Machine learning is becoming the future of numerous sectors, which is good news for job seekers. Learning the ins and outs of this innovative technology can be a lucrative investment in your career.
Simply studying the theory is a fair start, but it will never equip you with such mastery as first-hand practice. The best way to see the inner workings of machine learning is through individual projects.
Learning through practical means speeds up your machine-learning journey and is also an enjoyable way to approach a complex subject. Each successfully completed project will fuel you with motivation to learn and expand your portfolio at the same time.
Here are 13 machine learning projects that not only allow beginners to dabble in this field but are also fun at the same time.
Movie Recommendation System
You’re faced with personalized recommendations whenever you log into your Netflix account. These are generated by machine learning algorithms that use your history to predict what other shows you’ll like. Since most of us are familiar with these systems, creating a movie recommendation algorithm is a straightforward project to start with machine learning.
As with any machine learning project, you’ll need a sizeable dataset to feed the algorithm. MovieLens offers several datasets anyone can use. Their Latest Datasets are highly recommended for educative purposes and are popular among beginner learners as they have everything you’ll need for your first recommendation system. The full dataset contains 27,000,000 ratings of 58,000 movies from 280,000 users.
Titanic Passenger Survival
Would you have been among the 706 passengers that survived the sinking of history’s most well-known ship? An algorithm can give you the answer. If you’re looking for a playful, game-like project, consider executing the Titanic passenger survival project.
Through this machine learning project, you’ll build an algorithm that can predict whether someone would have survived the catastrophe based on several factors. You’ll need a dataset that contains information about the passengers that did and did not make it. The set mentioned above contains data like their name, gender, age, socio-economic status, and more. The machine will use this information to determine whether someone would have been rescued in the 1912 tragedy.
Housing Prices Prediction
The housing market often sees significant fluctuations. This machine learning project will help you determine the expected price changes of properties based on data collected previously. The project is an entirely beginner-friendly project with a small set of data that sheds light on the process in a simple manner.
You can download this dataset containing information on Boston housing that has been used extensively for similar practice sessions. The data was collected by the U.S Census Bureau and contains 506 cases.
Stock Prices Prediction
Finance is a great field to explore for anyone honing their machine learning skills. There are so many types of data available that you can come up with countless project ideas. Thanks to short feedback cycles, you can also evaluate the precision of your predictions soon after. A beginner-friendly but slightly more challenging finance-related project idea has to do with stock prices.
Predicting stock prices can be fun when your money isn’t on the line. Since the factors involved in stock value tend to be extremely dynamic and volatile, this project might have you rack your brain. You can use any organization’s reports to draw the necessary data. For instance, you can find Google’s 5-year stock price dataset on Kaggle.
Sentiment Analysis
Sentiment analysis is an invaluable tool in business today. Companies can use it to gain an understanding of the public’s opinion of their brand or products. Machine learning can help analyze large volumes of data on social media platforms to evaluate customer reactions and determine whether positive or negative language is used in textual communication. Sentiment analysis is complex, but that’s what makes this project particularly engaging.
Sentiment analysis can be applied to many fields. You can conduct a study based on Amazon product reviews or use a simple movie review dataset to determine the polarity of opinions. For a more advanced project, you can also mine Twitter data to examine the public’s opinion on certain topics.
Find Similar Images
If you’re leaning towards more visual projects, there are plenty of machine learning challenges to choose from that are based on image analysis. One is teaching a machine to find similar images based on the input accurately.
This technology can revolutionize e-commerce by facilitating customers’ browsing experience. With smart image recommendations, customers can find the products they are looking for even if they don’t remember their names. Image similarity can also make archives more easily browsable. You can download this product recognition dataset to use in your project.
Sales Predictions
Thanks to machine learning, stores can now manage their inventories better than ever. A system that forecasts sales volumes can help optimize restocks so there is no supply disruption.
You can try your hand at sales forecasting with this simple project using the data of a grocery store chain. The BigMart sales dataset contains the annual sales records of 1559 products at 10 different stores from 2013. The goal of the project is to predict the sales trends for the following year based on the data.
Handwriting Recognition
The digitizing of text has many applications today, but handwriting poses challenges to even the best optical character recognition (OCR) programs. Teaching a machine to recognize handwriting through computer vision and machine learning provides a solution to this problem. If you want to learn about neural networks and more advanced, deep machine learning, this handwriting recognition project is for you.
Since image-based projects tend to be more complex, it’s recommended that you start with a small and more manageable dataset, like digits. The MNIST dataset contains 70,000 images of handwritten digits. The images are labeled, enabling the algorithm to learn various handwritten variations of the same numbers.
Plant Species Classification
Machine learning can aid efficient classification, whether about facial expressions, music genres, or plant species. This simple but popular project is a great starter for anyone interested in computer vision.
The project aims to create a system that can effectively recognize and categorize different species of iris flowers. The small dataset makes this project manageable even for complete beginners. This dataset contains 150 instances which will be sorted into three categories. Once you feel confident, you can attempt a similar project with a larger dataset.
Loan Eligibility
The process of determining someone’s eligibility for a loan can be rigorous and lengthy. Banks take no chances, which often results in clients’ disappointment. Today, machine learning can help anyone determine their chances of qualifying. It can also give them pointers about the amount they will be able to borrow based on a slew of different factors.
Through this project, you’ll create a system that does exactly that. You’ll need a dataset that contains essential data about loan applicants, like their gender, marital status, education level, number of dependents, income, and other factors.
Home Value
Another housing-related machine learning project investigates the expected home value of a property. Zillow utilizes this technology in their Zestimate tool, which can reach high accuracy thanks to an extensive amount of available data.
This project is more complex but still beginner-friendly. You’ll use Zillow’s Economics dataset to create a house price prediction model.
Fake News Detection
The internet has become a great source of information, but it also creates the perfect environment for fake news. These stories can spread like wildfire thanks to social media, and few people will bother to check their authenticity. A machine learning model created to recognize fake news can help keep social spaces clear of misinformation. You’ll learn how to create a fake news detector through this project.
The model will use natural language processing to classify fake and real news. There are several datasets appropriate for the project available on Kaggle.
Music Recommendation
To finish off this list with another fun and lighthearted project, developing a system for music recommendations is a popular machine-learning project for those new to this technology. The project is similar to the movie recommendation project we mentioned earlier.
Like e-commerce and movie streaming websites, it’s also possible to generate recommendations based on music taste. Services like Spotify and YouTube utilize algorithms to keep their customers hooked, and you’ll see the secret behind it through this project. You can use KKBox’s dataset, which contains over 30 million tracks. Since classification is key to this project, you’ll get to dabble in neural networks.
Start Your First Machine Learning Project Today
Fun projects are the perfect way to get introduced to a complex field like machine learning. The 13 projects mentioned above are all beginner-friendly and can be finished within a weekend. Once you have completed a few of these projects, you’ll be able to come up with your own and solve unique problems with the experience you’ve acquired.
