Machine learning projects is an effective way to gain hands-on experience in this transformative field. Whether you are a beginner looking to break into this domain or a seasoned professional, these projects will help you tackle real-world problems. Through the ML projects, you will also develop critical-thinking abilities and strengthen your portfolio.
ML is one of the hottest and most exciting career paths right now. It has exploded in popularity over the past decade as it has allowed computers to access and use data to learn from themselves without being explicitly programmed. Technology is rapidly changing, and these jobs didn’t even exist a decade ago.
So, if you’re thinking of transitioning into this magical world of machine learning, then wait — learning by doing is the most efficient way to get started with machine learning projects.
Also read: How to Become a Machine Learning Engineer in 2024?
Top 10 Machine Learning Projects for Beginners
Machine learning projects for beginners help you give your career a boost. If you’re a beginner, then it’s crucial to give time to pet projects. These projects give you a chance to apply what you’ve learned & strengthen your core concepts. Following are 10 machine learning projects for beginners:
1. Iris Flower Classification Machine Learning Projects
In this machine learning project, you will predict the species of the iris flower. To do this project, you should know about supervised learning algorithm decision tree (or KNN) in machine learning.
2. Titanic Survival Predictor Machine Learning Projects
The beginner ML project is basically a project in which datasets are provided related to the passengers of the Titanic ship. Here you have to predict whether a passenger has survived or not based on several features given about them, namely – age, sex, and class.
This is a great tool to practice:
- Data cleaning
- Feature engineering
- Logistic regression
3. Handwritten Digit Recognition Machine Learning Projects
In this machine learning project you will build a system that can recognize and manipulate images in a very simple way. This machine learning project is good for a first step into image processing, neural networks and the MNIST dataset.
4. Movie Recommendation System Machine Learning Projects
In this machine learning project you will build a system which can recommend movies to users based on their past ratings or by their previous preferences. Additionally you will also learn about collaborative and content-based filtering.
5. Spam Email Detection Machine Learning Projects
In this machine learning project you will build a model to differentiate between spam and normal emails, considering the email content as well as other attributes. As a student, you will learn how to work with text data, process it, extract features from it and then build multiple classification algorithms.
6. House Price Prediction Machine Learning Projects
Predict the selling prices of houses based on different features like:
- Location
- Size
- Number of rooms
This is a practical beginner machine learning project on regression analysis and feature selection.
Also read: What is Machine Learning? A Comprehensive Guide
7. Customer Churn Prediction Machine Learning Projects
This ML project helps businesses identify customers more likely to churn or stop using their services. By building from a snapshot of identified customers and their classification, you get to work on customer data using classifiers to create a model that will forecast new classifications.
8. Stock Price Prediction Machine Learning Projects
This machine learning project investigate the stock market by predicting prices based on historical data and technical indicators. This challenging beginner ML project mixes time series analysis with machine learning.
9. Sentiment Analysis Machine Learning Projects
This machine learning project analyzes social media posts, product reviews, etc., to determine whether the review is positive or negative. This is a type of natural language processing (NLP) and text classification project.
10. Image Caption Generator Machine Learning Projects
Build a system that writes accurate descriptive captions for your images. This is a very interesting human-computer beginner machine learning project involving vision and NLP.
Top 10 Intermediate Machine Learning Projects
Now that you have got a hang of the basics, let us try a few machine learning projects which are a little advanced:
11. Automatic License Plate Recognition Machine Learning Projects
This is one of those cool ML projects, where which criminal is driving the car is known, just like in those cool detective scenes. Well, that’s a small but impactful example to describe what we are about to do here. Automatic license plate recognition has the ability to identify the license plate number from an image. It combines object detection and text recognition.
12. Land Use Segmentation Machine Learning Projects
This machine learning project involves processing the scenes of land which are visible in the satellite images. The idea is to partition the scene into agriculture, forest, river, road etc. Good project for a scientist inclined towards computer vision.
Also read: Artificial Intelligence vs Machine Learning: 9 Key Differences
13. Fake News Detection Machine Learning Projects
This is another cool machine learning project. In this era of fake news, this kind of news has become one of the most effective way to manipulate masses. So, detecting it is really important to avoid any potentially dangerous impact.
14. Diabetes Prediction Machine Learning Projects
It’s a cool machine learning project which can save a patient’s life. By using the patient information, we are going to predict whether a person will be diabetic in the coming years or not. This project shows that ML can be used to improve healthcare.
15. Movie Recommendation Systems Machine Learning Projects
This is again a really cool machine learning project. A recommendation system would be a good project. Plus there are already many recommendations available on how to go about building a recommendation system.
16. Image Denoising Machine Learning Projects
You will need a noisy image for this awesome ML project. We will be training a convolutional neural network to reconstruct the original image given the noisy one. But if it is not noisy enough for you, simply search for a pack of images to generate some uniform noise on all the images.
17. Deep Learning With Genetic Algorithms Machine Learning Projects
For all the future Darwin enthusiasts, this simple machine learning project is a nice option to start playing with evolved models. Also, you can select your working environment. To focus the subject let’s say that reinforcement learning is the brain-stretching work.
18. Data Science For Startups Machine Learning Projects
This machine learning project is really for beginners. It demonstrates how to invent your own data product. The idea is to predict or generate the data with machine learning. For an in-depth example, extract and analyze the data for any startup that does launches in San Francisco.
19. Sales Forecasting Machine Learning Projects
Businesses should be able to forecast their sales accurately. Use this simple machine learning project to forecast your future sales and see the expected revenues.
20. Object Detection Machine Learning Projects
Ever wanted to create your own self-driving car? AI Object Detection and Image Classification with TensorFlow is a really exciting research area but also very complex, so there will be some leniency from the machines.
Also read: Demystifying the Role of a Machine Learning Engineer: Skills, Responsibilities, and Career Path
Top 9 Advanced Machine Learning Projects
Are you ready for the majors? If you’re looking for a real challenge, we have some advanced machine learning projects:
21. Simulate a Self-Driving Car Machine Learning Projects
This is another very cool and trendy ML project these days. The hardest part of building a self-driving car is building a self-driving car. But you can simulate it with machine learning and reinforcement learning. It is a milestone paper that combines so many AI technologies.
22. Natural Language Generation (NLG) Machine Learning Projects
In this machine learning project you will build a system that gives possible solutions to generate human-like text, say essays, poems or e-commerce product descriptions. There are always some more challenging workarounds, like NLP and machine learning chatbots, at almost the human level. In this ML project you will use different concepts of Generative AI.
23. Speech Recognition Machine Learning Projects
Speak with your computer and it becomes the same as speaking with a friend. Based on deep learning and speech recognition models, you will develop a ML project for converting speech into text. This task is very interesting and can be applied in virtual assistants or auto-transcription systems.
24. Summarizing Your Videos Machine Learning Projects
Videos can be long and time-consuming. In this machine learning project, either you can provide keyframes for videos as summaries or deep learning and computer vision techniques can generate short summaries from the video. This productive machine learning project saves time and increases video understanding.
Also read: Steps to Transition into ML Engineer Role for Software Engineers
25. Game Playing Using Reinforcement Learning Machine Learning Projects
Have you ever thought of making an AI which can beat humans in games? Reinforcement learning is the way to go for training agents on how to play and learning survival while playing (e.g religious conflict spaceships). This machine learning project is all about machine learning and game theory.
26. Generative Adversarial Networks (GANs) Machine Learning Projects
The generative adversarial networks (GANs) can generate realistic images, music, or any other data. It is an emerging subject with a wide scope for splendid creation.
27. Climate Change Modeling Machine Learning Projects
Build models to replicate forecasted climate change projections for terrestrial and marine systems globally. Very high stakes machine learning here, requiring a lot of fancy data work in this machine learning project.
28. Multimodal Learning Machine Learning Projects
Leverage multiple data modalities for richer understanding. In this machine learning project, you’ll explore multimodal learning— for example:
- Image captioning
- Video understanding
- Sentiment analysis with visual context
This level of artistry demands expertise and experience across numerous domains of machine learning.
29. Explainable AI (XAI) Machine Learning Projects
Many machine learning models are black boxes. This explainable AI machine learning project is about interpreting machine learning models and getting more interpretable and understandable predictions. It is one of the most important works on AI ethics and transparency.
How to Start a Machine Learning Projects?
Embarking on a new machine learning project may be intimidating, but it need not be. Below are some pointers to help you get going:
- Select a Project: Your machine learning project should match your skill level and interests. Since you are just starting out, start out with easy beginner level small projects and slowly work your way up to more advanced projects as you master the skills.
- Data Collection: Create or find a dataset that is suitable for your project. The data should not be dirty, wrong or be of any other type but the one that fully represents the problem you are trying to solve.
- Examine the data: Spend some time to look at the contents of your datasets properly. This can help you to learn more about the data, e.g. its nature and patterns, possible mis-filled values so that they can be replaced with new ones.
- Pick Algorithms: Select the right machine learning algorithms based on the type of project you are working on and the kind of data sets you have.
- Train and Evaluate Models: Train models in the process indicated; the models should have been or should be trained on data and their performance tested with standard metrics (e.g. precision, recall).
- Tune and Iterate: Change algorithm hyperparameters or do more feature engineering to improve the models.
- Deploy and Monitor: Once you have built and trained your model, you will need to deploy it in real time production and constantly monitor its performance if it is generating accurate results or not.
Master Machine Learning With Interview Kickstart Today!
Our Advanced Machine Learning Course is designed with a curriculum that is updated in real-time and consists of 500+ FAANG mentors. You will be exposed to interactive live training sessions and interview prep advice, which will help you with gaining confidence in answering challenging technical interview questions.
We have seen these modules successfully prepare over 17,000 tech professionals before you. Now it’s your turn.
FAQs: Machine Learning Projects
Q1. What Programming Language Is Best For Machine Learning?
Given the diverse libraries and frameworks including Scikit-learn, TensorFlow, Keras (now TF.K) and PyTorch, Python has become the most used language in machine learning.
Q2. Do I Need A Strong Math Background For Machine Learning?
You don’t technically need to have a strong background in Linear Algebra, Calculus, or Statistics to start hacking on ML from Day 1 (but again most people think you do). Thankfully there are plenty of resources to learn the math if you want.
Q3. How Much Data Do I Need For A Machine Learning Project?
The amount of data you need is also determined in part by how complex your machine learning project ideas are – what sort of algorithms will you be using? How much diverse, chaotic movement do you want to extract from that data?
Q4. What Are Some Common Challenges In Machine Learning Projects?
Various challenges are faced while addressing machine learning projects, such as data cleaning and preprocessing, feature engineering, model selection, and avoiding underfitting or overfitting the models. Finally, there is the challenge of deploying it in production.
Q5. Where Can I Find Datasets For Machine Learning Projects?
Several repositories are available online to look for datasets for use in machine learning project ideas. Some include Kaggle and the UCI Machine Learning Repository. There is also the option of gathering your data or utilizing publicly available APIs that provide this information.
Related reads:
