加入“人工智能A-Z 2023”课程，掌握数据科学、机器学习和深度学习的综合力量，为实际应用创建尖端的AI解决方案！
电商之家 
使用Python编写自我提升的AI，即使没有编程经验也可以轻松上手。
通过直觉训练深入了解关键的AI概念。
将你的AI技能应用到实际场景中。
获取每个AI构建过程中的可下载Python代码模板。需要基本的Python知识。
无论你是初学者还是经验丰富的专业人士，这门课程将赋予你在不断发展的技术领域中有效应用AI并产生重大影响的能力。Join the “Artificial Intelligence A-Z 2023” course and harness the combined power of Data Science, Machine Learning, and Deep Learning to create cutting-edge AI solutions for real-world applications.
Start coding self-improving AI using Python, even with no prior coding experience.
Gain a deep understanding of key AI concepts through intuition training.
Apply your AI skills to real-world scenarios.
Access downloadable Python code templates for every AI built in the course.Requires Basic Python knowledge
Whether you’re a beginner or an experienced professional, this course empowers you to effectively apply AI and make a significant impact in the ever-evolving field of technology.
- 教程编号：2084721761
- 教程语言：英语 / 无字幕
- 安全扫描：无病毒无插件 / 云查杀 Virustotal Virscan
- 培训机构：未知
- 文件大小：2.02GB
- 文件格式：视频 / 文档 / 图文
- 压缩软件：7ZIP
- 视频播放：完美解码
教程目录
Artificial Intelligence A-Z 2023
├─01 Welcome to the course
│ 001 Why AI.mkv
│ 002 Course Structure.html
│ 003 BONUS Learning Paths.html
│ 004 Installing Anaconda.mkv
│ 005 BONUS Meet Your Instructors.html
│ 006 Updates on Udemy Reviews.mkv
│ 007 Artificial-Intelligence-A-Z-Learn-How-To-Build-An-AI-2.pdf
│ 007 This PDF resource will help you a lot.html
│ 008 FAQBot.html
├─02 ---------- Part 0 - Fundamentals Of Reinforcement Learning ----------
│ 009 Welcome to Part 0 - Fundamentals of Reinforcement Learning.html
├─03 Q-Learning Intuition
│ 010 Plan of Attack.mkv
│ 011 What is reinforcement learning.mkv
│ 012 The Bellman Equation.mp4
│ 013 The Plan.mp4
│ 014 Markov Decision Process.mp4
│ 015 Policy vs Plan.mp4
│ 016 Adding a Living Penalty.mp4
│ 017 Q-Learning Intuition.mp4
│ 018 Temporal Difference.mp4
├─04 Q-Learning Visualization
│ 019 Q-Learning Visualization.mp4
├─05 ---------- Part 1 - Deep Q-Learning ----------
│ 020 Welcome to Part 1 - Deep Q-Learning.html
├─06 Deep Q-Learning Intuition
│ 021 Plan of Attack.mp4
│ 022 Deep Q-Learning Intuition - Learning.mp4
│ 023 Deep Q-Learning Intuition - Acting.mp4
│ 024 Experience Replay.mp4
│ 025 Action Selection Policies.mp4
├─07 Deep Q-Learning Implementation
│ 026 Plan of Attack.html
│ 027 Where to get the Materials.html
│ 028 Getting Started.mp4
│ 029 Self Driving Car - Step 1.mp4
│ 030 Self Driving Car - Step 2.mkv
│ 031 Self Driving Car - Step 3.mkv
│ 032 Self Driving Car - Step 4.mkv
│ 033 Self Driving Car - Step 5.mkv
│ 034 Self Driving Car - Step 6.mp4
│ 035 Self Driving Car - Step 7.mp4
│ 036 Self Driving Car - Step 8.mp4
│ 037 Self Driving Car - Step 9.mp4
│ 038 Self Driving Car - Step 10.mp4
│ 039 Self Driving Car - Step 11.mp4
│ 040 Self Driving Car - Step 12.mp4
│ 041 Self Driving Car - Step 13.mp4
│ 042 Self Driving Car - Step 14.mp4
│ 043 Self Driving Car - Step 15.mp4
│ 044 Self Driving Car - Step 16.mp4
├─08 Deep Q-Learning Visualization
│ 045 Self Driving Car - Level 1.mp4
│ 046 Self Driving Car - Level 2.mp4
│ 047 Self Driving Car - Level 3.mp4
│ 048 Self Driving Car - Level 4.mp4
│ 049 Challenge Solutions.html
├─09 ---------- Part 2 - Deep Convolutional Q-Learning ----------
│ 050 Welcome to Part 2 - Deep Convolutional Q-Learning.html
├─10 Deep Convolutional Q-Learning Intuition
│ 051 Plan of Attack.mp4
│ 052 Deep Convolutional Q-Learning Intuition.mp4
│ 053 Eligibility Trace.mp4
├─11 Deep Convolutional Q-Learning Implementation
│ 054 Plan of Attack.html
│ 055 Where to get the Materials.html
│ 056 Doom - Step 1.mp4
│ 057 Doom - Step 2.mp4
│ 058 Doom - Step 3.mp4
│ 059 Doom - Step 4.mp4
│ 060 Doom - Step 5.mp4
│ 061 Doom - Step 6.mp4
│ 062 Doom - Step 7.mp4
│ 063 Doom - Step 8.mp4
│ 064 Doom - Step 9.mp4
│ 065 Doom - Step 10.mp4
│ 066 Doom - Step 11.mp4
│ 067 Doom - Step 12.mp4
│ 068 Doom - Step 13.mp4
│ 069 Doom - Step 14.mp4
│ 070 Doom - Step 15.mp4
│ 071 Doom - Step 16.mp4
│ 072 Doom - Step 17.mp4
├─12 Deep Convolutional Q-Learning Visualization
│ 073 Watching our AI play Doom.mp4
├─13 ---------- Part 3 - A3C ----------
│ 074 Welcome to Part 3 - A3C.html
├─14 A3C Intuition
│ 075 Plan of Attack.mp4
│ 076 The three As in A3C.mp4
│ 077 Actor-Critic.mp4
│ 078 Asynchronous.mp4
│ 079 Advantage.mp4
│ 080 LSTM Layer.mp4
├─15 A3C Implementation
│ 081 Plan of Attack.html
│ 082 Where to get the Materials.html
│ 083 Breakout - Step 1.mp4
│ 084 Breakout - Step 2.mp4
│ 085 Breakout - Step 3.mp4
│ 086 Breakout - Step 4.mp4
│ 087 Breakout - Step 5.mp4
│ 088 Breakout - Step 6.mp4
│ 089 Breakout - Step 7.mp4
│ 090 Breakout - Step 8.mp4
│ 091 Breakout - Step 9.mp4
│ 092 Breakout - Step 10.mp4
│ 093 Breakout - Step 11.mp4
│ 094 Breakout - Step 12.mp4
│ 095 Breakout - Step 13.mp4
│ 096 Breakout - Step 14.mp4
├─16 A3C Visualization
│ 097 Watching our AI play Breakout.mp4
│ 098 THANK YOU bonus video.mp4
├─17 Annex 1 Artificial Neural Networks
│ 099 What is Deep Learning.mp4
│ 100 Plan of Attack.mp4
│ 101 The Neuron.mp4
│ 102 The Activation Function.mp4
│ 103 How do Neural Networks work.mp4
│ 104 How do Neural Networks learn.mp4
│ 105 Gradient Descent.mp4
│ 106 Stochastic Gradient Descent.mp4
│ 107 Backpropagation.mp4
├─18 Annex 2 Convolutional Neural Networks
│ 108 Plan of Attack.mp4
│ 109 What are convolutional neural networks.mp4
│ 110 Step 1 - Convolution Operation.mkv
│ 111 Step 1(b) - ReLU Layer.mkv
│ 112 Step 2 - Pooling.mkv
│ 113 Step 3 - Flattening.mkv
│ 114 Step 4 - Full Connection.mkv
│ 115 Summary.mkv
│ 116 Softmax Cross-Entropy.mkv
└─19 Bonus Lectures
117 YOUR SPECIAL BONUS.html
