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Learn how to classify 10 famous personalities image dataset using Residual Network in PyTorch with over 90% accuracy in just 1 minute on a single GPU. Follow our step-by-step guide now!

Classifying 10 Famous Personality Image Dataset using Residual Network in PyTorch

A.K.A. Training an image classifier from scratch to over 90% accuracy in around 1 minute on a single GPU

In this project, we'll use the following techniques to train a state-of-the-art model in around 1 minute to achieve over 90% accuracy in classifying images from the 10 Famous personality Image Dataset,

  • Data normalization
  • Data augmentation
  • Residual connections
  • Batch normalization
  • Learning rate scheduling
  • Weight Decay
  • Gradient clipping
  • Adam optimizer
import torch
import torchvision
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
matplotlib.rcParams['figure.facecolor'] = '#ffffff'

%matplotlib inline

Fetching Kaggle Datasets into Google Colab

Follow the below step to download kaggle dataset. This applies to any of Kaggle dataset.