About this video
ML is becoming increasingly pervasive in the modern data-driven world. This course takes a hands-on approach and demonstrates how you can perform various machine learning tasks on real-world data. The course starts by talking about various realms in machine learning followed by practical examples. It then moves on to discuss the more complex algorithms, such as Support Vector Machines, Extremely Random Forests, Hidden Markov Models, Sentiment Analysis, and Conditional Random Fields. You will learn how to make informed decisions about the types of algorithm that you need to use and how to implement these algorithms to get the best possible results.
After you are comfortable with machine learning, this course teaches you how to build real-world machine learning applications step by step. Further, we’ll explore deep learning with TensorFlow, which is currently the hottest topic in data science. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change the way you look at data. You will also learn how to train your machine to build new models that help make sense of deeper layers within your data.
By the end of this course, you should be able to solve real-world data analysis challenges using innovative and cutting-edge machine learning techniques.
Style and Approach
With easy-to-follow practical examples, this course will help you gain a grip on each and every aspect of machine learning. Covering all the powerful algorithms of machine learning, we’ll teach you how to build different interesting machine learning applications and finally cover deep learning with TensorFlow.
This course is a blend of text, videos, code examples, and assessments, all packaged up keeping your journey in mind. The curator of this course has combined some of the best that Packt has to offer in one complete package. It includes content from the following Packt products:
- Python Machine Learning Cookbook by Prateek Joshi
- Python Machine Learning Solutions by Prateek Joshi
- Python Machine Learning Blueprints by Alexander T. Combs
- Python Machine Learning Projects by Alexander T. Combs
- Deep Learning with TensorFlow by Dan Van Boxel
- Getting Started with TensorFlow by Giancarlo Zaccone
- Python Machine Learning by Sebastian Raschka
- Building Machine Learning Systems with Python - Second Edition by Luis Pedro Coelho and Willi Richert
Note: This interactive EPUB adheres to the latest specification, and requires that your reader supports video and interactive content. We recommend using Readium with the latest stable version of Google Chrome, or iBooks for OSX.
- Publication date:
- January 2017
- 7 hours