Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers

Рет қаралды 228,100

Күн бұрын

Andrew Ng, Adjunct Professor & Kian Katanforoosh, Lecturer - Stanford University
onlinehub.stanford.edu/
Andrew Ng
Adjunct Professor, Computer Science
Kian Katanforoosh
Lecturer, Computer Science
To follow along with the course schedule and syllabus, visit:
cs230.stanford.edu/
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0:00 Introduction
2:25 Reading Research Papers
3:13 Building a Speech Recognition System
6:25 Reading One Paper
6:56 My Real Life
13:15 Practice Questions
15:52 Reading Practice
21:23 Where do you go
23:50 Two Lost Tips
26:26 Code
29:41 Career Advice
32:27 Job Scenario
34:51 Machine Learning Engineers
37:31 Failure Modes
29:46 Small Projects
40:59 Horizontal Pieces
42:36 Saturday Morning Problem
46:06 WorkLife Integration
49:26 Team Influence

Пікірлер: 27

@nirajpudasaini4450 2 ай бұрын

Such a golden lecture. Thanks Andrew - the best teacher in AI.

@simonkang7387 2 жыл бұрын

Great lecture. I have got some inspirations. Thank you!

@omar.sultan Жыл бұрын

This was inspiring. Thank you

@mohamadzakaria6637 5 ай бұрын

Very inspiring! Lot of stuffs I have missed here :)

@abrahamowos 2 жыл бұрын

"Those things do not as directly contribute to this" 😂😂

@tushihahahi Жыл бұрын

Career advice starts at 29:00

@akarshrastogi3682 Жыл бұрын

TREASURE ADVICE. This has been sitiing on youtube since 2019, I only now viewed it. I regret not knowing this earlier.

@EmiTheLoomistar 2 жыл бұрын

Andreeew!!

@muhammadumarsotvoldiev8768 Жыл бұрын

Great!

@Minimalrevolt-m83 Жыл бұрын

Wish I could migrate to U.S from Malaysia and study at Stanford. Need to surround more with intellectual societies who values the truth of knowledge, not mythological of ignorance.

@aricircle8040 4 ай бұрын

Great lecture! Are there also lectures about how to perform research/write a paper?:)

@lone0017 5 ай бұрын

I wish I saw this 4 years ago

@Will29295 5 ай бұрын

If we are kind of new. How to we go about compiling a reasonable list of papers especially papers that cover some of the more basic topics?

@robensonlarokulu4963 Жыл бұрын

Very true. Attended Virginia Tech PhD program and had all the issues mentioned after 55.00. The program was terrible and a really bad fit for me in terms of research and had to drop out. I wish I had seen this advice before.

@mprone 2 ай бұрын

Can you elaborate a little more? What is Virginia Tech PhD program exactly?

@user-wz6xy4gn7j Жыл бұрын

34:00

@klindatv 13 күн бұрын

Well, he didn't explain if you have to be wide or deep on topics. Probably he advises to do a trade-off.

@SuryaDevta108 11 ай бұрын

Sandeep sir video dekh ke koi aaya hai

@pavel.pavlov 7 ай бұрын

This is wrong. First you check if there is a ready model or API for this problem

@fgfanta Жыл бұрын

3 years later, with the demand for MLOps and ML in the cloud, and models democratization, this hasn't aged well, not outside of academia at least.

@TheFinalVenue Жыл бұрын

Interesting. What would your advice be?

@fgfanta Жыл бұрын

@@TheFinalVenue Here, straight from the horse's mouth kzfaq.info/get/bejne/ZpxddL2J0t2smqM.html

@ngocminhdoan9655 Жыл бұрын

I'm new to this, could you elaborate a little bit on what you meant?

@itaymargolin1436 Жыл бұрын

@@ngocminhdoan9655 My guess that he meant that in industry, knowing how to utilize and deploy models has become more important than understanding the math behind them. In my opinion, this is partially correct. You can create a wonderful zero shot recommendation systems, chatbots and descent cv-based solutions without a single training loop.

@ngocminhdoan9655 Жыл бұрын

@@itaymargolin1436 Thank you so much for your explanation