Python Data Visualization Analysis Practical Project

Hello , Nomad  Creator  Student  everyone !

Yours  In class  Help  I want to give it to you  always  Trying  Nomad  I am a creator .

A while ago [OpenCV] Python  Deep Learning  Image processing  Project 2 - Bad Apples  Find it !' process  Released and  promise  I gave it to you, right ?

first  Just a sigh  Resting  Student  People  Interested in  Contents  As a special lecture  Make it  I will update it .

So  Wow  count  egg plant  Special lecture  Update  I prepared it .

First , all  The students  You will hear  number  There is a '[ luxury lecture  I found ]Tensorflow in Colab' . This time .  The lecture  While Custom YOLO is  more  more  On my PC  Make  number  There wasn't any . And  many  People  Deep learning requires a GPU  good  equipment  Should I buy it?  You asked . So  Get GPU or TPU for free  To use  number  present  Google Colab ​  Using  Contents  Introducing  This is a lecture . Tensorflow YouTube  Channel's  Luxury  English class  I am  Explaining  Additional explanation  This is the content . Lecture  The data  I was downloading  my  Knowledge Portal  From Creapple (www.creapple.com)  every  Minute  For free  To take the class  number  There is  once  Listen, thanks to Colab.  jeon  Now inside the GPU  I'm buying ~~.

 

two  The second is 'Model accuracy is over 99%'  This is a special lecture called 'Raising the bar'. This lecture is ' [ Raspberry Pi ] IoT Deep Learning Computer Vision Practice  The project started with a question from students in the course: "Why can't the MNIST handwriting model say '7' is '7'?" Of course, there are various factors such as the accuracy of the model, program exception handling, and the raw MNIST data, but since the existing Nueral Network model is simple for learning, I created the content to reconfigure the Nueral Network model to increase its accuracy to 99.38%.

'Model accuracy is over 99%  The special lecture titled 'Raising' is updated for free in the related lectures below among my lectures. Learn fun and useful content. Those who have taken all the lectures, it's not over yet!

• [ Raspberry Pi ] IoT Deep Learning Computer Vision Practice  Project
• [ Mobile ] Deep Learning Computer Vision Practice  Project
• [ Tensorflow 2] Python  Deep Learning  Complete Conquest - Latest GAN, BERT, RNN, CNN Techniques
• [ Tensorflow 2] Python  Machine Learning  Complete Conquest - Marathon  Record Prediction  Project
• Keras , artificial intelligence  Common language  Complete conquest

 

The third one is ' [OpenCV] Python', which is loved by many people these days.  Deep Learning  Image processing  Project - Son Heung-min  Find it !' and '[OpenCV] Python  Deep Learning  Image processing  Project 2 - Bad Apples  Find it !' lecture  For  This is the content . This  The series  Make it  every  Part 1 and Part 2  together  Not taking the class  Won't  capital  There will be  Thinking about  I did . So  one  Widespread  You see  People  sibling  The lecture  body  Don't have to  Really  container  big  Make a decision  I did . Each one  One by one  Unit ( Section ) ​  As a special lecture  To each other  Periodically  i did it .

• Brother '[OpenCV] Python  Deep Learning  Image processing  Project - Son Heung-min  The lecture ' Find it !'  Face recognition ​  Strengthening  The 'Face Landmark and Alignment' section of the content  I got it .
• Brother '[OpenCV] Python  Deep Learning  Image processing  Project 2 - Bad Apples  The lecture ' Find it !'  YOLO images and videos for my brother  treatment  etc.  The basics  Learning 'YOLO '  Used  objects  The 'Identification (Object Detection)' section  I received a gift .

so  two  The lecture  Are you listening  The person is  As a bonus  one  Unit  more  You will hear  number  There is . Already  You have taken the course  You too  lecture  When you come in  Special lecture  Included  there is .

In the future too  more  good  Contents  Make it  Sharing  Nomad  The creator  It will be okay .

thank you .