Machine Learning For Beginners
Machine Learning For Beginners

Abstract: 

Hadelin is one of the creators of the Machine Learning A-Z course which has over 26,000 students: www.udemy.com/machinelearning - in this session we will break down the complexities of Machine Learning for beginners. We will describe the intuition behind three select algorithms (Naive Bayes, Support Vector Machine and Thompson Sampling - although these may change), showcase some coding libraries both in R and Python and then demonstrate the practical real-world applications of each algorithm. The goal is for listeners to walk away with an intuitive understanding of three ML algorithms, a good overview of how they could use them in their work and an inspired passion for exploring Machine Learning further.

Bio: 

Hadelin is passionate about data science, artificial intelligence and deep learning. Hadelin teaches on Udemy and other platforms with tens of thousands of students Worldwide. Hadelin holds an engineering masters degree with a specialization in data science. He spent one year doing research in machine learning, working on innovative and exciting projects. He has also worked at Google where he implemented machine learning models for business analytics. After realizing that he spent most of my time doing analysis with insufficient room for his creativity Hadelin became an entrepreneur. Hadelin’s courses combine the two dimensions of analysis and creativity, allowing his students to learn all the analytic skills required in data science, by applying it on creative ideas.

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