Title: Implementing Plant Disease Prediction using ResNet Model

[PRIYANSHU2026]

Description: I am working on implementing a plant disease prediction system using the ResNet model. I plan to use the HAGGLE dataset for training the model. The goal is to train the model on a cloud platform to leverage its computing power and scalability.

Tasks:

• [x] Download the KAGGLE dataset.
• [x] Preprocess the dataset for training.
• [x] Implement the ResNet model architecture.
• [x] Train the model on a cloud platform.
• [x] Evaluate the model's performance.
• [ ] Deploy the trained model for inference.

Additional Features:

• [x] Import necessary libraries:
  • import os for working with files
  • import numpy as np for numerical computations
  • import pandas as pd for working with dataframes
  • import torch for PyTorch module
  • import matplotlib.pyplot as plt for plotting information on graphs and images using tensors
  • import torch.nn as nn for creating neural networks
  • from torch.utils.data import DataLoader for dataloaders
  • from PIL import Image for checking images
  • import torch.nn.functional as F for functions for calculating loss
  • import torchvision.transforms as transforms for transforming images into tensors
  • from torchvision.utils import make_grid for data checking
  • from torchvision.datasets import ImageFolder for working with classes and images
  • from torchsummary import summary for getting the summary of our model

Labels: machine learning, cloud computing, enhancement, big project

Note: This will be the biggest project in this repository.

[Amarta113]

@PRIYANSHU2026 there is a typo error Kaggle

[Akshat111111]

The repo is of finance not, machine learning

[Amarta113]

@Akshat111111 is it necessary to work on finance related tasks?

[Akshat111111]

yes, this repo is directly or indirectly related to finance.