Machine Learning Interview with Alex - R, Python, ML, Real Answers

1:15 Welcome Alex
1:35 What Type of Work
3:10 Complexities of Access to Data
4:55 Data Clean Up
6:00 Explain to Manager
7:40 Data Analytics, Machine Learning, AI
10:50 I Love Turkey
12:55 Black Box (Neural Network) Algorithym
15:15 OCDevel and ML - Gradient Descent, Local Minima
19:05 Complexity of Evaluation Model
20:12 Natural Language Processing (NLP) and Google
22:23 NLP vs Vocal Audio
23:32 Opposite of King, is Queen. How?
25:35 Training Models is Actually Bad for the Environment
26:15 Theory/Computations & Linear Algebra
27:45 Math, Practicality, STEM
29:32 Citizen Data Science/ Democratized DS, Are there Jobs?
31:00 Demand in Industry Jobs
32:15 Foot in the Door as ETL, apprentice/intern
34:07 Why Linear Algebra, Options (bubble sort, quick sort, etc.)
37:10 Open Source - Don’t Miss this Tip!!!
38:35 Dream Job and 30 Hour Work-Week
40:52 Final Thoughts

I have conducted an interview with a Machine Learning engineer:

How do you get into Machine learning?
What kind of background in coding do you need?
How about math, should I know linear algebra?
Do I need a STEM degree? Are boot camps any good?

Find out all of those things from this ML Engineer.

The audio did get messed up and I cleaned it up as best as I could. Hopefully, it's not too distracting.

Also, I would LOVE to interview more people from my R Channel. Please contact me if you are interested.

I try to create videos based on common interests, so your feedback is wanted. Thank you.

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