Python Machine Learning Cookbook - download pdf or read online

Key Features

• Understand which algorithms to take advantage of in a given context with the aid of this interesting recipe-based guide
• Learn approximately perceptrons and notice how they're used to construct neural networks
• Stuck whereas making feel of pictures, textual content, speech, and genuine property? This consultant will come for your rescue, displaying you ways to accomplish laptop studying for every this type of utilizing numerous techniques

Book Description

Machine studying is turning into more and more pervasive within the smooth data-driven global. it truly is used widely throughout many fields similar to se's, robotics, self-driving vehicles, and more.

With this booklet, you'll how one can practice a variety of computer studying projects in numerous environments. we will begin via exploring more than a few real-life eventualities the place computing device studying can be utilized, and examine a number of construction blocks. in the course of the ebook, you are going to use a wide selection of computer studying algorithms to unravel real-world difficulties and use Python to enforce those algorithms.

You'll detect easy methods to take care of a number of forms of info and discover the variations among computer studying paradigms reminiscent of supervised and unsupervised studying. We additionally conceal various regression thoughts, type algorithms, predictive modeling, facts visualization thoughts, advice engines, and extra with the aid of real-world examples.

What you'll learn

• Explore type algorithms and practice them to the source of revenue bracket estimation problem
• Use predictive modeling and use it on real-world problems
• Understand the way to practice marketplace segmentation utilizing unsupervised learning
• Explore information visualization options to engage along with your facts in different ways
• Find out easy methods to construct a suggestion engine
• Understand the best way to engage with textual content info and construct versions to investigate it
• Work with speech info and realize spoken phrases utilizing Hidden Markov Models
• Analyze inventory industry facts utilizing Conditional Random Fields
• Work with photo info and construct platforms for picture reputation and biometric face recognition
• Grasp how one can use deep neural networks to construct an optical personality reputation system

About the Author

Prateek Joshi is a man-made Intelligence researcher and a broadcast writer. He has over 8 years of expertise during this box with a first-rate specialise in content-based research and deep studying. He has written books on machine imaginative and prescient and computer studying. His paintings during this box has led to a number of patents, tech demos, and examine papers at significant IEEE conferences.

People from around the globe stopover at his weblog, and he has obtained greater than one million web page perspectives from over two hundred nations. He has been featured as a visitor writer in famous tech magazines. He enjoys running a blog approximately issues, equivalent to synthetic Intelligence, Python programming, summary arithmetic, and cryptography. you could stopover at his weblog at www.prateekvjoshi.com.

He has gained many hackathons using a large choice of applied sciences. he's an avid coder who's captivated with construction game-changing items. He graduated from collage of Southern California, and he has labored at businesses reminiscent of Nvidia, Microsoft learn, Qualcomm, and a pair of early degree start-ups in Silicon Valley. you could research extra approximately him on his own web site at www.prateekj.com.

Table of Contents

1. The Realm of Supervised Learning
2. Constructing a Classifier
3. Predictive Modeling
4. Clustering with Unsupervised Learning
5. Building advice Engines
6. Analyzing textual content Data
7. Speech Recognition
8. Dissecting Time sequence and Sequential Data
9. Image content material Analysis
10. Biometric Face Recognition
11. Deep Neural Networks
12. Visualizing Data