Idézet:Understand data analysis pipelines using machine learning algorithms and techniques with this practical guide

Key Features
Prepare and clean your data to use it for exploratory analysis, data manipulation, and data wrangling
Discover supervised, unsupervised, probabilistic, and Bayesian machine learning methods
Get to grips with graph processing and sentiment analysis
Book Description
Data analysis enables you to generate value from small and big data by discovering new patterns, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you'll get up and running using Python for data analysis by exploring the different phases used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines.

Starting with the essential statistical and data analysis fundamentals using Python, you'll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You'll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you'll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. You'll also work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask.

Idézet:? 9781806022878.epub (Avinash Navlani, Cornellius Yudha Wijaya) (2026) (9.29 MB)

Idézet:A kódrészlet megtekintéséhez be kell jelentkezned, vagy nincs jogosultságod a tartalom megtekintéséhez.

Idézet:A kódrészlet megtekintéséhez be kell jelentkezned, vagy nincs jogosultságod a tartalom megtekintéséhez.