: Using GPUs in Local, Docker, and Docker Compose Environments
Aprende a instalar PyTorch con soporte GPU y configura Docker y Docker Compose para aprovechar el poder de procesamiento gráfico en tus proyectos de aprendizaje automático.
Get to Know PyTorch - A Cutting Edge Open Source AI Framework for Machine Learning
Explore PyTorch's fundamentals, latest developments, and community contributions. Learn to leverage this open-source AI framework for creating neural network models and advancing machine learning research.
Efficient Serving of LLMs for Experimentation and Production with Fireworks.ai
Explore efficient LLM deployment strategies for experimentation and production using Fireworks.ai GenAI Platform. Learn to optimize cost, latency, and scalability for various model variants.
Functional Transforms in PyTorch Using Torch.func
Master functional transforms in PyTorch with torch.func module, covering per-sample-gradients, function vectorization, and model ensembles. Learn practical applications and avoid common pitfalls.
Machine Learning Software Ecosystems: Frameworks, Compilers, and Models - Part 1
Explore the landscape of ML frameworks, compilers, and models while understanding performance considerations for various hardware platforms and edge computing requirements.
Image Recognition Using OpenAI, Streamlit and Snowflake
Discover how to build image recognition applications by combining PyTorch, OpenAI, Streamlit, and Snowflake in this practical demonstration of modern AI integration.
Node Classification with Graph Convolutional Networks for Graph Machine Learning
Master Graph Convolutional Networks (GCN) implementation in PyG for node classification, featuring practical coding examples and theoretical foundations of spectral graph convolutions.
JAX vs PyTorch 2 - Converting Stateful to Stateless Operations in Neural Networks
Explore functional programming in JAX through hands-on comparison with PyTorch 2, focusing on neural network implementation and stateless operations for gradient descent.
Future of LLMs and Machine Learning Productionization - Conf42 LLMs 2024
Explore the future of LLM deployment, traditional AI models in production, and generative AI application development using Langchain frameworks. Gain insights into MLOps and ChatGPT's impact.
The Fragmented ML Stack and How to Fix It
Explore the fragmented ML stack, understand Ivy's role in unification, and see demonstrations of function, library, and model transpilation.
Integrating Julia for Perception Tasks in Autonomous Driving
Explore Julia's potential in autonomous driving perception tasks, from LIDAR processing to ML algorithm development and integration in real vehicles.
Installing WSL with CUDA Support and PyTorch for Data Science and Machine Learning
Aprenda a instalar WSL con soporte CUDA y PyTorch para potenciar sus proyectos de aprendizaje automático y ciencia de datos en Windows.
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.
Llama - Scaling Up LLMs in an Open Ecosystem
Explore Llama's evolution, its impact on Generative AI, and learn how to leverage state-of-the-art performance using Ray-based platforms for building with open-source large language models.
VeScale - A PyTorch Native LLM Training Framework
Explore a novel PyTorch-native framework for LLM training, combining automatic parallelism and ease of use. Scale your models efficiently with single-device code and transparent nD parallelization.
Intersection over Union (IoU) Explained with PyTorch
Learn to implement Intersection over Union (IoU) for object recognition using PyTorch. Covers theory, formulas, and practical code for bounding boxes and segmentation masks.
LivePortrait - Efficient Portrait Animation with Stitching and Retargeting Control
Innovative framework for video-driven portrait animation, balancing efficiency and control. Utilizes implicit keypoints, large-scale training, and advanced modules for superior performance and speed.
Prompting for Code Generation - Leveraging LLMs for Efficient Programming
Learn to leverage AI for efficient code generation using OpenAI's LLMs. Explore practical examples, from simple Fibonacci sequences to complex neural networks, and discover how to integrate AI tools into your programming workflow.