I wrote this quick primer so you don't have to parse all the information out there and instead can learn the things you need to know to quickly get started.
Source: kDnugget
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Whether you're a novice data science enthusiast setting up TensorFlow for the first time, or a seasoned AI engineer working with terabytes of data, getting your libraries, packages, and frameworks installed is always a struggle.
Source: HOB12966
I would never use as a data scientist, or too shallow: not giving me enough information to help me understand how to be effective with Docker quickly.
Source: HOB21522
MRE provides real insight for effective decisions to help business with the help of current industry trends and accurate data available in the market.
Source: MRE3744
Job postings for cloud computing and cloud engineers have risen 27% in the past two years, according to Indeed. AWS, Python, and Java are the most in-demand skills for cloud computing roles
Source: HOB15471
We will now talk about what are some steps that you can do if you want to deploy your recently trained model as an API. The discussion on how to do this with Fast.ai is currently ongoing (more) and will most likely continue until PyTorch releases their official 1.0 version. You can find more information in the Fast.ai Forums, PyTorch Documentation/Forums, and their respective GitHub repositories.
Source: HOB17712
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