[Last updated 6/2024] Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT (Udemy – Vietsub and Engsub)
About Course
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What you’ll learn:
Build 7 different AIs for 7 different applications
Understand the theory behind Artificial Intelligence
Master the State of the Art AI models
Solve Real World Problems with AI
Q-Learning
Deep Q-Learning
Deep Convolutional Q-Learning
A3C (Asynchronous Advantage Actor-Critic)
PPO (Proximal Policy Optimization)
SAC (Soft Actor-Critic)
LLMs
Transformers
Low-Rank Adaptation (LoRA) and Quantization (QLoRA)
NLP techniques for Chatbots: Tokenization and Padding
Fine-Tuning an LLM with Knowledge Augmentation
As Extras: DDPG, Full World Model, Evolution Strategies & Genetic Algorithms
Link gốc:
https://www.udemy.com/course/artificial-intelligence-az/
Time Course:
15.5 hours (130 Lectures + Documents)
Instructor
: Hadelin de Ponteves
Total Weight:
5.87 GB
** Note
:
Chú ý:
Course Content
01 – Welcome to the course!
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05:10
03 – Q-Learning Intuition
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04:03
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002 What is reinforcement learning.mp4
11:26 -
003 The Bellman Equation.mp4
18:24 -
004 The Plan.mp4
02:12 -
005 Markov Decision Process.mp4
16:26 -
006 Policy vs Plan.mp4
12:55 -
007 Adding a Living Penalty.mp4
09:47 -
008 Q-Learning Intuition.mp4
14:45 -
009 Temporal Difference.mp4
19:26
06 – Deep Q-Learning Intuition
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001 Plan of Attack.mp4
02:17 -
002 Deep Q-Learning Intuition – Learning.mp4
15:15 -
003 Deep Q-Learning Intuition – Acting.mp4
06:06 -
004 Experience Replay.mp4
15:45 -
005 Action Selection Policies.mp4
16:22
07 – Deep Q-Learning Implementation
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012 Deep Q-Learning Implementation – Step 11.mp4
07:35 -
021 Deep Q-Learning Implementation – Step 20.mp4
05:44 -
020 video.mp4
00:11 -
020 Deep Q-Learning Implementation – Step 19.mp4
05:18 -
019 Deep Q-Learning Implementation – Step 18.mp4
20:26 -
018 Deep Q-Learning Implementation – Step 17.mp4
09:38 -
017 Deep Q-Learning Implementation – Step 16.mp4
05:37 -
016 Deep Q-Learning Implementation – Step 15.mp4
02:09 -
015 Deep Q-Learning Implementation – Step 14.mp4
06:47 -
014 Deep Q-Learning Implementation – Step 13.mp4
08:54 -
013 Deep Q-Learning Implementation – Step 12.mp4
08:58 -
002 Deep Q-Learning Implementation – Step 1.mp4
06:59 -
011 Deep Q-Learning Implementation – Step 10.mp4
07:39 -
010 Deep Q-Learning Implementation – Step 9.mp4
08:16 -
009 Deep Q-Learning Implementation – Step 8.mp4
03:07 -
008 Deep Q-Learning Implementation – Step 7.mp4
02:43 -
007 Deep Q-Learning Implementation – Step 6.mp4
03:54 -
006 Deep Q-Learning Implementation – Step 5.mp4
05:45 -
005 Deep Q-Learning Implementation – Step 4.mp4
03:57 -
004 Deep Q-Learning Implementation – Step 3.mp4
08:23 -
003 Deep Q-Learning Implementation – Step 2.mp4
06:24
09 – Deep Convolutional Q-Learning Intuition
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001 Plan of Attack.mp4
03:26 -
002 Deep Convolutional Q-Learning Intuition.mp4
07:12 -
003 Eligibility Trace.mp4
08:38
10 – Deep Convolutional Q-Learning Implementation
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002 Deep Convolutional Q-Learning Implementation – Step 1.mp4
05:16 -
003 Deep Convolutional Q-Learning Implementation – Step 2.mp4
05:30 -
004 Deep Convolutional Q-Learning Implementation – Step 3.mp4
11:05 -
005 Deep Convolutional Q-Learning Implementation – Step 4.mp4
04:33 -
006 Deep Convolutional Q-Learning Implementation – Step 5.mp4
07:14 -
007 Deep Convolutional Q-Learning Implementation – Step 6.mp4
04:05 -
008 Deep Convolutional Q-Learning Implementation – Step 7.mp4
02:03 -
009 Deep Convolutional Q-Learning Implementation – Step 8.mp4
08:20 -
010 Deep Convolutional Q-Learning Implementation – Step 9.mp4
09:47 -
011 Deep Convolutional Q-Learning Implementation – Step 10.mp4
07:37 -
012 Deep Convolutional Q-Learning Implementation – Step 11.mp4
14:13 -
013 Deep Convolutional Q-Learning Implementation – Step 12.mp4
03:54 -
013 video.mp4
00:27 -
014 Deep Convolutional Q-Learning Implementation – Step 13.mp4
05:23
12 – A3C Intuition
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001 Plan of Attack.mp4
03:39 -
002 The three A’s in A3C.mp4
04:44 -
003 Actor-Critic.mp4
06:36 -
004 Asynchronous.mp4
11:43 -
005 Advantage.mp4
15:20 -
006 LSTM Layer.mp4
15:36
13 – A3C Implementation
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002 A3C Implementation – Step 1.mp4
06:06 -
003 A3C Implementation – Step 2.mp4
05:52 -
004 A3C Implementation – Step 3.mp4
11:45 -
005 A3C Implementation – Step 4.mp4
08:25 -
006 A3C Implementation – Step 5.mp4
05:48 -
007 A3C Implementation – Step 6.mp4
07:13 -
008 A3C Implementation – Step 7.mp4
11:50 -
009 A3C Implementation – Step 8.mp4
18:28 -
010 A3C Implementation – Step 9.mp4
02:06 -
011 A3C Implementation – Step 10.mp4
09:58 -
012 A3C Implementation – Step 11.mp4
07:22 -
013 A3C Implementation – Step 12.mp4
09:58 -
014 A3C Implementation – Step 13.mp4
03:46 -
015 A3C Implementation – Step 14.mp4
20:21 -
015 video.mp4
00:39 -
016 A3C Implementation – Step 15.mp4
13:15
16 – LLMs Intuition
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001 Introduction to LLMs.mp4
01:40 -
002 Ingredients of an LLM.mp4
02:50 -
003 Who invented LLMs.mp4
01:23 -
004 How LLMs generate text.mp4
02:56 -
005 Inside an LLM – Under the Hood.mp4
04:43 -
006 LLM Parameters.mp4
02:04 -
007 LLM Context Window.mp4
02:07 -
008 Fine-Tuning LLMs.mp4
02:58
17 – LLMs Implementation
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002 Fine-Tuning LLMs with Hugging Face – Step 1.mp4
09:58 -
003 Fine-Tuning LLMs with Hugging Face – Step 2.mp4
12:12 -
004 Fine-Tuning LLMs with Hugging Face – Step 3.mp4
07:43 -
005 Fine-Tuning LLMs with Hugging Face – Step 4.mp4
05:11 -
006 Fine-Tuning LLMs with Hugging Face – Step 5.mp4
12:58 -
007 Fine-Tuning LLMs with Hugging Face – Step 6.mp4
06:42 -
008 Fine-Tuning LLMs with Hugging Face – Step 7.mp4
10:37
18 – THANK YOU
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001 THANK YOU Video.mp4
02:40
19 – Annex 1 Artificial Neural Networks
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001 What is Deep Learning.mp4
12:34 -
002 Plan of Attack.mp4
02:51 -
003 The Neuron.mp4
16:15 -
004 The Activation Function.mp4
08:29 -
005 How do Neural Networks work.mp4
12:47 -
006 How do Neural Networks learn.mp4
12:58 -
007 Gradient Descent.mp4
10:12 -
008 Stochastic Gradient Descent.mp4
08:44 -
009 Backpropagation.mp4
05:21
20 – Annex 2 Convolutional Neural Networks
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001 Plan of Attack.mp4
03:31 -
002 What are convolutional neural networks.mp4
15:49 -
003 Step 1 – Convolution Operation.mp4
16:38 -
004 Step 1(b) – ReLU Layer.mp4
06:41 -
005 Step 2 – Pooling.mp4
14:13 -
006 Step 3 – Flattening.mp4
01:52 -
007 Step 4 – Full Connection.mp4
19:24 -
008 Summary.mp4
04:19 -
009 Softmax & Cross-Entropy.mp4
18:19
21 – Extra Materials
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002 Extra Section – Q-Learning Part I.mp4
01:15 -
003 Extra Section – Q-Learning Part II.mp4
04:07 -
004 Extra Section – Q-Learning Part III.mp4
07:04 -
005 AI-Bonus-Section-4.mp4
04:40 -
005 Extra Section – Q-Learning Part IV.mp4
04:40 -
007 Extra Section – Q-Learning Section VI.mp4
08:04
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