Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics
About This Video
Leverage Python’s most powerful open source libraries for deep learning, data wrangling, and data visualization
Get to know effective strategies and best practices to improve and optimize machine learning systems and algorithms
Ask—and answer— tough questions of your data with robust statistical models, built for a range of datasets
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.
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. You can find him on LinkedIn(https://www.linkedin.com/in/wolosonovich). You can also write to him at firstname.lastname@example.org or email@example.com