Machine Learning 101
This was the presentation for the Microsoft Community Technology Update of 2016. The idea was to introduce to people the concept of Machine Learning and its easy to get started if you are keen. My objective was also to communicate how some of the algorithms work and they require no more than basic understanding of Math to get going, sometimes not even that. The algorithms we covered were, Support Vector Machines (SVM), Decision Tree using R2D3 and Neural Networks for classification. We used the Tensorflow Playground to help understand the Neural Network and Deep Learning concepts. I gave an analogy of how Machine Learning process is like making a smoothie where your algorithm is a recipe, your data are your ingredients, your computer is your blender and your smoothie is the model that you developed. I used the same example to convey the concept of Training Validation and Testing. Coverage of Type 1 and Type 2 errors together with the metrics of Recall and Precision was covered as well. Finally I closed the session with what are some good resources to get started with Machine Learning for all skill levels. There are references to websites, courses, kaggle competition, podcasts, cheat sheets and books.
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Machine Learning 101
- 5. Data wrangling (munging), retrieval + storage Data mining & machine learning Statistics Big data Data science
- 8. Chart from "2016 Data Science Salary Survey"
- 10. Source: Data Science For Beginners - 5 Questions Data Science Answers by Brandon Rohrer
- 11. Is this A or B?
- 12. Is this Weid?
- 15. What should I do now?
- 18. 1. Define 2. Train 3. Validate scoring evaluating Explore Deploy …visualise and study …deploy as a (web) service 5. Update and revalidate
- 20. Classification
- 21. 21
- 27. 27
- 28. 28
- 29. ® 99.9%-ile
- 30. 30
- 32. 34
- 33. 35 FALSE NEGATIVE TRUE POSITIVE FALSE POSITIVE Relevant Elements PRECISION RECALLSELECTED ELEMENTS
- 34. 4 Step process to mastery
- 41. Thank you!
Notas del editor
- I want to start by grounding this discussion in Microsoft’s mission because everything we’re going to talk about today begins and ends with our mutual goal of empowering our customers and our communities. To that end we have three bold ambitions, and they form the foundation of the evolution of the MVP Award. Building the intelligent cloud. We want to have the richness of the cloud infrastructure that accommodates for the complexities and the diversity of the way the world works today. Our goal is to build the most comprehensive cloud infrastructure and support hybrid computing in its purest form so that it provides flexibility. And then build out a rich data platform on top of it for building new systems of intelligence that drive business transformation. Create more personal computing. This is where we focus on creating a more natural interface and building experiences that are about the mobility of the experience, not the mobility of the device. Increasingly the issue of our time is going to be privacy and being in control of what data you share, how that data is being used. Windows 10 marks a huge milestone on this journey of more personal computing where it will span with one consistent experience for users, developers, and IT administrators from across Internet of Things to these holographic computers. Reinvent productivity and business process. The intersection between productivity and communication and collaboration and business process. This is where Office 365 and Dynamics in particular come together to enable that new way of working, the new workflows of the enterprise.