Level up your software engineering skills as a data scientist | ML Monthly February 2021

How do you go from a data scientist or machine learning researcher to building full-stack applications? In this episode of Machine Learning Monthly, I cover resources to answer that question such as Lj Miranda’s blog post on improving your software engineering skills as a researcher. Plus plenty more from the ML space during February 2021.

Read the post – https://zerotomastery.io/blog/machine-learning-monthly-february-2021/

My courses:
Learn Machine Learning (beginner) – https://dbourke.link/mlcourse
Learn TensorFlow and Deep Learning – https://dbourke.link/ZTMTFcourse

Connect elsewhere:
Web – https://www.mrdbourke.com/
Live coding on Twitch – https://www.twitch.tv/mrdbourke
Get email updates on my work – https://www.mrdbourke.com/newsletter

0:00 – Intro/dancing/hello
1:01 – Where to sign up for ML Monthly emails
1:30 – My new TensorFlow course
2:45 – See me code live on Twitch (https://www.twitch.tv/mrdbourke)
3:00 – My ML deployment tutorial for CS329s
4:11 – Using deep learning to read brainwaves
7:07 – Alvaro’s guide to TensorFlow Serving
9:05 – Chip Huyen’s MLOps Tooling Landscape v2 blog post
11:08 – ML is going real-time by Chip Huyen
14:04 – Using GitHub for MLOps
15:42 – Upgrade your software engineering skills as a machine learning practitioner
17:42 – freeCodeCamp’s upcoming DS + ML curriculum
19:22 – Transformers from scratch by Peter Bloem
21:44 – Estimating training data influence with TracIn
24:40 – Learn fundamental statistics with Python
26:25 – The most important statistical ideas of the past 50 years
28:56 – Outro/submit your work/more dancing

#machinelearning #datascience

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