Links to AI, LLM, ML, RPA Articles and Learning Opportunities

Introduction to Large Language Models
Getting Started with LangChain
Generative AI Prompt Engineering | Click Prompt Design
Build with Generative AI
MIT Explains Generative AI
Training Large Language Models on Google Cloud
Generative AI for Developers
The future of generative AI is niche, not generalized
Proactive Risk Management in Generative AI

ML Articles

Introduction to Machine Learning with KNIME
MAXIMIZING ROI FOR MACHINE LEARNING
Cross-industry standard process for data mining
What IT needs to know about data mining

NVIDIA

NVIDIA GTC 2024

AI and LLM Articles

HELM-Holistic Evaluation of Large Language Models NEW!!
QUEST Algorithm NEW!!

Common ML Algorithms

CHAID Algorithm NEW!!
Decision Tree Learning
CART Algorithm NEW!!
Link to Apple's Machine Learning Research

FREE AI TRAINING

The best free AI Training Courses

Introduction to Generative AI

Beginner

Prompt Design in Vertex AI
Introduction to Duet AI in Google Workspace

Intermediate

Conversational AI on Vertex AI and Dialogflow CX
Attention Mechanism
Create Image Captioning Models
Encoder-Decoder Architecture

Advanced

ML Pipelines
Google Cloud Solutions IIData/ ML

DISCLAIMER: Most course materials are free to consume. But labs may need a subscription, credits, or participation in campaigns to be accessed.

Learn Databricks NEW!!
PAIR Explorables

Big ideas in machine learning, simply explained

The rapidly increasing usage of machine learning raises complicated questions: How can we tell if models are fair? Why do models make the predictions that they do? What are the privacy implications of feeding enormous amounts of data into models? This ongoing series of interactive essays will walk you through these important concepts.