Artificial intelligence is one of the most sought-after fields of research in 2023. All sectors are rushing to incorporate AI and machine learning to make their processes more efficient, resilient, and productive. Hence, it is only natural that more and more students and professionals are looking to benefit from the ever-expanding realm of artificial intelligence .
Some of the best artificial intelligence applications are chatbots, image recognition technologies, product recommendation systems, search engines , and spam filters.
There are several means of learning AI, such as books, online tutorials, offline courses, and projects. Probably the best mode of learning is AI books . They are your companion for all seasons.
However, working on artificial intelligence projects will allow you to understand AI better and check how much you’ve learned.
Therefore, here, we will discuss some of the best AI project ideas to get you started or going if you are already on the path of becoming an AI developer.
10 Best Artificial Intelligence Projects with Source Code
AI projects come in all shapes and sizes. Working on them is much more complex than working on programming projects because you have many options. However, that’s not always the case.
To make this list of the best artificial intelligence projects legible, we will divide it into beginner, intermediate, and advanced levels so that you can choose where to start. That said, let’s start with artificial intelligence projects for beginners.
Artificial Intelligence Projects for Beginners
For newcomers and starters, beginner-level AI projects are the perfect launchpad. These projects don’t necessitate going in-depth into artificial intelligence or machine learning. Instead, they allow learners to understand the mechanics of AI.
Below we have compiled a list of four beginner-friendly artificial intelligence project ideas:
1. A Resume Screening Tool
A beginner-friendly AI project could involve designing a tool to screen resumes based on job requirements. This is an excellent tool that has been used by full-fledged organizations to cut both effort and time in selecting the best candidates for a specific job profile. That’s what we can call a resume-screening tool. You can also call it a resume parser or resume screener for simplicity.
Anyways, it will work based on identifying specific keywords in candidate resumes. To accomplish this project, you must understand clustering algorithms and natural language processing (NLP). The basic task here is to filter resumes based on keywords. Keep resumes with the required keywords and toss away resumes that don’t have them.
To work on the resume parser project, you need a resume dataset. There is a multitude of them available at Kaggle . Otherwise, you can use datasets from other platforms too. Depending on the dataset, you will get many columns, including job title and bio.
As the data is in the form of text in the dataset, you need to preprocess it. You can use the NLTK library or some other ML library with NLP capabilities.
Next, you need to develop a clustering algorithm that filters keywords, skills, and closely-related words to keywords.
2. Instagram Spam Detector
Another great artificial intelligence project idea for a beginner to try their hands on is an Instagram spam detector. You can leverage the capabilities of machine learning to develop a spam detection model that can distinguish between genuine and spam comments. It’s a useful AI project that you can keep to yourself or develop and sell as a product (yes, that might be too ambitious, but it can work out).
For the required dataset, you can either download one from the web or scrape the web and build one on your own. Do whatever you find convenient. Now, there are multiple approaches to accomplishing this beginner-level AI project.
One approach is adding keywords for classifying words akin to spam comments. Use N-Gram to provide weightage to words commonly appearing in spam comments. Next, compare them with scrapped comments from the web.
Alternatively, you can use cosine similarity or some other distance-based algorithm. Please note that to enhance the performance of the algorithm employed, you need to eliminate punctuation, stop words, and whitespaces from the dataset.
You can use a pre-trained model like BERT or ALBERT for superior results. What makes these models powerful is that they consider factors such as coherence and the context of the sentence.
3. Animal Species Detection
Computer vision is a distinct field of machine learning, which, in turn, is a subset of AI. There are several beginner-level AI projects that you can develop using it, and one that we suggest is an animal species detection system.
Here, you need to simply use images to train an ML model to understand the difference between various animals, such as dogs, cats, horses, hens, sheep, cows, and so forth. Technically, identifying animal species is a multi-class classification problem. Thankfully, being a beginner-friendly project, you can find several datasets on the web, such as Kaggle and GitHub .
One dataset you can try is Animals-10, available on Kaggle. It has data on ten different animal species: butterfly, cat, chicken, cow, dog, elephant, horse, sheep, spider, and squirrel.
If you want to focus on a Pythonic build, you can use a popular pre-trained model, VGG-16, and load it into Python using the Keras library. It is a CNN architecture trained on ImageNet that has more than 14 million images.
Once you’ve successfully loaded the VGG-16 model, you can train it using the ML dataset that you chose earlier. For instance, if it was the Kaggle Animals-10 dataset, then you need to train VGG-16 to identify among ten different types of animals.
4. Autocorrection Tool
MS Word and Google Docs have an autocorrect feature that generates suggestions for correcting grammatical and writing errors. Grammarly is a popular tool among content developers capable of detecting grammatical, syntactical, and - to some extent - logical errors and spelling mistakes. It is not an autocorrect tool, but it has the functionalities of one.
A basic autocorrect tool can be developed using artificial intelligence. You can develop it using many technologies, but Python is a good option as it already has a library for developing it, TextBlob.
TextBlob comes with a correct() function that will check the word (a string of text) for spelling mistakes and then autocorrect it to make a correct word closest to the original word. There are certain limitations to the Pythonic library that you can overcome by building your own model using BERT or some other pre-trained NLP model.
5. Fake News Detection System
Many people disclose fake news or misleading information in the media. However, fake news can create a lot of chaos in people. Today, with the help of AI, many social media platforms, like Twitter, Facebook, and Instagram, are working on making their systems perfect to detect fake news accurately and prevent them from reaching out to people.
Creating a fake news detection system as a beginner can be an excellent AI project idea. To get started, you will need access to the Kaggle dataset . Next, leverage various data science libraries , such as NumPy, Pandas, Scikit-Learn, and py caret and transformers.
Once you develop the system, it can detect whether the news is fake or not.
More Beginner-Level AI Projects
Other than the projects mentioned above, here are some more beginner-level AI project ideas for you to try out:
- Fake product review identification system
- Language Translator
- Object detection system
Artificial Intelligence Projects for Intermediate Learners
You must proceed with intermediate-level artificial intelligence projects once you’re done with many generic beginner-level AI projects. These are neither too difficult to develop nor neither too easy. Thus, you need to invest a good amount of research and effort in them.
Moreover, you must have a robust knowledge of many advanced AI and machine learning concepts, like ANNs , CNNs, transfer learning, visual recognition, etc. Following are our three picks for the best intermediate AI projects:
6. Ethnicity Detection Model
An interesting artificial intelligence project idea for intermediate (and advanced-level) developers is an ethnicity detection model, which, as its name suggests, will identify a person's ethnicity from a given picture.
To accomplish this AI project, you need to have a good knowledge of computer vision, artificial neural networks (ANNs), and convolutional neural networks (CNNs). However, if you don’t want to use ANNs and CNNs, you can use transfer learning as an alternative.
Accuracy is an important factor in developing the ethnicity detector. That’s because there are so many ethnicities worldwide, and many share several similarities. Hence, you can restrict ethnicities to 3 or 4 to keep the project's complexity low. Nonetheless, you can go with a higher number if you want.
Use the UTKFace dataset at Kaggle or some other online dataset to train the model. Models developed using UTKFace allow developers to achieve an impressive accuracy of 0.80. Also, use the Ethnicity Detection in Python GitHub resource.
7. Stock Price Predictor
If you’re already an investor or would like to invest in securities and equities, like stocks, then you can kill two birds with one stone with a stock price predictor. Working on this project will allow you not only to put many AI and ML techniques to test but also to create something helpful to understand the price movement in stock markets better.
Today, many apps and tools leverage the capabilities of machine learning and AI to predict the future price fluctuations of a stock. The share market is a goldmine of data for ML experts.
Moreover, you can try different types of datasets to work on the stock price prediction model. Because the feedback cycles of the stock market are transient, it can help you to validate your predictions.
You can try to predict the price movements of a particular stock in a particular time period, such as for the upcoming month or 3 months, or 6 months. To accomplish this project, you must collect stock report data.
8. Product Recommendation System
A product recommendation system is a typical example of AI. It is also known as the customer recommendation system. It’s a popular component of eCommerce websites. The idea is simple, provide the customer with relevant product suggestions based on their recent purchases and product search history.
Developing a product recommendation system is a good idea to learn the various concepts involved in AI and machine learning . To know more about how such a system works, look no further than Amazon.
In addition to making life easier for customers, a product recommendation system helps organizations deliver a better customer experience and increase their sales. The data fed to the model will be the browsing history and the customer's recent purchases. You can either prepare data on your own or download one of the already available on the web.
Source Code: Product Recommendation System
More Intermediate-Level AI Projects
That sums up our list of intermediate-level artificial intelligence projects. Some more intermediate-level AI project ideas that you can tinker with are:
- Age detection system
- A chess game
- Next word predictor
- Price comparison tool
- Traffic predictor
Advanced Artificial Intelligence Projects
This is when things get interesting and complex! Advanced AI projects will not only allow you to test your learning but also have the potential to create real-world-ready systems that can prove to be more than just projects for demonstration.
In this section, we will discuss only two projects. We will start by looking into developing a sign language recognition app in Python and then proceed to build a system that can automatically mark attendance.
So, let’s start.
9. Sign Language Recognition (Python)
Sign language is complex, but many learn it to better communicate with people with hearing and speaking disabilities. However, not everyone knows it. An advanced AI project idea is a sign language recognition system. The one we are going to discuss here leverages Python .
Working on this project is challenging. Hence, you need to understand many machine learning concepts, such as model training, perceptron, and multi-layer model development.
Now, there are various ways to accomplish this model. One way is to leverage the World-Level American Sign Language dataset. It has more than 2,000 classes of sign languages.
For training your model, you need to extract frames from the data and then load the Inception 3D model trained on the ImageNet dataset, a visual database of more than 14 million hand-annotated images. You must train a few dense layers on top of the model using frames from the loaded dataset.
You can generate text labels for specific sign language gesture image frames by doing so. Once you’re done building the model, you can deploy it to help normal people communicate effectively with people with hearing or speaking impairments.
10. Automatic Attendance System
Although it might sound like an easy task to develop an automatic attendance system, it is actually quite complex and challenging to do so. It involves dataset loading, model training, face recognition, and more. The system must be able to recognize the faces of the students or employees and then mark their attendance accordingly.
Therefore, you need a camera that can take pictures of the candidates and then compare them with the images stored in a database and mark attendance accurately.
More Advanced-Level AI Projects
Other than the advanced-level artificial intelligence projects explained above, here are some more advanced-level AI projects to try:
- Colour detection
- Detecting violence in videos
- Fake product review monitoring system
- Hand gesture recognition model
- Sports betting apps
- Text generation model
Bonus Artificial Intelligence Projects with Source Code
Besides the ones mentioned above, here are some other bonus project ideas you can consider to add to your portfolio and advance your skills.
11. Wine Quality Prediction
Wouldn't it be amazing to predict the quality of the wine you drink? You can do it by creating a system that anticipates the quality of the wine. Many factors impact the quality of the wine, such as location, types of grapes, age, etc. Create a system that accepts input, such as location, year of manufacturing, pH level, acidity levels, flavor, and other factors. Based on the input provided, the system should anticipate the quality of the wine.
Source code: Wine Quality Prediction
12. Password Checker
As there has been an increase in the rate of cyberattacks these days, one of the ways to protect your system and data from hackers is to choose strong passwords. But how will you know your password is strong? Well, for that, you can create a password checker. A password checker should indicate a password as strong if it contains letters, numbers, and special symbols. If a password does not contain any of the three types of characters, it should indicate as weak.
Source code: Password Checker
13. Heart Disease Prediction
The healthcare section is one industry vertical where AI is proving to be very beneficial. It assists hospitals in efficiently handling administrative tasks, patients care, diagnosing diseases in no time, and many other aspects. To create a heart disease predictor, you will need to use a heart disease patient dataset . Further, you need to train the system with various machine learning algorithms so that it provides accurate predictions.
Source Code: Heart Disease Prediction
14. Image Caption Generator
Many people opt for using caption generators to post images with catchy captions. You can consider creating an image caption generator that takes an image as input and creates a caption accordingly. It should be able to create a caption based on things it detects in an image. In short, it should be able to transform an image into words in a sequential order that makes sense.
Source Code: Image Caption Generator
15. CV Analysis
Analyzing CVs from a huge pile is a pretty mundane and intimidating task. Wouldn't it be great if there were a machine that would analyze all CVs ad shortlist some of the best ones? Yes, you can create such a system. A CV analyzer will list a few best CVs from a large file that helps organizations hire the right candidate that best fits the job. You need to use natural language processing (NLP) to implement this system.
Source code: CV Analysis
Artificial intelligence is a lucrative career path in 2023 and beyond. However, it requires dedication, creative thinking, knowledge, and lots of practice. Since the tools and techniques for AI are evolving quickly, an AI developer should stay abreast of the latest developments. The abovementioned artificial intelligence projects will help you learn AI better by putting your knowledge to the test.
However, please note that the projects that we have mentioned above are mere ideas. Hence, please don’t shy away from being creative while working on them.
Wish you all the luck!
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