---
product_id: 304802052
title: "Learning Predictive Analytics with Python"
price: "541.57 DT"
currency: TND
in_stock: true
reviews_count: 5
url: https://www.desertcart.tn/products/304802052-learning-predictive-analytics-with-python
store_origin: TN
region: Tunisia
---

# Learning Predictive Analytics with Python

**Price:** 541.57 DT
**Availability:** ✅ In Stock

## Quick Answers

- **What is this?** Learning Predictive Analytics with Python
- **How much does it cost?** 541.57 DT with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.tn](https://www.desertcart.tn/products/304802052-learning-predictive-analytics-with-python)

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## Description

n practical insights into predictive modelling by implementing Predictive ytics algorithms on public datasets with Python About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Get to grips with the basics of Predictive ytics with Python Learn how to use the popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Who This Book Is For If you wish to learn how to implement Predictive ytics algorithms using Python libraries, then this is the book for you. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about Predictive ytics algorithms, this book will also help you. The book will be beneficial to and can be read by any Data Science enthusiasts. Some familiarity with Python will be useful to get the most out of this book, but it is certainly not a prerequisite. What You Will Learn Understand the statistical and mathematical concepts behind Predictive ytics algorithms and implement Predictive ytics algorithms using Python libraries yze the result parameters arising from the implementation of Predictive ytics algorithms Write Python modules/functions from scratch to execute segments or the whole of these algorithms Recognize and mitigate various contingencies and issues related to the implementation of Predictive ytics algorithms Get to know various methods of importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and numpy Create dummy datasets and simple mathematical simulations using the Python numpy and pandas libraries Understand the best practices while handling datasets in Python and creating predictive models out of them In Detail Social Media and the Internet of Things have resulted in an avalanche of data.

Review: Good book! - This is a good book. I do not understand why there are bad reviews for it. I would like to thank the author for the good job! Well done! Unfortunately, the author deleted the datasets the book uses from the Google drive.
Review: Ok - Book deserves three to four stars max. It is ok and interesting. It is introduces a lot of concepts but shame it doesn't go a little bit more into details especially in the end of the book when talking about clustering and regression. It is one thing to talk about clustering but there is nothing about what to do with it once it is done.there isnt much discussion about regression tree and random forest algorithms which deserve more such as for example what can one do to improve the algos if thstbdont work well or what other algos are available.perhaps simply the book needs to advise on further reading

## Features

- Item Trademark: PACKT PUBLISHING
- manufacturer: Packt Publishing Limited
- Item Weight: pounds, pounds, 1.34, 1.34

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Customer Reviews | 3.4 out of 5 stars 10 Reviews |

## Images

![Learning Predictive Analytics with Python - Image 1](https://m.media-amazon.com/images/I/71Zb9fZlNiL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Good book!
*by A***R on 26 September 2020*

This is a good book. I do not understand why there are bad reviews for it. I would like to thank the author for the good job! Well done! Unfortunately, the author deleted the datasets the book uses from the Google drive.

### ⭐⭐⭐⭐ Ok
*by J***E on 4 October 2017*

Book deserves three to four stars max. It is ok and interesting. It is introduces a lot of concepts but shame it doesn't go a little bit more into details especially in the end of the book when talking about clustering and regression. It is one thing to talk about clustering but there is nothing about what to do with it once it is done.there isnt much discussion about regression tree and random forest algorithms which deserve more such as for example what can one do to improve the algos if thstbdont work well or what other algos are available.perhaps simply the book needs to advise on further reading

### ⭐⭐⭐ Has typos, more suitable for people who know stats already
*by L***S on 24 August 2018*

It tries to tackle relevant topics with predictive modelling, but contains a lot of typos that for someone who has never taken stats before can be misleading. For example in the photo, under the hypothesis test example, Dm should be 21.2 and not 24. May be more suitable for people who already know stats and just need the python aspect, but even then there are bits that need to be read more than once.

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*Product available on Desertcart Tunisia*
*Store origin: TN*
*Last updated: 2026-06-04*