AI4ALL: Basics in Artificial Neural Network


Basics and Foundation of Artificial Neural Networks

What you will learn

Learn about the basics of neural network models without any prior knowledge

Learn to use python to design a neural network model without any prior knowledge

Learn from top tier Data Scientists to build neural network models for production

Learn to develop your own customized neural network models

Description

This course is created to follow up with the AI4ALL initiatives. The course presents coding materials at a pre-college level and introduces a fundamental pipeline for a neural network model. The course is designed for the first-time learners and the audience who only want to get a taste of a machine learning project but still uncertain whether this is the career path. We will not bored you with the unnecessary component and we will directly take you through a list of topics that are fundamental for industry practitioners and researchers to design their customized neural network model.

This instructor team is lead by Ivy League graduate students and we have had 3+ years coaching high school students. We have seen all the ups and downs. Moreover, we want to share these roadblocks with you. This course is designed for beginner students at pre-college level who just want to have a quick taste of what AI is about and efficiently build a quick Github package to showcase some technical skills. We have other longer courses for more advanced students. However, we welcome anybody to take this course!


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For full series of machine learning and deep learning topics, please view our other more in-depth courses at WYN Associates Education.

English
language

Content

Lecture

Load and Save Data
One Hot Encode
Q1
Rescale Data
Activation and Softmax Function
Q2
Regularization
Build a Neural Network Model
Loss Function
Optimization
Compiler
Fit and Train
Q3
Evaluation and Accuracy
Q4
Save and Load Model
Create Installable Git Package
Enroll for Free

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