---
product_id: 379713051
title: "Blueprints for Text Analytics using Python: Machine Learning Based Solutions for Common Real World (NLP) Applications"
price: "€ 162.69"
currency: EUR
in_stock: true
reviews_count: 5
url: https://guadeloupe.desertcart.com/products/379713051-blueprints-for-text-analytics-using-python-machine-learning-based-solutions
store_origin: GP
region: Guadeloupe
---

# Python-powered practical code 1.5 lbs of expert NLP insights 54 reviews, 4.6-star trusted guide Blueprints for Text Analytics using Python: Machine Learning Based Solutions for Common Real World (NLP) Applications

**Price:** € 162.69
**Availability:** ✅ In Stock

## Summary

> 📈 Unlock the power of text—turn words into winning strategies!

## Quick Answers

- **What is this?** Blueprints for Text Analytics using Python: Machine Learning Based Solutions for Common Real World (NLP) Applications
- **How much does it cost?** € 162.69 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [guadeloupe.desertcart.com](https://guadeloupe.desertcart.com/products/379713051-blueprints-for-text-analytics-using-python-machine-learning-based-solutions)

## Best For

- Customers looking for quality international products

## Why This Product

- Free international shipping included
- Worldwide delivery with tracking
- 15-day hassle-free returns

## Key Features

- • **Data to Decisions:** Transform raw text into business intelligence with ease
- • **Semantic Exploration:** Leverage word embeddings and knowledge graphs to uncover hidden connections
- • **Explainable AI Insights:** Understand and visualize model results for confident decisions
- • **Machine Learning Mastery:** Hands-on classification, topic modeling, and summarization
- • **Blueprints for Real-World NLP:** Step-by-step Python recipes for actionable text analytics

## Overview

This 1.5-pound e-book from O'Reilly Media offers data scientists and developers practical, Python-based blueprints for solving common NLP challenges. With 54 reviews averaging 4.6 stars, it delivers real-world case studies, detailed code, and explainable AI techniques to help professionals extract actionable insights from text data and elevate their analytics game.

## Description

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations

Review: the "so what" behind the code and analysis is present - What distinguishes this book from others in the same area is that all recipes included lead to an actual insight at the end, authors don't forget the so what behind the code and the analysis. Recipes are combined with some theory background too to help build intuition about the key concepts, which is useful. I come from an R background, but found the Python code easy to follow (use of many familiar data frame concepts).
Review: El contenido es de otro libro. No lo compren.

## Features

- Item Trademark: O'REILLY MEDIA
- manufacturer: O'Reilly Media, Inc, USA
- Item Weight: pounds, pounds, 1.5, 1.5

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Customer Reviews | 4.6 out of 5 stars 54 Reviews |

## Images

![Blueprints for Text Analytics using Python: Machine Learning Based Solutions for Common Real World (NLP) Applications - Image 1](https://m.media-amazon.com/images/I/91uU8BGFw3L.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ the "so what" behind the code and analysis is present
*by A***U on 31 January 2022*

What distinguishes this book from others in the same area is that all recipes included lead to an actual insight at the end, authors don't forget the so what behind the code and the analysis. Recipes are combined with some theory background too to help build intuition about the key concepts, which is useful. I come from an R background, but found the Python code easy to follow (use of many familiar data frame concepts).

### ⭐ El contenido es de otro libro. No lo compren.
*by A***N on 14 April 2023*



### ⭐⭐⭐⭐⭐ Outstanding
*by D***R on 27 March 2023*

I noticed this in my bookshelf last week, and apparently I had bought it and forgotten to even take a look. I started skimming and was surprised at the usefulness of this book. It is very good. Pros: It does an excellent job of explaining fundamentals and common workflows of NLP. I know this, because my work is primarily NLP. It covers fundamentals quite well, such as tokenization, word vextors, similarity, classification; topic modeling, etc. It also gets into topic modeling. Later, there is a whole chapter about explainability of NLP models, which I am excited to read. I adore NLP insights. Cons: Like cookbooks, most things are blueprints. That’s very useful if you like those kinds of boxy explanations. I personally prefer typical book format, but this works too. I just find it a little distracting. But the book is rare in that it really explains the fundamentals. Many books junp straight to ML, or are only ML. This is good for foundation. It is also really useful and practical. This is now in my top four favorite NLP books. The pros absolutely outweigh the cons. And the datasets seem wonderful. I’m still reading and learning from this. Really glad I noticed I forgot to read.

## Frequently Bought Together

- Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications
- Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems
- Natural Language Processing with Transformers, Revised Edition

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*Last updated: 2026-08-17*