AnyML User Journey - Automated Machine Learning Platform скачать в хорошем качестве

AnyML User Journey - Automated Machine Learning Platform

🔍 What You’ll Learn in This Video: AnyML User Journey In this walkthrough, you'll master the entire AnyML process—from uploading raw data to deploying a production-ready model: 📁 Data Upload & Experiment Setup Start by uploading a dataset (e.g., telco‑churn.csv), naming your experiment, and selecting a target feature (or choose unsupervised options like anomaly detection). ⚙️ Advanced Settings Explore options for data preprocessing (e.g., correlation filters, subsampling) and training configurations—including optimization methods, iteration limits, and the ability to add custom evaluation metrics. 🚀 Model Training & Comparison Run the experiment using default or advanced settings. The leaderboard presents top models (e.g., XGBoost, ExtraTrees, Random Forest optimized with ASHA or PBT‑Custom). Analyze results with feature importance, performance metrics (accuracy, precision, recall), visual tools (ROC, Precision‑Recall curves, Confusion Matrix), explainers (SHAP, Permutation Importance), and view optimized hyperparameters. 🔁 Iterative Tuning See how tweaking parameters (like correlation thresholds) affects model performance and learn to interpret feature removal via preprocessing logs. 🔧 Scenario Builder & Validation Use the Scenario Builder's Prediction, Batch, Counterfactual, and What‑If modes to test hypotheses and validate model decisions under different scenarios. ✅ One-Click Deployment & Monitoring Deploy your chosen model with a single click. Get a model URL, sample input/output, and a ready-to-use API. Monitor real-time performance, track data drift, receive retraining alerts, and assess operational metrics. By the end of this video, you’ll confidently navigate the full AnyML user journey: upload → train → analyze → tune → deploy → monitor—unlocking predictive power for your data projects. For more resources or support, visit anyml.com or contact info@anyml.com.