You are a data scientist. Every day, you stare at reams of data trying to apply the latest and brightest of models to uncover new insights, but there seems to be an endless supply of obstacles. Your colleagues depend on you to monetize your firm’s data – and the clock is ticking. What do you do?

Troubleshooting Python Machine Learning is the answer.

Machine learning gives you powerful insights into data. Today, implementations of machine learning are adopted throughout Industry and its concepts are many. Machine learning is pervasive in the modern data-driven world. Used across many fields such as search engines, robotics, self-driving cars, and more.

The effective blend of Machine Learning with Python, helps in implementing solutions to real-world problems as well as automating analytical model.

This comprehensive 3-in-1 course is a comprehensive, practical tutorial that helps you get superb insights from your data in different scenarios and deploy machine learning models with ease. Explore the power of Python and create your own machine learning models with this project-based tutorial. Try and test solutions to solve common problems, while implementing Machine learning with Python.

Contents and Overview

This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Python Machine Learning Projects, covers Machine Learning with Python’s insightful projects. This video is a unique blend of projects that teach you what Machine Learning is all about and how you can implement machine learning concepts in practice. Six different independent projects will help you master machine learning in Python. The video will cover concepts such as classification, regression, clustering, and more, all the while working with different kinds of databases. You’ll be able to implement your own machine learning models after taking this course.

The second course, Python Machine Learning Solutions, covers 100 videos that teach you how to perform various machine learning tasks in the real world. Explore 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. Discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning

The third course, Troubleshooting Python Machine Learning, covers practical and unique solutions to common Machine Learning problems that you face. Debug your models and research pipelines, so you can focus on pitching new ideas and not fixing old bugs. By the end of the course, you’ll get up-and-running via Machine Learning with Python’s insightful projects to perform various Machine Learning tasks in the real world.