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Python Machine Learning Solutions

100 videos that teach you how to perform various machine learning tasks in the real world.

Course Description

Machine learning is increasingly pervasive in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more.
With this course, you will learn how to perform various machine learning tasks in different environments. We’ll start by exploring a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the course, you’ll use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.
You’ll discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modelling, data visualization techniques, recommendation engines, and more with the help of real-world examples.

Learning Outcomes

Explore classification algorithms and apply them to the income bracket estimation problem
Use predictive modeling and apply it to real-world problems
Understand how to perform market segmentation using unsupervised learning
Explore data visualization techniques to interact with your data in diverse ways
Find out how to build a recommendation engine
Understand how to interact with text data and build models to analyze it
Work with speech data and recognize spoken words using Hidden Markov Models
Analyze stock market data using Conditional Random Fields
Work with image data and build systems for image recognition and biometric face recognition
Grasp how to use deep neural networks to build an optical character recognition system

Pre-requisite

This course is friendly to Python beginners, but familiarity with Python programming would certainly be useful to play around with the code.

Who is this course intended for?

This video is for Python programmers who are looking to use machine-learning algorithms to create real-world applications. This course is friendly to Python beginners, but familiarity with Python programming would certainly be useful to play around with the code.

These independent videos teach you how to perform various machine learning tasks in different environments. Each of the video in the section will cover a real-life scenario.


Your Instructor


Packt Publishing
Packt Publishing

Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.


Class Curriculum



Frequently Asked Questions


When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

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