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Data Science  with Python

You're reading from   Data Science with Python Combine Python with machine learning principles to discover hidden patterns in raw data

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Product type Paperback
Published in Jul 2019
Publisher Packt
ISBN-13 9781838552862
Length 426 pages
Edition 1st Edition
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Authors (3):
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Rohan Chopra Rohan Chopra
Author Profile Icon Rohan Chopra
Rohan Chopra
Mohamed Noordeen Alaudeen Mohamed Noordeen Alaudeen
Author Profile Icon Mohamed Noordeen Alaudeen
Mohamed Noordeen Alaudeen
Aaron England Aaron England
Author Profile Icon Aaron England
Aaron England
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Toc

Table of Contents (10) Chapters Close

About the Book 1. Introduction to Data Science and Data Pre-Processing FREE CHAPTER 2. Data Visualization 3. Introduction to Machine Learning via Scikit-Learn 4. Dimensionality Reduction and Unsupervised Learning 5. Mastering Structured Data 6. Decoding Images 7. Processing Human Language 8. Tips and Tricks of the Trade 1. Appendix

Installation and Setup

Open Anaconda Prompt and follow these steps to get your system ready for data science. We will create a new environment on Anaconda in which we will install all the required libraries and run our code:

  1. To create a new environment and install all the libraries, download the environment file from https://github.com/TrainingByPackt/Data-Science-with-Python/blob/master/environment.yml and run the following command:

    conda env create -f environment.yml

  2. To activate the environment, run this command:

    conda activate DataScience

    For this book, whenever you are asked to open a terminal, you need to open Anaconda Prompt, activate the environment, and then proceed.

  3. Jupyter Notebook allows us to run code and experiment in code blocks. To start Jupyter Notebook run the following inside the DataScience environment:

    jupyter notebook

    A new browser window will open with the Jupyter interface. You can then navigate to the project location and run the Jupyter Notebooks.

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