A comprehensive course to teach you Machine Learning on Python & R, accurate predictions, powerful analyses, robust Machine Learning models; how to handle Reinforcement Learning, NLP, Deep Learning, Dimensionality Reduction etc.
This course has been designed by two professional Data Scientists who will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. The ten parts of this course go from Data Preprocessing to Classification, Clustering, Deep Learning etc.
Moreover, the course is packed with practical exercises which are based on live examples, giving you hands-on practice building your own models.
And as a bonus, you get both Python and R code templates which you can download and use on your own projects; 19 articles; full lifetime access; certificate of completion.
Welcome to the course!
Part 1: Data Preprocessing
Part 2: Regression
Part 3: Classification
Part 4: Clustering
Part 5: Association Rule Learning
Part 6: Reinforcement Learning
Part 7: Natural Language Processing
Part 8: Deep Learning
Part 9: Dimensionality Reduction
Part 10: Model Selection & Boosting
200
https://www.udemy.com/machinelearning/
Kirill Eremenko teaches courses in two distinct Business areas on Udemy: Data Science and Forex Trading. He is a Data Science management consultant with over five years of experience in finance, retail, transport and other industries, trained at Deloitte Australia. He now leverages Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.
Hadelin de Ponteves is a consultant in the field of Machine Learning, Deep Learning and Artificial Intelligence. He holds an engineering master’s degree with a specialisation in Data Science, worked for Google and eventually became an entrepreneur.
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Great instructors that really know their stuff. They explain the concepts clearly and give you the exact blueprint to succeed today.