Introduction

This is my intro to the deep learning section of the blog. Here I plan on explaining concepts in machine learning and related topics. Everything I share is already public knowledge, but my hope is that my way of interpreting these concepts could offer a different (possibly helpful) perspective.

Before I dive in, I want to note my reasoning for my interest. Though a reason is not always necessary, my perspective is that deep learning/machine learning has the capability to transform the landscape of modern tech, just as mobile computing has done a decade before (and the internet two decades before). Though deep learning concepts & research has been around since the mid-1950s (https://www.dartmouth.edu/~ai50/images/program.pdf), it seems that we finally have the infrastructure needed to make these self-learning algorithms useful. Now that websites and mobile apps have become socially standardized, absurd amounts of data is being generated each second. This is more information than what a traditional algorithm is capable of processing.

Deep learning algorithms will allow us to see relations in generated data on high level dimensions by conforming the algorithm to the data. Thus, the more data we feed the beast, the better our algorithms become. Now is the intersection between an oversupply of data and a scarcity of ML/DL algorithms tailored to this data. We are at the cusp of a new era of algorithms that have the power to transform every industry (again!). If I haven’t sold you yet, don’t take my word for it…

Overall overview of AI:

Click to access ai_index_2019_report.pdf

Jobs soon to be replaced by AI:

Click to access 2019.11.20_BrookingsMetro_What-jobs-are-affected-by-AI_Report_Muro-Whiton-Maxim.pdf