Coding neural networks scikit learn de bitwright caelum (5 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. Print on Demand.

Paperback. Condición: new. Paperback. In a world dominated by massive, complex AI frameworks, the true power players know a secret: the most elegant and efficient predictive models often start with the basics.Master the Foundation of Modern IntelligenceStop getting lost in the noise of over-engineered AI. Coding Neural Networks with Scikit-Learn and Pandasis your definitive guide to reclaiming the "logic" in predictive logic. This book bridges the gap between raw data manipulation and sophisticated neural architectures using the two most trusted tools in the Python ecosystem.Whether you are cleaning messy datasets or building your first Multi-Layer Perceptron, this guide strips away the jargon and replaces it with clarity, code, and results. You will learn to treat data not just as numbers in a table, but as the lifeblood of a living, breathing model.Your Blueprint for Predictive SuccessInside, we move beyond theory to give you the practical skills required in the 2026 tech landscape: Pandas for Power Users: Master advanced data wrangling, feature engineering, and "data-first" preprocessing to ensure your models never starve for quality input.Scikit-Learn Neural Architectures: Build and fine-tune MLPClassifiers and MLPRegressors with precision.The Logic of Prediction: Understand the "why" behind activation functions, backpropagation, and gradient descent without needing a PhD in mathematics.Model Evaluation & Tuning: Use cross-validation and grid search to squeeze every ounce of accuracy out of your networks.Real-World Pipelines: Create seamless workflows that take you from a raw CSV file to a deployed, high-performance predictive engine.Why This Book?Clarity Over Complexity: No unnecessary math. Just the essential concepts and the code to back them up.Immediate Application: Every chapter features hands-on projects designed to be adapted for your professional work.Future-Proof Skills: Master the core principles of neural networks that apply across all frameworks, from Scikit-Learn to PyTorch and beyond.Who Is This Book For?This is the perfect match for Software Engineers and Data Analysts who want to step into the world of AI without the steep learning curve of more academic texts. If you already know basic Python and want to turn your data into a competitive advantage, this book was written for you.The AI revolution is happening now. Don't be a spectator-become the architect.Buy Coding Neural Networks with Scikit-Learn and Pandas today and start building the future of predictive logic. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. In a world dominated by massive, complex AI frameworks, the true power players know a secret: the most elegant and efficient predictive models often start with the basics.Master the Foundation of Modern IntelligenceStop getting lost in the noise of over-engineered AI. Coding Neural Networks with Scikit-Learn and Pandasis your definitive guide to reclaiming the "logic" in predictive logic. This book bridges the gap between raw data manipulation and sophisticated neural architectures using the two most trusted tools in the Python ecosystem.Whether you are cleaning messy datasets or building your first Multi-Layer Perceptron, this guide strips away the jargon and replaces it with clarity, code, and results. You will learn to treat data not just as numbers in a table, but as the lifeblood of a living, breathing model.Your Blueprint for Predictive SuccessInside, we move beyond theory to give you the practical skills required in the 2026 tech landscape: Pandas for Power Users: Master advanced data wrangling, feature engineering, and "data-first" preprocessing to ensure your models never starve for quality input.Scikit-Learn Neural Architectures: Build and fine-tune MLPClassifiers and MLPRegressors with precision.The Logic of Prediction: Understand the "why" behind activation functions, backpropagation, and gradient descent without needing a PhD in mathematics.Model Evaluation & Tuning: Use cross-validation and grid search to squeeze every ounce of accuracy out of your networks.Real-World Pipelines: Create seamless workflows that take you from a raw CSV file to a deployed, high-performance predictive engine.Why This Book?Clarity Over Complexity: No unnecessary math. Just the essential concepts and the code to back them up.Immediate Application: Every chapter features hands-on projects designed to be adapted for your professional work.Future-Proof Skills: Master the core principles of neural networks that apply across all frameworks, from Scikit-Learn to PyTorch and beyond.Who Is This Book For?This is the perfect match for Software Engineers and Data Analysts who want to step into the world of AI without the steep learning curve of more academic texts. If you already know basic Python and want to turn your data into a competitive advantage, this book was written for you.The AI revolution is happening now. Don't be a spectator-become the architect.Buy Coding Neural Networks with Scikit-Learn and Pandas today and start building the future of predictive logic. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…