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Leo Isikdogan @UC-YAxUbpa1hvRyfJBKFNcJA@youtube.com

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I make concise educational videos on artificial intelligence


09:01
Things We Do That AI Can't Master Yet
09:17
How Diffusion Models Work
05:38
I asked artificial intelligence to rate my pictures
16:06
Artificial Intelligence Art: Questions Answered
08:57
Image Filters Explained
02:32
Neural Networks for Babies
05:40
Multi-Task Learning | Explained in 5 Minutes
08:46
Turning Photos into Paintings using Neural Networks
08:28
Can AI Create Original Art?
01:18
SemifreddoNets: Partially Frozen Neural Networks for Efficient Computer Vision Systems (ECCV 2020)
05:58
Reward Hacking in AI
04:43
Perceptual Fusion
08:38
How to Predict Stock Market Crashes using Mathematical Models
07:45
Optical Illusions Explained
16:02
How to Train Neural Networks Fast and Efficiently | Tutorial
09:45
How to Design a Neural Network | 2020 Edition
09:29
How Super Resolution Works
13:33
Hanauma Bay Snorkeling Experience | Oahu, Hawaii
10:06
Network Architecture Search: AutoML and others
04:06
VisionISP: an Image Processing Pipeline for Computer Vision Applications
03:23
Eye Contact Correction using Deep Neural Networks
08:10
Can deep learning predict the stock market?
05:11
Computer Science Electives
04:21
Computer Science Curriculum
05:21
How much math do you need for Computer Science?
05:34
What is new in TensorFlow 2.0 | Tutorial
05:30
7 Tips to Speak English Like a Native Speaker
04:30
TensorFlow Coding Session #7 Transfer Learning
04:57
TensorFlow Coding Session #6 TFRecords and Freezing Models
09:52
TensorFlow Coding Session #5 Convolutional Neural Networks
11:47
TensorFlow Coding Session #4 Regularization, Checkpoints, and TensorBoard
06:58
TensorFlow Coding Session #3 Training and Validation Sets
13:25
TensorFlow Coding Session #2 Training a Model
07:19
TensorFlow Coding Session #1 Introduction
04:26
Computer Vision vs Image Processing
04:44
How Video Compression Works
06:52
How Image Compression Works
07:51
How Digital Cameras Process Images
01:31
Chicago Timelapse | Merchandise Mart, Navy Pier, Museum Campus
02:01
Deep Learning Crash Course: Introduction
06:57
Practical Methodology in Deep Learning
06:04
Generative Adversarial Networks
10:10
Deep Unsupervised Learning
07:46
Recurrent Neural Networks
10:16
Optimization Tricks: momentum, batch-norm, and more
06:47
Transfer Learning
11:47
How to Design a Convolutional Neural Network
14:31
Convolutional Neural Networks Explained
09:55
Data Collection and Preprocessing
08:09
Regularization and Data Augmentation
09:07
Overfitting, Underfitting, and Model Capacity
10:04
Artificial Neural Networks: Going Deeper
10:07
Artificial Neural Networks Demystified
00:31
Austin, TX Hyperlapse
01:06
Chicago Timelapse
01:04
Austin, TX Timelapse