Go gaga over Machine Learning

A Diagram Editor for JupyterLab - Jupyter Blog The new JupyterLab interface is much more than a replacement for the classic notebook. It aims to bring together all the pieces required for a complete scientific workflow. The extension-based architecture of JupyterLab comes with a number of components already enabled: a Jupyter notebook, a text editor, a file browser in the sidebar, a number of editors and viewers for various file formats, and much more.

I often wonder when I see people completing certificates on ML, are these more for showing the world that you know and understand ML or is it really a sense of achieving something! If it is the latter then why pay ? and why need a certificate at all? Let me elaborate on the resources that are free and can do a better job than most paid ML courses: Googles free website to choose videos, docs,tutorials, courses , sample code and Interactive demos -  https://ai.google/education/#?modal_active=none Have you read this? Triskelion one of the leaders on Kaggle explains how he went from a  beginner and finished up as a master with a top 10 finish -  https://mlwave.com/reflecting-back-on-one-year-of-kaggle-contests/  or  https://machinelearningmastery.com/master-kaggle-by-competing-consistently/ Kaggles Learning modules that are amazing  Machine Learning -  https://www.kaggle.com/learn/machine-learning R -  https://www.kaggle.com/learn/r Data Visualization -  https://www.kagg