Deep Learning Course for Beginners

This deep learning course is designed to take you from beginner to proficient in deep learning. You will learn the fundamental concepts, architectures, and applications of deep learning in a clear and practical way. So get ready to build, train, and deploy models that can tackle real-world problems across various industries.

Course created by @AyushSinghSh

⭐️ Contents ⭐️
0:00:00 Intro
0:03:07 Getting started
0:05:07 Vectors
0:21:51 Operation on vectors
0:38:52 Matrices
0:52:02 Operation on Matrices
0:52:27 Matrix Scalar Multiplication
0:55:47 Addition of Matrices
0:59:27 Properties of Matrix addition
1:03:07 Matrix Multiplication
1:08:02 Properties of Matrix Multiplication
1:18:32 Linear Combination Concept
1:36:20 Span
1:50:57 Linear Transformation
2:05:30 Transpose
2:14:02 Properties of Transpose
2:19:52 Dot Product
2:25:22 Geometric Meaning of Dot Product
2:34:32 Types of Matrices
3:04:22 Determinant
3:11:17 Geometric Meaning of Determinant
3:15:42 Calculating Determinant
3:23:37 Properties of Determinant
3:27:22 Rule of Sarus
3:48:42 Minor
3:56:49 Cofactor of a Matrix
4:00:42 Steps to calculate Cofactor of a Matrix
4:03:17 Adjoint of a Matrix
4:18:47 Trace of a Matrix
4:17:22 Properties of Trace
4:38:17 System of Equations
5:03:07 Example
5:17:42 Determinant
5:57:47 Single Variable Calculus
6:02:48 What is Calculus?
6:11:07 Ideas in Calculus
6:11:33 Differentiation
6:18:38 Integration
6:22:07 Precalculus Functions
6:43:52 Single Variable Calculus (Trigonometry Review)
6:45:02 Trigonometry functions
7:12:02 Unit Circle
7:24:32 Limit Concept
7:51:47 Definition of a limit
7:53:27 Continuity
8:00:17 Evaluating Limits
8:17:12 Sandwich Theorem
8:21:12 Differentiation
8:45:42 Differentiation as rate of Change
8:52:37 Differentiation in terms of Limit
9:04:51 Example
9:09:54 Important Differentiation Rules
9:53:12 Rule Chain Rule
10:17:27 What is Deep Learning
10:18:27 What is Machine Learning
10:36:37 Definition of Deep Learning
10:43:07 Applications
10:47:19 Introduction to Neural Networks
10:51:17 Artificial Neural Networks
11:08:31 The Perceptron
11:19:57 Linear Neural Network
11:21:32 Intuition Behind Activation function and Backpropagation Algorithm

🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama

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[AyushSinghSh]

Hope you guys enjoy the course, checkout Github for resources :) People "might" think it's too much maths/core, where people forget that maths is not prerequisite of ML & DL - it's literally the core, so spend most of your time in it :) you will be fine!

[probalkar]

Should've called it linear algebra and calculus for machine learning coz out 13 hrs 10 hrs straight its just that only. U can't cover deep learning in the remaining time. Still the curriculum looks good for linear algebra and calculus for machine learning and deep learning so I'll definitely follow it. If it also had statistics and probability it would've been awesome.

[SJ-yfxy]

I remember thiss dude made an ml course when he was like 13. Cant wait to complete this

[shafayetshourov]

Bro taught us entire 12th grade math in one video 💀

[nocopyrightgameplaystockvi]

This is a very good introduction to Maths behind Machine Learning. Anwyays Thanks.

[AshishRaj]

10 hours of maths + 1.5 hours of intro to Neural Networks
I guess the thumbnail is misleading

[uzairmughal]

Finally witnessing the 13 hours+ course that I know it all. Sometimes it feels good to be acknowledged :)

[yousamshashad]

An educational channel of this size should add dubbing to the list

[djo_shorts]

We love you FCC and you Ayush.. thank very much for all you guys do.. we love and appreciate it all ✨🤝🏾

[redrooster]

I have been note taking, and i would love to use practice questions to put it to use, is there any URL that have practice questions to these lectures? I would love to practice]

[elliotarledge]

I don't think the underlying linear algebra is the most appealing to the public. Math is super important if you care about Kernel engineering and PyTorch CUDA extensions but that's about it (neural net architectures too). A general deep learning lingo course is what people expect when they see "Deep Learning for beginners". Good job though, glad this is all in one place :)

[superfliping]

Want to be a judge?

1. CodeCraft Duel: Super Agent Showdown
2. Pixel Pioneers: Super Agent AI Clash
3. Digital Duel: LLM Super Agents Battle
4. Byte Battle Royale: Dueling LLM Agents
5. AI Code Clash: Super Agent Showdown
6. CodeCraft Combat: Super Agent Edition
7. Digital Duel: Super Agent AI Battle
8. Pixel Pioneers: LLM Super Agent Showdown
9. Byte Battle Royale: Super Agent AI Combat
10. AI Code Clash: Dueling Super Agents Edition

[yunkkim]

This course is called Matrix Algebra in undergraduate applied mathematics level

[hernandez]

10:16:40 To skip linear algebra and go to deep learning...

[mazharansari]

I am currently at 1:51:01 and so far course is great, if you're complete noob in maths and want to learn things this is a good course atleast where i am now it seems great only caviat is instructor has spend so much more time to explain things i mean if a topic x is covered in 10 minutes he has taken more time than that to explain it I learnt many topics in an instant but he spends over more time over all its a good course if you're completely don't know much maths

[DC-xtry]

Thx for sharing, just a quick comment regarding the background noice.

[sujalkapoor]

I can’t get your newera youtube channel pls send the link……

[RanjitKumar-jcow]

Vector have both magnitude and direction.

[ejm]

28:06 geometrically speaking wouldn't adding vectors like this(connection is tail to tail instead of head of one vector pointing to tail of other vector) using triangle method give the wrong direction?

Or can it be done as the direction isn't important in deep learning like in physics or something? 🤔

[arjuntt]

So are you saying if I'm good at math i can skip the first 10 hours,

Yaay happiest news i heard today, lol