Machine learning is how to classify categoires practically. Then type of machine will be selected to predict a new data point based upon data classifying traing.

** Bye bye Labeling ***

Why is the real science approaching Support Vector Mahcine. Let’s make an artifial neural network based on Protein Data bank(You could use other resource, just pick the one of mRNA string that you would like being curious about diseas and symptom).

Classifying protein data out-front to identify a new protein

Simply understand mRNA translated in ribosome, that is a factory of protein. How tRNA manipulated mRNA it turns into protein. So let’s say an Artifical Neural Network that build protein after tRNA.

>>>Go to “protein data bank”

To choose an example — building protein identity classification is much easier and simple. You know how AGTC the code of mRNA and variety from tRNA. Goal is the building 3000 proteins. That is another assginment before beginning Support Vector Machine. Grab the most interesting mRNA and take into the protein data bank. Pull, Pulling. SVM doesn’t need that much code compared to other theories. We will discuss the SVM methodically.

>>>Be aware of SVM that is not made for probabilitic measure. Instead, it needs to be converted bettwen loss fucntion and the likelihood.

**Learning points**

1. Understanding Maximum Margin Classifiers (Links available soon)
2. To Define Support Vector Classifier
3. To Run Support Vector Machine in Python
4. To Compare Support Vector Machine vs. Logistic Classifier Method.

Practice Link >>SVM

ML series(1)- Support Vector Machine was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

The Most Hottest List of Academic Journal Paper in 2021 ≈ Learning Prep for the Case Group

Case Study > >

Convolutional 3D to 2D Patch Conversion for Pixel-wise Glioma Segmentation in MRI Scans

3D to 2D conversion by Using Pixel-Size segmentation

Key code:

Key idea and the unique set-up of Linear Equation:

Distributing Products toward Data model:

10-day challenging course just like building the case

Group Learning Class included Linear Algebra, Tensorflow, Matrix Talk

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

Loss function’s debates with Matthew correlation and Dice coefficient
Key code:

Key idea and the unique set-up of Linear Equation:

Distributing Products toward Data model:

Group Learning Class :

Research AI GroupStudy : Deep Neural Networks was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

🎯Deep Learning — Open Course Curator List was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

🎯AI — Open Course Curator list was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Introduction of Ubuntu 20.03 RTX3090 Tensorflow 2.4.1

Getting tensorFlow and pyTorch running on NVDIA. It’s considered in using RTX 3090, 3080, 3070. Here is the Guid for installation.

Keras vs. TensorFlow was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Youth Tech @groupstudy got inspired by the remarkable open course curator!

🎯Tensor Flow — Open Course Curator List was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Creatively Gifted Kid’s Pattern Development Machine learning model

The most exciting thing about this project is that it is simple and it works really well, which is based on the best-in-class design. The solutions and the latest in machine learning model is still in the process of being developed. The process of development includes the following a combination of open-source and proprietary software, including the integration of Gift Kid’s question data, the design of a question bank system, the integration of the pattern, and the evaluation and execution of the design in a professional, research-oriented active user base.

In one year, the development of this project based on a series of questions with an intuitive user experience from the user’s own creative brain will reach the best goal -learning, and simulation of a child’s life.

Creatively Gifted Kid’s Pattern Development was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Youth Tech @groupstudy got inspired by the remarkable “Core ML” open course curator

Core ML- Open Course Curator was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Youth Tech @groupstudy got inspired by the remarkable “Keras” open course curator!

🎯Keras— Open Course Curator List was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Youth Tech @groupstudy got inspired by the remarkable “Turi Create” open course curator!

🎯Turi Create — Open Course Curator List was originally published in AI Open Course Curator List by @ NakedAI on Medium, where people are continuing the conversation by highlighting and responding to this story.