By Aqsa Zafar, Ph.D. Scholar in Machine Learning | Founder at MLTUT | Solopreneur | Blogger.

1. Dog’s Breed Identification

There are various dog breeds, and most of them are similar to each other. As a beginner, you can build a Dog’s breed identification model to identify the dog’s breed.

For this project, you can use the dog breeds dataset to classify various dog breeds from an image. You can download the dog breeds dataset from Kaggle.

I also found this complete tutorial for Dog Breed Classification using Deep Learning by Kirill Panarin.

2. Face Detection

This is also a good deep learning project for beginners. In this project, you have to build a deep learning model that detects the human faces from the image.

Face recognition is computer vision technology. In face detection, you have to locate and visualize the human faces in any digital image.

You can build this project in Python using OpenCV. For the complete tutorial, check this article, Real-time Face Recognition with Python & OpenCV.

3. Crop Disease Detection

In this project, you have to build a model that predicts diseases in crops using RGB images. For building a Crop disease detection model, Convolutional Neural Networks (CNN) are used.

CNN takes an image to identify the disease and detect it. There are various steps in Convolutional Neural Network. These steps are:

  1. Convolution Operation.
  2. ReLU Layer.
  3. Pooling.
  4. Flattening.
  5. Full Connection.

You can download the Agriculture crop images dataset from Kaggle.

4. Image Classification with CIFAR-10 Dataset

Image classification is the best project for beginners. In an image classification project, you have to classify the images into various classes.

For this project, you can use CIFAR-10 Dataset, which contains 60,000 color images. These images are categorized into 10 classes, such as cars, birds, dogs, horses, ships, trucks, etc.

Source: CIFAR-10 dataset.

For training data, there are 50,000 images, and for test data, 10,000 images are used. Image classification is one of the most used applications of deep learning. You can download the CIFAR-10 dataset here.

5. Handwritten Digit Recognition

To explore and test your deep learning skills, I think this is the best project to consider. In this project, you will build a recognition system that recognizes human handwritten digits.

You can check this tutorial for Handwritten Digit Recognition using Python.

This tutorial uses the