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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

Product type Paperback

Published in Jul 2019

Publisher Packt

ISBN-13 9781838552862

Length 426 pages

Edition 1st Edition

Languages

Python

Tools

Combine

Concepts

Data Science

Authors (3):

Rohan Chopra

Mohamed Noordeen Alaudeen

Aaron England

View More author details

Table of Contents (10) Chapters

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

Keras

Keras is an open-source, high-level neural network API written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit (CNTK), or Theano. Keras was developed to enable fast experimentation and thus help in rapid application development. Using Keras, one can get from idea to result with the least possible delay. Keras supports almost all the latest data science models relating to neural networks due to the huge community support. It contains multiple implementations of commonly used building blocks such as layers, batch normalization, dropout, objective functions, activation functions, and optimizers. Also, Keras allows users to create models for smartphones (Android and iOS), the web, or for the Java Virtual Machine (JVM). With Keras, you can train your models on your GPU without any change in code.

Given all these features of Keras, it is imperative for data scientists to learn how to use all the different aspects of the library. Mastering the use of Keras...

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Authors (3)

Rohan Chopra

Rohan Chopra

Rohan Chopra graduated from Vellore Institute of Technology with a bachelors degree in computer science. Rohan has an experience of more than 2 years in designing, implementing, and optimizing end-to-end deep neural network systems. His research is centered around the use of deep learning to solve computer vision-related problems and has hands-on experience working on self-driving cars. He is a data scientist at Absolutdata.

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England

England

Aaron England earned a Ph.D from the University of Utah in Exercise and Sports Science with a cognate in Biostatistics. Currently, he resides in Scottsdale, Arizona where he works as a data scientist at Natural Partners Fullscript.

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Mohamed Noordeen Alaudeen

Mohamed Noordeen Alaudeen

Mohamed Noordeen Alaudeen is a lead data scientist at Logitech. Noordeen has 7+ years of experience in building and developing end-to-end BigData and Deep Neural Network Systems. It all started when he decided to engage the rest of his life for data science. He is Seasonal data science and big data trainer with both Imarticus Learning and Great Learning, which are two of the renowned data science institutes in India. Apart from his teaching, he does contribute his work to open-source. He has over 90+ repositories on GitHub, which have open-sourced his technical work and data science material. He is an active influencer( with over 22,000+ connections) on Linkedin, helping the data science community.

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