machine learning
Posts
- Have we hit the AI ceiling? Understand why prompt-only agents fail in production and why hybrid architecture is the only path to systems that actually deliver real-world value.
- While the world fights over trillions of parameters, Google released a model that runs on a toaster and actually gets things done. Welcome to the era of Utility AI.
Background
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Provider: Alura
Focused on the operationalization of ML. Developed interactive web-based dashboards using Plotly Dash to visualize model outputs, enabling stakeholders to interact with real-time predictions and data insights.
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Provider: Alura
Comprehensive 48-hour specialization covering the end-to-end Machine Learning lifecycle. Focused on data preprocessing, feature engineering, and deploying classification/regression models. Validated expertise in model evaluation metrics and production-ready ML workflows.
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Provider: Alura
Implementation of unsupervised learning techniques. Focused on partitioning data using algorithms like K-Means, evaluating cluster validity, and extracting patterns from high-dimensional datasets without prior labeling.
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Provider: Alura
Statistical analysis and predictive modeling. Applied Linear Regression to identify correlations between variables and quantify the impact of features on target outcomes using statistical significance tests.
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Provider: Alura
Developed robust classification pipelines using SKLearn. Focused on model selection, cross-validation, and performance metrics (Precision, Recall, F1-Score) to solve multi-class and binary classification problems.
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Provider: Alura
Applied Keras for predictive modeling, focusing on hyperparameter tuning, model evaluation metrics, and optimizing neural networks for high-accuracy forecasting in production environments.