Browsing: Optimization

best_C = best[“params”][“C”] best_solver = best[“params”][“solver”] final_pipe = Pipeline([ (“scaler”, StandardScaler()), (“clf”, LogisticRegression( C=best_C, solver=best_solver, penalty=”l2″, max_iter=2000, random_state=42 )) ]) with mlflow.start_run(run_name=”final_model_run”) as final_run: final_pipe.fit(X_train, y_train)…

In this tutorial, we build a production-style Route Optimizer Agent for a logistics dispatch center using the latest LangChain agent APIs. We design a tool-driven workflow…

In this tutorial, we implement an end-to-end Direct Preference Optimization workflow to align a large language model with human preferences without using a reward model. We…

Earth observation (EO) constellations capture huge volumes of high-resolution imagery every day, but most of it never reaches the ground in time for model training. Downlink…

We implement an advanced, end-to-end Kornia tutorial and demonstrate how modern, differentiable computer vision can be built entirely in PyTorch. We start by constructing GPU-accelerated, synchronized…

Microsoft Research has released OptiMind, an AI based system that converts natural language descriptions of complex decision problems into mathematical formulations that optimization solvers can execute.…

Private equity firm Everstone Capital is bringing together India’s Wingify — a company that helps businesses test different versions of their websites to improve sales and…

How can we build AI systems that keep learning new information over time without forgetting what they learned before or retraining from scratch? Google Researchers has…

In this tutorial, we build a Wet-Lab Protocol Planner & Validator that acts as an intelligent agent for experimental design and execution. We design the system…