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In this text, I'll reveal tips on how to move from simply forecasting outcomes to actively intervening in systems to steer toward desired goals. With hands-on examples in predictive maintenance, I'll show how data-driven...

Master fine-tuning Transformers, comparing deep learning architectures, and deploying sentiment evaluation modelsThis project provides an in depth, step-by-step guide to fine-tuning a Transformer model for sentiment classification while taking you thru the complete Machine...

If someone advises you to “know your limits,” they’re likely suggesting you...

Dive into MLOPS basics to enhance your skills for designing, developing, and deploying computer vision projects for real-world, industrial applicationsNowadays, we encounter (and perhaps produce on our own) many computer vision projects, where AI...

with Ollama, LangChain, LangGraph (No GPU, No APIKEY)(All images are by the writer unless otherwise noted)IntroPrompt Engineering is the practice of designing and refining prompts (text inputs) to boost the behavior of Large Language...

The arrival and progress of generative AI video has prompted many casual observers to predict that machine learning will prove the death of the movie industry as we comprehend it – as a substitute,...

A workflow and code walkthrough for constructing a Bayesian regression model in STANNote: Try my previous article for a practical discussion on why Bayesian modeling could also be the appropriate selection in your task.This...

import torch import torch.nn.functional as F class DPOTrainer: def __init__(self, model, ref_model, beta=0.1, lr=1e-5): self.model = model self.ref_model =...