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Deep Learning for Image Classification in Python with CNN

Deep Learning for Image Classification in Python with CNN

In this article we will discuss some deep learning basics. We will also perform image classification using CNN with python implementation.

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learn in  Deep Learning for Image Classification in Python with CNN

  • 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

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.

Course content

Download Dataset                                            01:50

What is inside train folder?                               01:01

What is the .hdf5 file?                                       00:42

What is inside test folder?                                 00:28

What is inside our_prediction folder?               00:27

Image Classification Python Code                    00:40

Enabling GPU in Google Colab                        00:39

Is GPU connected to Colab notebook?              01:49

Download TensorFlow and CUDA                    00:32

Compare the Speed of GPU with CPU              01:20

Connect Google Colab with Google Drive        00:58

Check the Number of Images in the Dataset      03:44

Image Augmentation                             09:57

Transfer Learning                                  02:11

Fine Tuning / Freezing of the Layers    02:04

Model Compilation                    01:02

Callbacks: EarlyStopping          02:16

Callbacks: ModelCheckpoint     01:13

Training          02:44

Testing            03:35

Prediction       02:18