Top AI Project Ideas & Topics
1. Fake News Finder
Fake news means false or ambiguous information spread to misguide people. Occasionally, fake news is presented so professionally that people completely trust it. It is imperative to differentiate between original news and fake news. If not detected early, it can create many unimaginable issues.
Utilize the Real and Fake News dataset available on Kaggle to develop a fake news detector project. The classification of fake and original news occurs via a pre-trained ML model known as BERT. Essentially, it is an open-source NLP model being loaded into Python.
2. Teachable Machine
Working on a Teachable Machine is one of the most interesting artificial intelligence project ideas for beginner-level AI enthusiasts. A Teachable Machine refers to a web-based tool developed to offer people easy access to machine learning functionalities. Its website allows you to upload images of various classes. Subsequently, you can train a client-side ML model on those images. This project enables you to learn many potent machine-learning functionalities.
3. Autocorrect Tool
When you start working on such AI based projects , you can gradually streamline your everyday tasks. Autocorrect application of AI is used in daily life, which assists in correcting spelling and grammatical errors.
You can build this project in Python using its TextBlob library. Its function ‘correct()’ will be helpful for this project.
4. Fake Product Review Identification
It is one of those AI projects for beginners that can deter business owners who usually upload fake product reviews on their websites. Its implementation will ensure that customers will not be diverted to false product reviews when they perform their product research. You can use Kaggle to build this project. Kaggle contains a Deceptive Opinion Spam Corpus dataset with 1600 reviews (800 positive and 800 negative reviews).
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5. Plagiarism Analyzer
Plagiarism Analyzer is one of the most prevalent artificial intelligence project ideas. The reason is it can detect plagiarism which is imperative to ensure original content. It can be challenging to determine the originality of the content without using a tool. This project helps you to build a plagiarism analyzer application to ensure originality and authenticity across a piece of content.
6. Bird Species Predictor
Topic experts can manually classify birds, but the process can be challenging and monotonous since it needs a massive data collection. The Bird Species Predictor project uses AI-based categorization, which uses a random forest to predict bird species.
7. Stock Price Predictor
It is one of the most valuable artificial intelligence projects for finance professionals and students aspiring to embark on a career in finance. This project provides access to a broad range of datasets. These datasets let you learn how to use ML algorithms to inspect a considerable amount of data. The availability of a vast amount of data simplifies finding models and patterns. Ultimately, it becomes easy to predict the future stock market precisely.
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8. Customer Advice System
It is one of the most prominent AI project ideas for those business owners willing to understand the customers’ product preferences. It uses a customer advice system to gain instant feedback on customers’ opinions of products. You need to build a real-time message tool within your e-commerce app. It helps you to communicate with customers and discerns their opinions regarding the products.
9. Lane Line Recognition
AI based projects are valuable for vehicles too. This project helps you develop a system connecting line-following robots and self-driven vehicles. So they can have real-time analysis of lane lines on a road. If self-driving cars are not effectively trained, it can lead to roadside accidents. This project solves this problem by using Python’s Computer Vision. It contributes to effectively detecting self-driven vehicles and reduces the risks of roadside accidents. Python’s OpenCV library helps you to accomplish this project.
10. Handwritten Digit Recognition
This project aims to develop a system that can identify handwritten digits using artificial neural networks. Usually, characters and digits written by humans represent different sizes, shapes, styles, and curves. The computers must be able to identify manual writing. The mentioned project uses artificial neural networks to develop a handwritten digit identification system to decode the digits that humans write accurately. CNN (Convolution Neural Network) is used for identifying digits on paper.
11. Pneumonia Detection
It is one of the most useful AI project ideas to detect pneumonia and ensure good health for people. Capturing patients’ X-ray images help you to detect diseases like a tumor, cancer, pneumonia, etc. But the images feature low visibility, and interpretation can be complex. This project aims to develop an AI system using CNN (Convolution Neural Networks) to identify pneumonia from a patient’s X-ray pictures effectively. It trains software solutions to detect and interpret this disease’s results accurately. The software processes the relevant information and tests it in the built-in database.
12. Recommendation System for Customers
It is one of the most versatile and prevalent AI projects for beginners in customer management. It builds a recommendation system that helps customers infer more details on products, music, video, and more. It uses concepts of machine learning, data mining, and ANN. The system drives more customers to the website and ultimately boosts the sales of a business.
13. Recognizing the genre of a song
This project imparts AI knowledge to beginners in an easy and fun-filled way. It is one of the famous mini- AI projects that gradually strengthen your AI skills. It helps you to recognize a song’s genre.
It uses an artificial neural network to identify the song and its genre. Subsequently, it showcases the appropriate playlist. You need to use Python’s Librosa library to derive all the necessary details of the song.
14. Predicting users’ forthcoming location
Travelers usually find it difficult to explore, especially when they travel to unaccompanied places. This AI project predicts the user’s most likely next location. It can be a restaurant or holiday venue. The projects make informed decisions using the LempelZiv (LZ) algorithm, Neural Networks (NNs), Markov Model (MM), Association rules, and Bayesian Networks.
15. Translator app
The translator app is an AI project that uses NLP fundamentals. It helps you to develop a translator app that helps translate a sentence from an unfamiliar language to your native one. It can be challenging and laborious to train an AI model from the beginning. However, you can use this project’s pre-trained models called ‘transformers’ that help you to translate any sentence easily. Python’s GluonNLP library can greatly assist in creating this app.
16. Housing Price Predictor
This project idea uses fundamental AI features to estimate home price variations. It also uses ML models and algorithms. To develop your dataset, you must download a public dataset from web scraping or Kaggle.
The next step is to clean the dataset by determining different null values, anomalies, duplicate entries, etc. Subsequently, you need to calculate different related histograms. As the project progresses, you will be acquainted with test web scraping methods and huge datasets to hold proficiency in the same.
17). Detecting fake products
There are many duplications happening for different products. So design a system which uses Artificial Intelligence to analyze the product and determine if it is authentic or not. Unlike humans, machines can analyze minutest of inconsistencies or faults in shape, colour, texture, size and many more. They can calculate all these and analyze if the product is fake or not. This accuracy will be based on numbers of images and data of the original product, it will then compare and detect the fake ones.
18). Facial Emotion Recognition
Now, everything that’s happening in a sci-fi movie, could be our future. There are a variety of fields where Artificial Intelligence is used. One such area of interest is detecting human emotions. There are many top companies investing a lot of money in doing this. So, you can design a facial emotion detection and recognition system that can be used to identify human facial expressions. So for this, first the system would have to analyze the facial expression for some time and then perform facial feature extraction and classify the facial expression. For starters, you can design the system to identify only one expression, maybe just happy or normal. Then you can enhance it and try different emotions.
19). AI Healthengine
Create a project that will use AI to give personalized health guidance to a user. The user must provide all their medical reports and based on that, the AI system will check for any pre-existing conditions, ongoing health concerns, and gaps in general health knowledge. Then the health engine could combine both these personal details and external health data to provide informed advice to the user. It can also help users with prescription support, vaccination advice, recommended doctor visits, and specific condition guidance.
20). Trying on online clothes and accessories
Now, you would have already heard about this feature, if you ever visited the lenskart app, here you can design an AI system that takes the input images and computes the person’s body model, representing their pose and shape. The segments are then selected on which the dresses are going to be displayed on, like for eg, a shirt on the body, gloves for hands, and so on and then when the user selects a particular dress, the system can combine them with the body model and update the image’s shape representation.
21). Spam email identification
Spam detection means detecting unsolicited emails by identifying the text content of the email. So for the project, create an artificial neural network to detect and block spam emails and also ensure that the user only receives notifications regarding the emails that are crucial to them. You can also enhance this by tuning it to user preferences. For example newsletters or updates that one person likes, will be disliked by someone else, so include fees.
22).E commerce recommendation engine
Have you ever liked any clothing item on any e-commerce website, and then you see the same clothing item in the ads of some website or on social media. AI is responsible for this. In this project, you can build an E commerce recommendation engine using the similarity among the background information of the items or users to propose recommendations to users. So, for example if the user has searched for apple phones, then you can design a recommendation engine that recommends apple phones to the user. Or you can identify trends and patterns in previous and other user-item interactions and advise similar recommendations to a present user based on his existing interactions. So, for example, if the person has bought a formal shirt, then you can design your recommendation engine, to recommend more formal clothing and accessories.
23).Loan Eligibility Prediction:
One of the major problems the banking sectors face is the increasing rate of loan defaults, so the employees find it difficult to decide who they should give loans to and who not to. Even if they do give, what are the chances of the person returning the loan amount?
So to solve this problem, You can use AI to design a program that predicts whether an individual should be given a loan by assessing various attributes like their salary, their previous loans details(did he pay all the installments on time) and many more and then notify whether or not to approve the loan. This can make the process easier of selecting suitable people from a given list of candidates who applied for a loan.
24).Handwritten notes recognition
Handwriting character recognition refers to the computer’s ability to detect and interpret alphabets and numbers. These inputs could be from various sources like paper documents, notes on phone, photos and other sources. Note that handwriting characters remain complex since different individuals have different handwriting styles. So you can develop a system that uses AI to scan the handwritten notes and convert them into digital format. You can use an artificial neural network, which is a field of study in artificial intelligence to design this system.