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 course 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 course is invaluable. It covers a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and features guidance 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.
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.
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
Prior of knowledge of Python is needed
Who is this course intended for?
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.