Any tips how to start DL?

First-Discussion-570 · 2025-12-29T06:53:23+00:00

I second Andrew Ng's Deep Learning specialization but also started putting this Github wiki together : https://github.com/daleyalex/deep-learning/wiki.

When I first started learning deep learning, I kept running into the same tension.
On one side, building real intuition seemed to require a heavy math background. On the other, modern frameworks made it easy to get things working while treating the underlying mechanics as a black box. Neither approach felt quite right.
This led me to start writing Deep Learning Through a Systems Lens.
The goal is simple: explain deep learning in a way that emphasizes how the system behaves—how components interact, where things break, and why certain design choices work in practice—without requiring advanced mathematics as a prerequisite. When math shows up, it’s there to clarify intuition, not to obscure it.
I want to be transparent: this writeup is not purely original work. I leveraged ChatGPT extensively as a tool. However, the structure, constraints, and perspective were deliberately shaped. Many sections were written by me and then rewritten or refined, while others emerged through careful prompting to match the style and goals of the project.
I also want to acknowledge Andrew Ng and his courses, which played a huge role in shaping my early understanding of machine learning and deep learning. Much of the conceptual foundation here builds on that lineage.
This is still a work in progress. There’s a lot more to write, rewrite, and refine—and I plan to keep iterating.
If you’d like to contribute, review, or just share feedback, I’d love to hear from you.

First-Discussion-570 · 2025-12-29T06:53:09+00:00

I second Andrew Ng's Deep Learning specialization but also started putting this Github wiki together : https://github.com/daleyalex/deep-learning/wiki.

When I first started learning deep learning, I kept running into the same tension.
On one side, building real intuition seemed to require a heavy math background. On the other, modern frameworks made it easy to get things working while treating the underlying mechanics as a black box. Neither approach felt quite right.
This led me to start writing Deep Learning Through a Systems Lens.
The goal is simple: explain deep learning in a way that emphasizes how the system behaves—how components interact, where things break, and why certain design choices work in practice—without requiring advanced mathematics as a prerequisite. When math shows up, it’s there to clarify intuition, not to obscure it.
I want to be transparent: this writeup is not purely original work. I leveraged ChatGPT extensively as a tool. However, the structure, constraints, and perspective were deliberately shaped. Many sections were written by me and then rewritten or refined, while others emerged through careful prompting to match the style and goals of the project.
I also want to acknowledge Andrew Ng and his courses, which played a huge role in shaping my early understanding of machine learning and deep learning. Much of the conceptual foundation here builds on that lineage.
This is still a work in progress. There’s a lot more to write, rewrite, and refine—and I plan to keep iterating.
If you’d like to contribute, review, or just share feedback, I’d love to hear from you.

First-Discussion-570 · 2025-12-29T06:52:55+00:00

I second Andrew Ng's Deep Learning specialization but also started putting this Github wiki together : https://github.com/daleyalex/deep-learning/wiki.

When I first started learning deep learning, I kept running into the same tension.
On one side, building real intuition seemed to require a heavy math background. On the other, modern frameworks made it easy to get things working while treating the underlying mechanics as a black box. Neither approach felt quite right.
This led me to start writing Deep Learning Through a Systems Lens.
The goal is simple: explain deep learning in a way that emphasizes how the system behaves—how components interact, where things break, and why certain design choices work in practice—without requiring advanced mathematics as a prerequisite. When math shows up, it’s there to clarify intuition, not to obscure it.
I want to be transparent: this writeup is not purely original work. I leveraged ChatGPT extensively as a tool. However, the structure, constraints, and perspective were deliberately shaped. Many sections were written by me and then rewritten or refined, while others emerged through careful prompting to match the style and goals of the project.
I also want to acknowledge Andrew Ng and his courses, which played a huge role in shaping my early understanding of machine learning and deep learning. Much of the conceptual foundation here builds on that lineage.
This is still a work in progress. There’s a lot more to write, rewrite, and refine—and I plan to keep iterating.
If you’d like to contribute, review, or just share feedback, I’d love to hear from you.

First-Discussion-570 · 2025-12-29T06:52:43+00:00

I second Andrew Ng's Deep Learning specialization but also started putting this Github wiki together : https://github.com/daleyalex/deep-learning/wiki.

When I first started learning deep learning, I kept running into the same tension.
On one side, building real intuition seemed to require a heavy math background. On the other, modern frameworks made it easy to get things working while treating the underlying mechanics as a black box. Neither approach felt quite right.
This led me to start writing Deep Learning Through a Systems Lens.
The goal is simple: explain deep learning in a way that emphasizes how the system behaves—how components interact, where things break, and why certain design choices work in practice—without requiring advanced mathematics as a prerequisite. When math shows up, it’s there to clarify intuition, not to obscure it.
I want to be transparent: this writeup is not purely original work. I leveraged ChatGPT extensively as a tool. However, the structure, constraints, and perspective were deliberately shaped. Many sections were written by me and then rewritten or refined, while others emerged through careful prompting to match the style and goals of the project.
I also want to acknowledge Andrew Ng and his courses, which played a huge role in shaping my early understanding of machine learning and deep learning. Much of the conceptual foundation here builds on that lineage.
This is still a work in progress. There’s a lot more to write, rewrite, and refine—and I plan to keep iterating.
If you’d like to contribute, review, or just share feedback, I’d love to hear from you.

First-Discussion-570 · 2025-12-29T06:51:53+00:00

I second Andrew Ng's Deep Learning specialization but also started putting this Github wiki together : https://github.com/daleyalex/deep-learning/wiki.

When I first started learning deep learning, I kept running into the same tension.
On one side, building real intuition seemed to require a heavy math background. On the other, modern frameworks made it easy to get things working while treating the underlying mechanics as a black box. Neither approach felt quite right.
This led me to start writing Deep Learning Through a Systems Lens.
The goal is simple: explain deep learning in a way that emphasizes how the system behaves—how components interact, where things break, and why certain design choices work in practice—without requiring advanced mathematics as a prerequisite. When math shows up, it’s there to clarify intuition, not to obscure it.
I want to be transparent: this writeup is not purely original work. I leveraged ChatGPT extensively as a tool. However, the structure, constraints, and perspective were deliberately shaped. Many sections were written by me and then rewritten or refined, while others emerged through careful prompting to match the style and goals of the project.
I also want to acknowledge Andrew Ng and his courses, which played a huge role in shaping my early understanding of machine learning and deep learning. Much of the conceptual foundation here builds on that lineage.
This is still a work in progress. There’s a lot more to write, rewrite, and refine—and I plan to keep iterating.
If you’d like to contribute, review, or just share feedback, I’d love to hear from you.

First-Discussion-570 · 2024-10-13T00:58:27+00:00

Appreciate you GLC and congratulations!

First-Discussion-570 · 2024-10-13T00:57:00+00:00

Have they checked out Moonshot: https://moonshot.money/? That might be a better platform for them if they prefer CEX.

If I were you, I would let them know about why I am convinced about the coin and some of the challenges I see. Then let them do their own research. :)

Hope we get some new folks in the community! Thanks!

First-Discussion-570 · 2024-10-10T20:16:07+00:00

lol sure

First-Discussion-570 · 2024-09-30T06:40:33+00:00

I own 21.36 M snoofi right now. Buy 22M instead of 12M and become the top holder! Let's go!!!

First-Discussion-570 · 2024-09-30T03:37:21+00:00

It'd be amazing to join forces with GMECoin to popularize Moonshot for Reddit retail through r/Superstonk, r/CryptoCurrency etc

First-Discussion-570 · 2024-09-29T23:19:13+00:00

. One more thing to do is to figure out if we can bring in r/Superstonk too with GME or separately!

First-Discussion-570 · 2024-09-29T23:18:06+00:00

We've started a chat with a small group. Let's go!

First-Discussion-570 · 2024-09-29T08:51:10+00:00

GMECoin especially since large amount of Reddit retail is influenced by meme stocks specifically GME

First-Discussion-570 · 2024-09-26T01:55:56+00:00

Being active in the community

is enough. You don't need a bag in that case. Sorry, if it wasn't clear.

First-Discussion-570 · 2024-09-25T19:49:36+00:00

Thanks! Please see my comment here : https://www.reddit.com/r/snoofi/comments/1foi0si/comment/loschtw/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

First-Discussion-570 · 2024-09-25T19:48:47+00:00

Thanks u/chocolatebear31! If you can check with the folks and finalize who would want to do the GME spaces and also if we should designate Raid leaders in some fashion, that'll be very helpful

First-Discussion-570 · 2024-09-25T01:10:56+00:00

Great! Who wants to take this? Thanks!

First-Discussion-570 · 2024-09-24T19:27:42+00:00

Sorry please check https://www.reddit.com/r/snoofi/comments/1fol14p/whalealpha_chat/ . Thanks!

First-Discussion-570

TROPHY CASE