About this nonfiction
Python Tour In Machine Learning by Md. Akramul Hossain is a nonfiction available to read on EtoBox.
An easy and step by step implementation of machine learning problem is shown in python. You will find 6 machine learning problems and their step by step solutions. Among 6 problems, 4 are supervised learning problems and 2 are unsupervised learning problems. There are 2 problems taken kaggle competitions to get started as beginners. The 6 problems are listed below: Prediction on iris plants dataset (data is taken from sklearn.datasets.load_iris()) California Housing dataset (data is taken from (sklearn.datasets.fetch_california_housing()) Titanic – Machine Learning from Disaster (kaggle link : https://www.kaggle.com/c/titanic) House Prices Advanced Regression Techniques (kaggle link : https://www.kaggle.com/c/house-prices-advanced-regression-techniques ) An artificial dataset made by sklearn.datasets.make_blobs() to understand unsupervised learning Market basket analysis (kaggle link : https://www.kaggle.com/vjchoudhary7/customer- segmentation-tutorial-in-python ) In chapter 1, some basic machine learning concepts is defined easily. In chapter 2, popular used python libraries is introduced. How to install, how to use etc. In chapter 3, Implementation of ML classification technique
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Md. Akramul Hossain
- Publisher
- John Wiley & Sons, Incorporated
- Published
- 1973
- Language
- EN
- ISBN
- 9780471223610
- Category
- nonfiction
- Subjects
- Computer Science, Science, Engineering