Transformers that Transform Well Enough to Support Near-Shallow Architectures - Stanford CS25 Lecture
Explore precision language models for efficient training and hardware-based control systems. Learn about non-random parameter initializations and applications in resource-limited environments.
Large Language Models - Will They Keep Getting Bigger?
Explore the future of large language models, discussing scaling challenges, sparse mixtures of experts, improved prompting techniques, and new forms of supervision for enhanced NLP performance.
EfficientML.ai Lecture - Introduction to Efficient Machine Learning
Dive into the world of efficient machine learning with this comprehensive lecture from MIT HAN Lab. Explore cutting-edge techniques and strategies for optimizing ML models, reducing computational costs, and improving overall performance. Learn from exper…
Leaner, Greener and Faster PyTorch Inference with Quantization
Explore PyTorch quantization techniques to optimize neural networks, reducing size and improving speed without sacrificing accuracy. Learn implementation strategies and real-world applications.
Efficiently Fine-Tune and Serve Your Own LLMs
Learn to efficiently fine-tune and deploy large language models, optimizing performance and resource utilization for production environments.
Beyond the Model Zoo - Optimizing Foundation Models for Your Application
Optimize foundation models for specific applications, exploring techniques beyond pre-trained models to enhance performance and efficiency in machine learning projects.
Using Reproducible Experiments to Create Better Machine Learning Models
Enhance ML model efficiency through reproducible experiments. Learn to track hyperparameter, code, and data changes using DVC for grid and random search tuning methods.
A Gentle Introduction to Sparsity with a Concrete Example
Explore sparsification techniques for ML models, including popular methods and a concrete example to understand their benefits.
Accelerating Transformers with Hugging Face Optimum and Infinity
Explore techniques to accelerate Transformer models using Hugging Face's Optimum library and Infinity solution for millisecond-scale latencies in production environments.
Enhance Cost Efficiency in Domain Adaptation with PruneMe
Optimize LLMs through layer pruning, enabling cost-effective domain adaptation and model merging for improved performance in specific applications.
TinyEngine: Transformer and Large Language Models - Lecture 12
Dive into Transformer and LLM architectures, exploring their applications and optimizations for efficient machine learning on resource-constrained devices.
Learn TensorFlow and Deep Learning Fundamentals with Python - Code-First Introduction Part 2/2
Dive deep into TensorFlow and Python, mastering non-linear models, multi-class classification, and advanced techniques for optimizing neural networks and evaluating their performance.
Text Analytics Crash Course with R
Learn text analytics fundamentals, data processing, machine learning models, and visualization techniques using R. Master handling big data and optimizing models for valuable insights from unstructured text.
LLMOps: Como usar Nvidia TensorRT SDK para Inferencia en GPU
Optimiza la inferencia en GPU con Nvidia TensorRT SDK, convirtiendo modelos y comparando tiempos de ejecución en diferentes precisiones de datos.
Advanced Anomaly Detection Made Easy
Advanced anomaly detection techniques for embedded ML, focusing on custom DSP blocks, feature importance, and threshold optimization. Learn to implement these methods for various IoT applications using Edge Impulse.
Reinforcement and Mean-Field Games in Algorithmic Trading - Sebastian Jaimungal
Explore reinforcement learning and mean-field games in algorithmic trading, covering deep Q-learning, reinforced deep Kalman filters, and heterogeneous agent interactions with differing beliefs in financial markets.
AutoML Toolkit Deep Dive - Automating Feature Engineering and Model Optimization
Explore Databricks Labs' AutoML Toolkit for automating feature engineering, model selection, tuning, and deployment. Learn to accelerate machine learning workflows and enhance productivity.
Augmenting Machine Learning with Databricks Labs AutoML Toolkit
Explore how Databricks Labs AutoML Toolkit simplifies and optimizes machine learning processes, from data preparation to model optimization, using financial loan risk data examples.
3D Printing with 3ds Max + TyFlow - Fastest Way to Clean Your Models
Learn efficient techniques to optimize 3D models for printing using TyFlow's VDB tools in 3ds Max. Discover how to create clean, water-tight meshes and avoid common printing issues.
3DXchange 6 Tutorial - Optimizing Sketchup Models for Architectural Rendering
Learn to optimize Sketchup models for rendering in iClone and Indigo. Covers techniques like excluding back faces, smoothing normals, creating sub-props, merging identical meshes, and setting pivot points for efficient customization.
CC3 to Smile Game Builder - Maya Bone Reduction Method
Step-by-step tutorial on reducing bones in Maya for exporting CC3 characters to Smile Game Builder, with real-time demonstrations and helpful links for game development tools.