Are you looking for some amazing deep learning project ideas? You have come to the right place. In this article, let’s go through some interesting deep learning project ideas that you can jump on to and implement pretty easily.
Deep learning is a very quickly growing technology and is often used in creating solutions to various problems. Deep learning technology can solve a lot of complex problems that are otherwise pretty hard to solve. Let’s discuss some exciting deep learning project ideas that you can implement without much effort.
Even though deep learning is an advanced topic in computer science, it is not rocket science. Any computer programmer can learn the basic concepts and get started with coding deep learning models. These days, we have the assistance of several libraries and tools to aid us in creating advanced deep learning solutions to problems.
Before we jump into the projects, let’s go through the fundamentals of deep learning that you never want to skip. Deep learning is a technology that tries to mimic the functionalities of the human brain in processing data to do various operations.
Deep learning uses algorithms called artificial neural networks to do tasks. Some of the important applications of deep learning are speech recognition, image recognition, classification, translating languages, facial recognition, virtual assistants, etc.
We will discuss about these applications and tutorials to implement them in detail. If you’re familiar with the basics of Python and machine learning concepts, you’re good to start with deep learning.
Now, let’s dive right in and discuss some pretty cool project ideas on deep learning.
Cats And Dogs Image Classification
Image classification is one of the most important applications of deep learning. If you don’t have prior experience working on deep learning projects, then I would highly recommend you to start with this project. Let’s classify images of dogs and cats using deep learning.
This was my first deep learning project, which I did when I was in the final year of my computer science degree. The prerequisites for doing this project are knowledge of Python fundamentals and machine learning/deep learning basics.
You don’t have to be an expert in programming to do this. If you have the basic skills and the eagerness to learn new things, this would be a fun project for you.
We can use the keras library of Python to classify the images of dogs and cats. Keras library makes the coding easy as it has several in-built methods for doing the tasks. We can also make use of some other important Python modules such as numpy, pandas, PIL, etc.
You need to provide a lot of images of cats and dogs to the model so that it can differentiate between cats and dogs. Thankfully, we can download the whole dataset from the Internet and provide it to the model. You don’t need to collect all the images by yourself.
When I did this project some time ago, I documented all the steps that I’ve done so that I can help someone else to do this project easily than I did. So, if you are interested in doing this project, I recommend you to check out the step-by-step tutorial that I wrote on Cats and Dogs Image Classification Using Keras.
AI Virtual Assistant
Why buy Alexa or any other virtual assistants when you can create your own? Yes, with the help of Python and deep learning, you can create your own virtual assistant that will communicate with you and obey your commands.
Maybe, it won’t give you all the superpowers of Iron man. But, you can keep this as your Jarvis that will assist you in several tasks such as sending emails, playing music, home automation, etc.
There are plenty of tutorials available online on creating virtual assistants using Python. This will be a fun and interesting project to do.
To create a virtual assistant, we can make use of the Python libraries such as pyttsx3, speech recognition, etc. These modules have built-in methods to do several tasks easily.
You can define different functions for the virtual assistant as you want. Start with the basic functionalities like replying to your commands. You can add more complex functionalities on top of that to improve the skills of your virtual assistant.
If you’re interested in doing this project, you can check out this article, which will help you in building an AI assistant. Also, don’t forget to search for some videos on YouTube. You’ll see a lot of really interesting videos there on this topic.
Image Classification Using Cifar-10 Dataset
Cifar-10 is a standard computer vision dataset that is used for image recognition. It contains 60000 images, which are 32×32 in size. The dataset contains images of 10 object classes with 6000 images for each class.
The object classes that are present in the cifar-10 dataset are airplanes, automobiles, birds, cats, deers, dogs, frogs, horses, ships, and trucks. All these different classes are mutually exclusive.
You don’t need to manually download all the images. You can import the cifar10 dataset from the keras module itself. The keras library makes it really easy to train the deep learning model and test it.
Once you complete training the convolutional neural network model, you can also test it by giving some random input images. The model will most likely predict the correct output.
I did this project after I completed the cats and dogs image classification. So, if you have done that project, then you can also try this one, which would be a slightly different image classification project than the previous one.
Just like I did with the cats and dogs image classification, I’ve documented all the steps that I’ve taken while doing the cifar-10 image classification project. If you are interested in doing this project, check out the step-by-step guide I made on Cifar-10 Image Classification Using Keras.
Face Detection From Images
We all might have used the face detection lock on our mobile phones or somewhere else. Have you ever wondered how these devices detect your face accurately? Well, your answer is deep learning. Deep learning is used to solve face detection problems with very high success rates.
Whether you want to identify faces from images or using the camera, deep learning can be used effectively. In this project, you’ll be creating a deep learning model to detect faces from images.
When you upload a group photo to Facebook or other social media apps, you might have seen that these apps detect the faces of your friends and give you autosuggestions. Now, if you know the fundamentals of deep learning and Python, you can also create a model that will work in the same way.
We can make use of the OpenCV module of Python that contains several methods that will make our tasks easy. Also, we can use the MTCNN library to create an MTCNN(Multi-task Cascade Convolutional Neural Network). The MTCNN model that we create is a Keras model.
If you are interested in building a face detection project using deep learning and Python, then I would suggest you check out this article, which will help you build the project step by step.
Handwritten Digit Recognition Using MNIST Dataset
Can deep learning techniques be used to detect the text we write? Of course! In this project, you’ll be creating a convolutional neural network to detect handwritten digits using deep learning.
To build this project, you need to provide a lot of images of handwritten digits to the CNN so that you can train it. But, you don’t need to take a lot of images or search for them on the Internet. You can use the MNIST dataset for doing this project.
The MNIST dataset is a standard dataset that is used in deep learning and computer vision.MNIST stands for Modified National Institute of Standards and Technology dataset. This dataset contains 60,000 small grayscale images of handwritten single digits between 0 and 9 with square 28×28 pixels.
You can use the keras library of python for building the CNN model and import this dataset directly using keras. Train and test the model with enough data so that it can predict handwritten digits with high accuracy.
If you’re interested in doing this project, then I would point you to a great article that covers everything in detail about this project. Click here to check it out and build your own version of the handwritten digits recognizer.
Final Thoughts
Deep learning is a very wast field within artificial intelligence, and you can do a lot of things about it. These projects were a few recommendations from me to help you get started with the subject quick and easy.
I hope this article was helpful to you in finding out some interesting deep learning project ideas. If you think you have some cool deep learning project ideas in your mind, then comment down below.
Select any one of these ideas and start coding with the help of the mentioned tutorials. You’ll learn more about deep learning as you build more projects.
If you’re interested, check out the article I wrote on 21 Machine Learning Project Ideas.
Happy coding!
