---
product_id: 260876196
title: "Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications"
price: "S/.328"
currency: PEN
in_stock: true
reviews_count: 12
url: https://www.desertcart.pe/products/260876196-blueprints-for-text-analytics-using-python-machine-learning-based-solutions
store_origin: PE
region: Peru
---

# Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications

**Price:** S/.328
**Availability:** ✅ In Stock

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- **What is this?** Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications
- **How much does it cost?** S/.328 with free shipping
- **Is it available?** Yes, in stock and ready to ship
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## Description

Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications [Albrecht, Jens, Ramachandran, Sidharth, Winkler, Christian] on desertcart.com. *FREE* shipping on qualifying offers. Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications

Review: Outstanding - 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.
Review: A must to have by desk side when working on any NLP task - I will start with a big thanks to the book authors for sharing their NLP wisdom. I have learned a lot from this book and ended up implementing the learnings at work (daily tickets) to my Computer Science Master's project. the chapters of 4,5,6, 8,9,10 were most used chapters in my use case. the blueprints are well explained and well documented. One recommendation is to download their code from GitHub and start using your own data to see the real magic.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #1,533,856 in Books ( See Top 100 in Books ) #65 in Data Mining (Books) #83 in Data Modeling & Design (Books) #99 in Natural Language Processing (Books) |
| Customer Reviews | 4.6 4.6 out of 5 stars (60) |
| Dimensions  | 7 x 0.75 x 9.25 inches |
| Edition  | 1st |
| ISBN-10  | 149207408X |
| ISBN-13  | 978-1492074083 |
| Item Weight  | 2.31 pounds |
| Language  | English |
| Print length  | 422 pages |
| Publication date  | January 12, 2021 |
| Publisher  | O'Reilly Media |

## 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

### ⭐⭐⭐⭐⭐ Outstanding
*by D***R on March 27, 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.

### ⭐⭐⭐⭐⭐ A must to have by desk side when working on any NLP task
*by G***N on June 16, 2022*

I will start with a big thanks to the book authors for sharing their NLP wisdom. I have learned a lot from this book and ended up implementing the learnings at work (daily tickets) to my Computer Science Master's project. the chapters of 4,5,6, 8,9,10 were most used chapters in my use case. the blueprints are well explained and well documented. One recommendation is to download their code from GitHub and start using your own data to see the real magic.

### ⭐⭐⭐⭐⭐ Start here to get into NLP in 2021
*by B***Y on June 27, 2021*

Exceptional introduction to NLP using Python and spaCy. This is a great book for working programmers who are looking to learn NLP by applying examples which are much more developed than those found in other cookbook texts. Unlike older Python books this skips NLTK and this focuses on modern libraries and tools which are more robust for production use. If you want to get an idea of the content before purchasing, you should review the chapter by chapter source code and notebooks on GitHub. They

## 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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*Product available on Desertcart Peru*
*Store origin: PE*
*Last updated: 2026-04-30*