The Data Science Workshop (ebook) Katowice

Where there’s data, there’s insight. With so much data being generated, there is immense scope to extract meaningful information that’ll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you’ll open new career paths and opportunities.The …

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Opis

Where there’s data, there’s insight. With so much data being generated, there is immense scope to extract meaningful information that’ll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you’ll open new career paths and opportunities.The Data Science Workshop begins by introducing different types of projects and showing you how to incorporate machine learning algorithms in them. You’ll learn to select a relevant metric and even assess the performance of your model. To tune the hyperparameters of an algorithm and improve its accuracy, you’ll get hands-on with approaches such as grid search and random search.Next, you’ll learn dimensionality reduction techniques to easily handle many variables at once, before exploring how to use model ensembling techniques and create new features to enhance model performance. In a bid to help you automatically create new features that improve your model, the book demonstrates how to use the automated feature engineering tool. You’ll also understand how to use the orchestration and scheduling workflow to deploy machine learning models in batch.By the end of this book, you’ll have the skills to start working on data science projects confidently. By the end of this book, you’ll have the skills to start working on data science projects confidently. Spis treści: 1. Introduction to Data Science in Python2. Regression3. Binary Classification4. Multiclass Classification with RandomForest5. Performing Your First Cluster Analysis6. How to Assess Performance7. The Generalization of Machine Learning Models8. Hyperparameter Tuning9. Interpreting a Machine Learning Model10. Analyzing a Dataset11. Data Preparation12. Feature Engineering13. Imbalanced Datasets14. Dimensionality Reduction15. Ensemble Learning

Specyfikacja

Podstawowe informacje

Autor
  • Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, Dr. Samuel Asare
Rok wydania
  • 2020
Format
  • PDF
  • MOBI
  • EPUB
Ilość stron
  • 824
Kategorie
  • Programowanie
Wybrane wydawnictwa
  • Packt Publishing