Deep Learning for Image Classification in Python with CNN

欢迎来到“使用 CNN 在 Python 中进行图像分类的深度学习”课程。在本课程中，您将学习如何在 Keras 中使用 TensorFlow 后端从头开始创建卷积神经网络 (CNN)，并且您将学习训练 CNN 以解决图像分类问题。请注意，您不需要高性能的工作站来学习本课程。我们将在免费的 Google Colab 环境中执行整个项目。您只需要互联网连接和免费的 Gmail 帐户即可完成本课程。这是一门实用的课程，我们将专注于 Python 编程，您将非常了解程序的每个部分。在本课程结束时，您将能够使用 Keras 和 TensorFlow 作为后端来构建和训练卷积神经网络。您还将能够可视化数据并使用该模型对新数据进行预测。这门图像分类课程实用且直接适用于许多行业。您可以将此项目添加到您的项目组合中，这对于您接下来的工作面试至关重要。本课程的设计最直接，可以明智地利用您的时间。

Convolutional Neural Networks for Computer Vision With Keras and TensorFlow on Google Colab Platform

Published 09/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 37 lectures (1h 7m) | Size: 820.5 MB

What you’ll learn

Understand the fundamentals of Convolutional Neural Networks (CNNs)
Build and train a CNN using Keras with Tensorflow as a backend using Google Colab
Assess the performance of trained CNN
Learn to use the trained model to predict the class of a new set of image data

Requirements

Basic knowledge of Python Programming

Description

Welcome to the “Deep Learning for Image Classification in Python with CNN” course. In this course, you will learn how to create a Convolutional Neural Network (CNN) in Keras with a TensorFlow backend from scratch, and you will learn to train CNNs to solve Image Classification problems. Please note that you don’t need a high-powered workstation to learn this course. We will be carrying out the entire project in the Google Colab environment, which is free. You only need an internet connection and a free Gmail account to complete this course. This is a practical course, we will focus on Python programming, and you will understand every part of the program very well. By the end of this course, you will be able to build and train the convolutional neural network using Keras with TensorFlow as a backend. You will also be able to visualise data and use the model to make predictions on new data. This image classification course is practical and directly applicable to many industries. You can add this project to your portfolio of projects which is essential for your following job interview. This course is designed most straightforwardly to utilize your time wisely.

Happy learning.

How much does an Image Processing Engineer make in the USA? (Source: Talent)

The average image processing engineer salary in the USA is $125,550 per year or $64.38 per hour. Entry-level positions start at $102,500 per year, while most experienced workers make up to $174,160 per year.

Who this course is for
Beginners starting out to the field of Deep Learning
Industry professionals and aspiring data scientists
People who want to know how to write their image classification code