Top 10 Machine Learning Project Ideas That You Can Implement

Machine Learning is one of the most popular emerging technologies in current times! And the best way to learn this technology is by doing projects. Other options like online courses, reading books, etc. only help in understanding the basics of ML, but it is only possible to truly learn the subject by doing projects with real-world data. This article has 10 Machine Learning Project Ideas that you can Implement and in doing so, learn more about Machine Learning than you ever did!

Most of these projects have corresponding data sets that are available on Kaggle. You can use these datasets to complete projects and learn some new skills in the field of ML. These projects are well suited to you if you are in the beginner/intermediate phase and still learning more about Machine Learning. In case you want more advanced challenges, you can always find more complex projects on Kaggle. So without further ado, let’s get started with these projects and learn something new!

1. Titanic Survival Project

This is a beginner’s project on Kaggle that is best for you if you are just getting started with ML projects. This deals with the Titanic disaster which is one of the most famous in marine history. All you have to do in the project is predict which passengers survived the Titanic shipwreck based on data such as their age, gender, socio-economic class, etc. 

For example, it is highly probable that someone rich from the first class survived as compared to someone from the third class. You can use the Titanic dataset on Kaggle for this machine learning project and just to make things more interesting, this dataset contains real data based on the people who died and survived the actual Titanic disaster.

2. Personality Prediction Project

Imagine how interesting it would be to read the posts written by people online and be able to understand their overall personality. It would solve a lot of confusion on the internet! This ML project aims to find the Myers-Briggs personality of a person based on the types of posts they put on social media. Myers Briggs Type Indicator is a personality identification system that divides a person into one of 16 different personalities based on introversion, intuition, thinking, and perceiving capabilities. 

The axis ranges from Introversion (I) to Extroversion (E), Intuition (N) to Sensing (S), Thinking (T) to Feeling (F), and Judging (J) to Perceiving (P). You can use the Personality prediction dataset available on Kaggle to create such ML projects.

3. Loan Prediction Project

It’s not at all easy to get a loan from the bank. Getting a loan approved requires a complex mix of factors not the least of which is a steady income! So this ML project aims to create a model that will classify how much loan the user can obtain based on various factors such as the user’s marital status, income, education, employment prospects, number of dependents, etc. 

Besides this, the Loan prediction data set provides details about all these factors which can then be used to create an ML model that demonstrates the amount of loan that can be approved.

4. Stock Price Prediction Project

The stock market is an ever-changing field with many highs and lows as companies succeed or go under. It is notoriously difficult to predict the stock market but that’s what this ML project is all about. You will predict future stock price returns based on past stock market data like opening price, closing price, trading volume, calculated returns, etc. as well as the news data like news articles published about company assets, etc. This stock market dataset on Kaggle contains all the data that you can use for projects on machine learning.

5. Xbox Game Prediction Project

Who doesn’t like Xbox gaming? Most people do and there are a lot of options for them to choose from! This project aims to predict which Xbox game a person will be most interested in based on their search queries online. And you can use the prediction dataset provided by BestBuy, a consumer electronics company that provides data on the search queries of millions of customers to understand what Xbox game they might be interested in. The data contains the user ID, the item that the user clicked on, the category the item belongs to, the query, click time, and query time.

6. Housing Prices Prediction Project

There are a lot of factors that determine the price of a house including its location, size, number of rooms, etc. But people ignore many of these factors while buying or selling a house. That’s where this machine learning project comes in! It provides many factors for the house like its frontage, area, street, land contour, utilities, proximity, garage quality, roof materials, etc. with the ultimate aim of predicting the final price of the house based on these factors. You can get the Housing Prices Prediction Project dataset for Kaggle and use it to create an ML algorithm that can accurately predict house prices based on these factors.

7. Sales Prediction Project

What if shops could estimate the products that they sell every month? That’s what this project aims to accomplices. You have to forecast the total amount of products that are sold in each shop while you are provided with the daily sales data. However, this machine learning project is dynamic as well because the list of shops and products may change every month. You can get the sales data set to create this ML project on Kaggle. The data set contains a training set and the test set for which you need to forecast the sales. This project on Kaggle is also part of the final project of the “How to Win a data science competition” course on Coursera.

8. Digit Recognizer Project

Out of all ML projects, this one will improve your computer vision skills tremendously! You need to create an ML algorithm to identify the identified digits from a dataset that has other handwritten images as well, and there’s a lot of data! The data set contains tens of thousands of images of which some are handwritten digits as well. Before starting this project, you must brush up on your skills in simple neural networks and Classification methods such as Support Vector Machines and K-nearest neighbors. You can obtain the dataset required for this project on Kaggle.

9. Credit Card Approval Prediction

Not everyone can obtain a credit card with ease. The bank decides whether or not to issue a credit card based on multiple factors that demonstrate how trustworthy the person is. And credit scores objectively quantify this trust factor and the amount of risk. So this ML project aims to create an ML model that can find out if an applicant is a ‘good’ or ‘bad’ client for obtaining a credit card. The dataset for this contains data such as annual income, income category, education level, way of living, etc. to decide whether the applicant is suitable for obtaining a credit card or not.

10. IMDB Box Office Prediction

Movies are a big part of our world! But nobody knows how a movie will perform at the box office. There are some big-budget movies that bomb and there are smaller movies that are smashing successes. This project on machine learning tries to predict the overall worldwide box office revenue of movies using data such as the movie cast, crew, posters, plot keywords, budget, production companies, release dates, languages, and countries. The dataset on Kaggle contains all these data points that you can use to predict how a movie will fare at the box office.

Conclusion

However, the list is not limited to this, but one thing is for sure, i.e. these projects on machine learning are truly a great option if you are just starting in Machine Learning or if you know the basics and need more practice. So check out all of these projects and when you are done with them, you can attempt even more projects on Kaggle and also take part in active competitions. Who knows, you might even win the first prize!

Machine Learning Project Ideas – FAQs

What are the 4 basics of Machine Learning?

The four major Machine Learning basics are:

• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Semisupervised Learning

Is there any real-life example of Machine Learning?

Since Machine Learning and Deep Learning have been growing at the pace of time, there are endless possibilities and real-life examples that are surrounded us, some of them are:

• Image & Speech Recognition
• Medical Diagnosis
• Predictive Analysis

How to start a Machine Learning project? 

For any beginner, it is a must to understand that a project must be deployed right from scratch. From finding the problem to creating the solution to train the model. Below are the defined 7 steps that are involved in this phase. They are:

• Data Collection
• Data Preparation
• Training Model
• Analyze/Evaluate
• Serve the Model
• Retrain the Model