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AI4ALL: Basics in Convolutional Neural Network
Rating: 4.2 out of 5(35 ratings)
2,417 students

AI4ALL: Basics in Convolutional Neural Network

Basics and Foundation of Convolutional Neural Networks
Created byYiqiao Yin
Last updated 6/2022
English

What you'll learn

  • Learn about the basics of Convolutional Neural Network models without any prior knowledge
  • Learn to use python to design a Convolutional Neural Network model without any prior knowledge
  • Learn from top tier Data Scientists to build Convolutional Neural Network models for production
  • Learn to develop your own customized Convolutional Neural Network models

Course content

2 sections • 11 lectures • 44m total length

  • Introduction1:09

    This video starts with the motivation of why we want to do convolutional neural networks.

  • CIFAR10 Dataset5:32

    This video introduces the basics of CIFAR10 data, a new data we will be looking at, and what are some features of this data that is a little above the difficulty of the MNIST Handwritten Digit Data.

  • Q1
  • Data Processing: CIFAR101:45
  • Convolutional Operation Theory6:04

    This video explains the theoretical concept of a convolutional operation.

  • Q2
  • Pooling3:40

    Pooling strategies are often times combined with convolutional layer. This video explains two common pooling strategies: average pooling and maximum pooling.

  • Fully Connectedness2:11

    To ensure the neural network model is well defined, this video explains the concept of fully connectedness.

  • Q3
  • Conv2D Layer7:06

    This video walks throug the line of code of conv2d layer and explores what this layer does to an image before training.

  • First Convolutional Neural Network Model8:10

    This video puts everything together and build the first Convolutional Neural Network model.

Requirements

  • No prior programming experience needed. You will learn directly in this class.

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.  The course focuses on Convolutional Neural Network models and introduce the important building block using Tensorflow.


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!



Who this course is for:

  • Pre-college level students interested in neural network models

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