12 Best Artificial Intelligence Projects in Python For Beginners [2024]

Starting your journey into artificial intelligence and machine learning might seem overwhelming. But as someone experienced in the field, let me assure you that this article is made just for beginners like you. Inside, you’ll find eight simple Python projects chosen especially to help you learn. 

Why are these projects so important? Well, think of them as your own little playground. They’re where you can try things out, make mistakes, and learn from them. And when you finish them, you’ll have something concrete to show off, which can really impress future employers. 

So, let’s dive into the world of AI through these fun Python projects. Together, we’ll learn and grow with every step we take. 

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Artificial Intelligence Projects in Python

1. Fake Review Detector

Everyone reads online reviews. Yelp, Trustpilot, Gripeo, and even Google My Business are well-known review sites where consumers come to check others’ reviews on businesses. However, some companies try to deceive customers by adding fake positive reviews. You can create a classifier that can recognize fake reviews and ensure that no fake reviews are allowed on the site.

Fake reviews tend to have specific tones and words which you can train your model to identify.

It’s a beginner-level project, so if you haven’t worked on artificial intelligence project ideas in Python before, you can start with this one.

2. Handwriting Recognizer

Computer vision is a central section of artificial intelligence. If you’re interested in using computer vision, then you can start with this project. Here, you have to create a solution that recognizes the handwritten content. You should be familiar with the basics of computer vision to work on this project.

However, it’s also a beginner-friendly task. You should start training your solution with simple symbols such as 0 and 1, then move onto more complicated characters.

3. Spoiler Blocker

In this project, you’d have to create a tool that identifies spam and blocks it automatically. It can be handy for discussion forums and platforms such as Reddit and Tumblr. We all hate spoilers, and if you’re interested in creating a tool related to media and entertainment, then this is the right project for you.

You can add the name of your show or movie, so if it’s mentioned somewhere, the tool will cover it with an image of your choice.

Working on this project will help you learn about natural language processing, which is quite a prominent section of AI and ML.

4. Spam Identifier

We have another natural language processing project for you. In this one, you have to create a tool that identifies spam content. Spam identifiers are commonplace these days. From Gmail to Truecaller, many devices use spam identifiers to streamline their user experience.

You can create one with natural language processing. Like the fake review project, you’ll have to identify specific tones and words prevalent in spam emails.

Then, you’d have to use that data to train your model.

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5. Traffic Analyzer

In this project, you’d have to build a traffic analyzing tool that suggests the optimal path for reaching a specific destination. The tool should check the different factors such as traffic density, length of a path, and the mode of travel while suggesting the right path to take.

You can take inspiration from Google Maps for this project. Apart from Google Maps, online taxi companies such as Uber and Ola utilize this technology as well.

That’s why working on this project would benefit you substantially.

6. Opinion Mining for Website

Sentiment analysis is among the most popular uses of artificial intelligence. In this project, you’d create a solution that analyses users’ comments about a website to see what’s the general opinion about that website.

FYI: Free nlp course!

7. Fire Detection and Localization Through Camera

You can create a solution that detects fire and localizes it through the surveillance cameras’ feeds. It’s an intermediate-level project, and you’d need to use CNN here.

At first, you should begin with a fire identifier and then add the ability to locate the fire so people can escape safely.

Check out all trending Python tutorial concepts in 2024

8. Game Automator (T-rex Dino)

Nearly every internet user has played Google Chrome’s Dino game. It’s the game where you control a dino that runs continuously and has to avoid obstacles through jumping up or bowing down. You can create a machine learning solution that automates the Dino and learns from its mistakes.

To work on this project, you should be familiar with reinforcement learning algorithms. This project is a great way to get a fantastic high score.

9. Resume Parser AI Project

The Resume Parser AI Project involves the development of an intelligent system using Natural Language Processing (NLP) and machine learning to extract relevant information from resumes. This project streamlines the recruitment process by automatically parsing resumes, extracting key details, and organizing the information for efficient candidate evaluation. 

Technical Requirements: 

• NLP Libraries: Utilize NLP libraries such as spaCy or NLTK to tokenize and process the textual content of resumes. 
• Machine Learning Models: Train machine learning models, potentially using frameworks like scikit-learn, to recognize and extract specific resume sections like education, experience, skills, and contact details. 
• Regular Expressions: Implement regular expressions for pattern matching to identify and extract key information, such as email addresses and phone numbers. 
• Database Integration: Store the parsed resume data in a structured database for easy retrieval and analysis. 
• User Interface: Develop a user-friendly interface, potentially using Flask or Django, to upload resumes, trigger parsing, and view extracted information. 

Artificial intelligence projects in Python with source code.

10. Object Detection System

The Object Detection System is an artificial intelligence project designed to identify and locate objects within images or video streams. Leveraging deep learning models, this system can real-time object detection, making it applicable for scenarios such as security surveillance, autonomous vehicles, and image analysis. 

Technical Requirements: 

• Deep Learning Framework: Use a deep learning framework like TensorFlow or PyTorch to build and train object detection models. 
• Pre-trained Models: Utilize pre-trained models such as YOLO (You Only Look Once) or SSD (Single Shot Multibox Detector) for efficient and accurate object detection. 
• Image/Video Input: Implement image or video input capabilities to test the object detection system on different media. 
• Real-time Processing: Optimize the system for real-time processing to ensure quick and accurate detection. 
• User Interface: Develop a user interface to visualize the detected objects and their bounding boxes. 

11. Pneumonia Detection with Python

The Pneumonia Detection with Python project aims to create an intelligent system capable of identifying pneumonia in medical chest X-ray images. By leveraging machine learning and image processing techniques, this artificial intelligence project in Python for beginners contributes to the early detection and diagnosis of pneumonia, assisting healthcare professionals in their decision-making process. 

Technical Requirements: 

• Dataset Acquisition: Gather a dataset of labeled chest X-ray images, with annotations indicating the presence or absence of pneumonia. 
• Deep Learning Framework: Utilize a deep learning framework like TensorFlow or PyTorch to build and train a convolutional neural network (CNN) for image classification. 
• Data Preprocessing: Implement image preprocessing techniques, including resizing, normalization, and augmentation, to enhance model performance. 
• Model Training: Train the CNN on the labeled dataset to enable it to learn patterns associated with pneumonia detection. 
• Evaluation Metrics: Assess the model’s performance using metrics such as accuracy, precision, recall, and F1 score. 
• User Interface (Optional): Develop a user interface for easy upload of chest X-ray images, initiating the pneumonia detection process. 

12. Product Recommendation Systems

The Product Recommendation System project involves creating an intelligent system that suggests personalized product recommendations to users based on their preferences, behavior, and historical interactions. This artificial intelligence project in Python is valuable for e-commerce platforms seeking to enhance user experience, increase sales, and foster customer loyalty. 

Technical Requirements: 

• User Data Collection: Gather user data, including historical interactions, purchase history, and preferences. 
• Collaborative Filtering Algorithms: Implement collaborative filtering techniques, such as user-based or item-based filtering, to identify patterns in user behavior and make personalized recommendations. 
• Content-Based Filtering: Incorporate content-based filtering methods that recommend products based on their attributes and the user’s preferences. 
• Matrix Factorization: Utilize matrix factorization techniques like Singular Value Decomposition (SVD) to discover latent factors influencing user-product interactions. 
• Evaluation Metrics: Assess recommendation system performance using metrics like precision, recall, and Mean Average Precision (MAP). 
• User Interface (Optional): Develop a user-friendly interface for users to view and interact with the recommended products. 

Source Code for the project.

Source Code for the project.

Checkout: 15 Interesting ML Projects for beginners

Why You Should Use Python for These Projects

There are many advantages to using Python for artificial intelligence projects in Python. When you start learning artificial intelligence and machine learning, you might wonder why Python is so prevalent in this field.

The biggest reason behind Python’s immense popularity is its various libraries. You can say that it has a library for nearly every imaginable task. Python has scikit-learn, NumPy, TensorFlow, and many other libraries that make ML easy.

AI and ML tasks require a lot of coding. Python’s pre-defined packages make this process much more straightforward as they reduce the amount of code you’d need to write.

Python is among the easiest programming languages to learn. Its syntax is very straightforward, which makes it accessible to everyone. This has played a massive role in making it a popular choice for AI and ML professionals.

Another huge reason behind Python’s widespread popularity is its compatibility. You can use Python with all the major systems, including Windows, macOS, Linux.

Because Python has been around for a long time and has many advantages, it has built a thriving community. Its community is very helpful and supportive. This makes it very suitable for beginners in AI and ML.

Why AI is in Demand

AI emerged in the 1950s, and since its arrival, it has grown exponentially. However, you might have noticed that the demand for AI professionals has grown substantially in recent years. You might wonder, “If AI has been around for over six decades, why has it gotten so popular recently?”

Our technological advancements have played a significant role in making AI accessible. Artificial intelligence and machine learning implementations demand a lot of computing power, which was not available before. Since the 1950s, our computing power has increased a trillion-fold, making it easier for us to perform AI processes.

Thanks to smartphones and the internet, the amount of data we generate every day has increased exponentially. We share social media posts, read news articles, shop online, and do a lot of stuff, all of which generate data. The most effective way to handle all of this data is through AI and ML.

The rise of tech giants such as IBM, Microsoft, and Tesla has considerably helped AI become popular. They made the financial commitments necessary that field research in this sector.

Now that we have discussed why we recommend doing artificial intelligence projects in Python and why this technology has become so popular let’s start discussing some artificial intelligence project ideas in Python.

Start Working on Artificial Intelligence Project Ideas in Python

I hope that this article on artificial intelligence projects in Python eliminated your doubts and questions regarding this topic. The only thing left now is to start working on a project and practice your skills. If you have questions or suggestions about these project ideas, please tell me by dropping a comment below. I’d love to hear from you. On the other hand, if you want an individualized learning experience, you can opt for an AI course. 

As you can see, AI is an amazingly powerful tool and startled the world many times, which we can use in many industries. From finance to social media, it has already become a crucial part of many companies. 

Also, If you’re interested to learn more about Machine learning, check out IIIT-B & upGrad’s Executive PG Programme in Machine Learning & AI which is designed for working professionals and offers 450+ hours of rigorous training, 30+ case studies & assignments, IIIT-B Alumni status, 5+ practical hands-on capstone projects & job assistance with top firms.