Parameter Tuning Courses and Certifications

Association for Computing Machinery (ACM)

Understanding Parameter Spaces Using Local Optima Networks

Explores using Local Optima Networks to analyze parameter landscapes of Particle Swarm Optimization, revealing complex structures influenced by underlying objective functions.

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

Support Vector Machines in R

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Density-Based Clustering Simplified

Master density-based clustering through DBSCAN algorithm implementation, from basic concepts to advanced parameter tuning, with hands-on Python examples using scikit-learn.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

XGBoost for Beginners

Master XGBoost fundamentals to build faster, accurate models with parameter tuning, early stopping techniques, and native interface configuration for optimal performance.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Density-Based Clustering Simplified

Master DBSCAN clustering techniques to identify unique cluster shapes through connectivity and density functions, with hands-on R implementation and parameter tuning.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Coursera

OpenAI: Consistent Response Strategies

14 ratings at Coursera

Learn strategies to enhance AI-generated responses' consistency using OpenAI's language models. Explore fine-tuning, prompt engineering, and post-processing techniques to improve reliability and user satisfaction.

• Coursera
• 2 hours 36 minutes
• On-Demand
• Paid Course

Coursera

Optimize with GA & RL

Master genetic algorithms and Q-learning for supply chain optimization, comparing AI methods with traditional approaches using real-world datasets and Python implementation.

• Coursera
• 3 hours 2 minutes
• On-Demand
• Paid Course

AI Bites

LoRA: Low-Rank Adaptation for Parameter-Efficient Large Language Model Fine-Tuning

Discover how LoRA enables efficient fine-tuning of large language models through low-rank adaptation, from fundamental concepts to practical implementation in transformer architectures.

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

Discover AI

Parameter-Efficient Fine-Tuning with LoRA - Optimizing LLMs for Local GPU Training

Master PEFT LoRA techniques to efficiently fine-tune large language models on local GPUs through low-rank adaptation, reducing memory requirements while maintaining model performance.

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

GAIA

P-Tuning: A Parameter Efficient Tuning to Boost LLM Performance

Explore p-tuning, a prompt-learning method for adapting LLMs to low-resource languages. Learn to enhance NLP task performance using NVIDIA NeMo's continuous multitask learning of virtual prompts.

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

Trelis Research

Very Few Parameter Fine-Tuning with ReFT and LoRA

Explore advanced fine-tuning techniques ReFT and LoRA for efficient parameter optimization in transformer models. Learn implementation, comparison, and practical tips for improved model performance.

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

Discover AI

Parameter Efficient Fine-Tuning with Multiple LoRA Adapters for Large Language Models

Dive into parameter efficient fine-tuning with LoRA adapters, exploring matrix factorization, SVD, and advanced configurations for optimizing large language models.

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

Generative AI - Adapting LLMs with Parameter-Efficient Fine-Tuning - Lecture 10

Master parameter-efficient fine-tuning techniques for adapting large language models, covering GPT versions, training data nuances, and instruction tuning methods.

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

Toronto Machine Learning Series (TMLS)

Prompt Optimization and Parameter Efficient Fine Tuning for Large Language Models

Explore state-of-the-art prompt optimization techniques and parameter efficient fine-tuning methods for large language models to enhance performance on various tasks.

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

Database Parameter Auto-Tuning Through CI/CD Pipelines

Learn how Yahoo Japan automates MySQL parameter tuning using machine learning in CI/CD pipelines, addressing challenges in cloud computing and improving database performance.

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