Python Machine Learning - Part 1
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Python Machine Learning - Part 1

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics
0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
27 students enrolled
Created by Packt Publishing
Last updated 2/2017
English
Curiosity Sale
Current price: $10 Original price: $125 Discount: 92% off
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Includes:
  • 3.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Discover the different types of machine learning and know when to use them
  • Explore machine learning algorithms and implement them in Python
  • Use powerful open source machine learning libraries to train predictive models
  • Use pandas, NumPy, and matplotlib to manipulate data
  • Evaluate and fine-tune machine learning models
View Curriculum
Requirements
  • This step-by step guide will walk you through connecting the fundamental theory of machine learning with practical tips for implementation using Python, complete with visualizations and hands-on code examples.
Description

Machine learning and predictive analytics are transforming the way that businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, and is becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data. Its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.

This video gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science courseis invaluable. It coversa wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuresguidance and tips on everything from sentiment analysis to neural networks. With this video,you’ll soon be able to answer some of the most important questions facing you and your organization.

About the Author

Jason is an avid Python machine learning practitioner, obsessed college football fan, and German Shepherd lover. Jason completed his graduate and undergraduate degrees at Arizona State University. During that time, Jason conducted statistical analysis and visual communication analysis for the Arizona State Football program and was part of a 4-person team that placed 3rd nationally in The Great Minds Challenge: IBM Watson Edition, a collegiate machine learning competition. Jason currently works for TransDev and zTrip where he combines data from multiple enterprise sources to gain actionable insights about customers. Jason also recently taught a Machine Learning workshop for a Fortune 500 company and is currently learning to leverage the Apache Spark ecosystem using both Scala and Python.

Who is the target audience?
  • If you want to find out how to use Python to start answering critical questions using your data, this video is ideal. Whether you want to get started from scratch or want to extend your data science knowledge, this is an essential resource.
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About the Instructor
Packt Publishing
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