Whether you are a data science novice or an expert in the field, you can enhance your portfolio by showcasing your Kaggle projects. Kaggle offers datasets for machine learning, data visualization, exploratory analysis, and neural network projects. You can use the applied machine learning process to enhance your current knowledge.
Read our article to find the best Kaggle projects to get started on. We will include Kaggle projects for beginners, intermediate, and advanced data science professionals. You can use Kaggle to learn data science and breeze through the hiring process to get your first job in tech.
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5 Skills That Kaggle Projects Can Help You Practice
Kaggle is a crowdsourced community that offers machine learning and data science courses, certifications, projects, and datasets. The community is ideal for new data scientists looking to expand their understanding of the subject. Below you will find the essential skills that can help you complete your Kaggle projects.
- Machine learning. Having great machine learning skills is essential to creating quality Kaggle projects. You will need to learn machine learning model training for data prediction and processing projects.
- Data analysis. As Kaggle is a data science community, it offers tons of data analysis projects. Having SQL, machine learning, and data visualization skills will help you finish projects and even compete in Kaggle competitions.
- Python. Having Python understanding and skills is crucial to data science projects as it is one of the most popular programming languages used in data science. Kaggle offers several Python projects using datasets for fake news detection, chatbot projects, and customer sentiment analysis.
- Artificial intelligence. Along with machine learning skills, Kaggle projects also require in-depth artificial intelligence skills. You will need to master computer vision, deep learning, neural networks, and AI languages.
- Statistics. Statistics and mathematics skills are also essential to succeed in the machine learning and data science fields. In addition, you’ll need to sharpen your skills in data visualization, probability, and data distributions.
Best Kaggle Project Ideas for Beginners
These Kaggle project ideas are best suited for those with foundational data collection, coding, and data science skills. These beginner ideas cover basic machine learning, datasets, Python, and supervised and unsupervised learning projects on Kaggle. Beginner projects are the best way to learn a coding language and enter the analytics industry.
Identify Characters from Google Street View Images using Julia
- Kaggle Skills Practiced: Julia, image processing, dataset analysis
If you have foundational coding skills and are looking to learn data science languages, then Julia is a great general purpose and high-level language to learn. It isn’t as widely used as Python or C++, but it is still used in the field. The level of difficulty is perfect for beginners because you can learn quickly if you already know other languages.
In this project, you will identify characters from Google Street View images using Julia. It is offered as a Kaggle competition that also offers tutorials on popular Julia features. You will use data from the Chars74K dataset that contains images with different fonts, characters, and backgrounds.
COVID-19 Open Research Dataset Challenge
- Kaggle Skills Practiced: Data logging, Kaggle coding, data assessment, summary tables
As a Kaggle beginner, you can practice a COVID-19 challenge where you access public datasets on the coronavirus and help scientists find the best methods of sifting through massive datasets related to COVID. This project’s dataset was created in collaboration with IBM, Microsoft, Google Cloud, and the World Health Organization.
You will use the dataset to create summary tables that incorporate risk factors, clinical studies, queries, patient descriptions, and interventions data. You will use foundational data processing, Kaggle code setup, word embeddings, and data logging in this project. You can also enter Kaggle’s competition for beginners with your project.
Run a Python Code on Kaggle
- Kaggle Skills Practiced: Python, operating systems, Jupyter notebooks, Python scripts, Python interpreter
There are many uses of Python, including assisting with artificial intelligence, data analysis, deep learning, and data visualization. This project is for those with basic Python and Kaggle environment knowledge. To get started with Python, you can run Python code on a Python interpreter, self-contained scripts, or Jupyter notebooks.
Real Estate Price Prediction on Kaggle
- Kaggle Skills Practiced: Machine learning models, regression analysis, prediction, linear regression, gradient techniques
Machine learning is a crucial skill to have when working with Kaggle on artificial intelligence and data science projects. This real estate price prediction project on Kaggle includes a complex dataset that incorporates transaction dates, house ages, and prices.
You will be diving into regression analysis, prediction, multiple regression, and linear regression. You will also input valuable data variables into your model for effective performance. If you are in search of foundational machine learning projects, then this is a great beginner’s learning tool.
Sentiment Analysis with Tweets on Kaggle
- Kaggle Skills Practiced: Pre-processing, machine learning, sentimental analysis, logistic regression, sentiment prediction
If you want to become a marketing analyst, research scientist, or UX researcher, having sentimental analysis skills is essential to your job. This project’s dataset requires you to translate human language into positive and negative polarity scale data values using emojis.
You will pre-process the data and use a classification model for sentiment prediction via machine learning processes. This project uses real datasets that contain over a million tweets. It is best suited for beginners in sentiment analysis and machine learning projects.
Best Intermediate Kaggle Project Ideas
The best intermediate Kaggle project ideas cover challenging artificial intelligence, time series forecasting, market analysis, and applied machine learning processes. You will need to have in-depth exploratory data analysis, predictive algorithm analysis, machine learning, and data science coding skills.
If you are an entry-level data science professional with intermediate industry skills and are looking to add Kaggle to your portfolio of projects, then these projects are ideal for you. They are at a medium difficulty level so you can start building portfolio projects and impressing your hiring manager.
Sales Forecasting Challenge for Store Item Demands Using Time Series Forecasting
- Kaggle Skills Practiced: Sales analytics, time-series analysis, deep learning methods, machine learning, predictive algorithms, ARIMA
Forecasting sales prices using time series forecasting in the business sector is a highly in-demand skill. If you are interested in working in advanced machine learning and sales analytics professions, then this project is for you.
You will have access to five years of datasets from 10 stores and will use predictive algorithms to forecast three months of sales trends for 50 products. Depending on your preference, you can use deep learning, ARIMA, or vector regression methods to forecast sales and develop a machine model with an effective approach to your training methodology.
Data Mining for Grocery Stores Using Market Basket Optimization
- Kaggle Skills Practiced: Data mining, market basket analysis and optimization, machine learning model, customer behavior analysis
Data mining essentially identifies valuable and approachable dataset patterns from raw datasets. You will need to learn R, SAS, and SQL, Python, and quantitative modeling to be a proficient data miner. This skill is valuable across technology, marketing, retail, criminal justice, and business industries.
In this project, you will use market basket analysis using the Apriori algorithm to predict customer purchasing behavior. You will use this dataset and train your machine learning model. Be sure to analyze the correlations between customer identity, product preference, and shopping patterns.
Exploratory Data Analysis with Python
- Kaggle Skills Practiced: Exploratory analysis, Python, data visualization, preliminary analysis
Exploratory data analysis is similar to feature engineering because it derives insights from data prior to the data prediction process. Kaggle offers tons of datasets for exploratory data analysis projects. You can choose from housing price, sales price, or automobile price datasets available on Kaggle.
You will need a working knowledge of descriptive analysis, Python, R, statistics, and data hypothesis tests to do this project. You will conduct a preliminary analysis, import the dataset, divide the dataset into numerical and categorical categories, and deal with missing values using Python.
Forecast Web Traffic Using Time Series Analysis and Predictive Analysis
- Kaggle Skills Practiced: Predictive analysis, data visualization, machine learning approach, ARIMA, time series analysis
Predictive analysis uses data mining, machine learning, and other statistical techniques to predict future events and time series analysis that tracks data sequences. To be proficient in both these analysis techniques, you will need to have an excellent understanding of data analytics processes.
This project is best suited for those looking to polish their data forecasting expertise. You will use Python, data visualization, competitive machine learning, and ARIMA to forecast web traffic for Wikipedia articles. You will also use deep learning tools for your model prediction when completing this project.
Real-Time SMS Spam Detection
- Kaggle Skills Practiced: Python, machine learning model, data sorting, pre-processing
This project uses machine learning, data sorting, pre-processing, and a Python chat server to create a spam detection system. You will use Kaggle’s SMS spam collection dataset and train your ML model while also creating a chatroom in Python. You will categorize spam and legitimate messages and identify incoming messages via the chatroom server.
Advanced Kaggle Project Ideas
If you have advanced data science skills and are looking to expand your machine learning, deep learning, and artificial intelligence knowledge, then advanced Kaggle project ideas are for you. Advanced Kaggle project ideas cover advanced Python, feature engineering, data visualization, deep learning classification, and deep neural network topics.
Having expertise in these skills can help you land senior data science jobs that come with high salaries. According to PayScale, the average salary of a senior data scientist is $127,456, which is much higher than average.
Credit Card Fraud Detection Using Machine Learning
- Kaggle Skills Practiced: Feature engineering process, machine learning model, logistic regression, data visualization
If you want to practice machine learning model training, logistic regression, artificial neural network, and background analysis, then this project is for you. Kaggle offers a dataset with 284,807 transactions with 492 fraud transactions and you will train your ML model to detect the fraudulent transactions.
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You will use the feature engineering process and extract test and training set features to create test model predictions using the testing model accuracy process. This is one of the best advanced projects on Kaggle that can help you become an expert.
Implement Customer Segmentation Using R
- Kaggle Skills Practiced: R, customer segmentation, data visualization, data exploration
Customer segmentation is an essential marketing strategy that allows businesses to divide their audience into categories based on gender and website activity. Having customer segmentation skills is beneficial for marketing analytics, user experience research, and data analytics jobs.
This project uses Kaggle’s mall customer dataset. You will use this data to perform data exploration, import essential packages, and gain insights about the data using R. You will also perform data visualization with R to identify the minimum and maximum customer ages, annual income, and spending scores.
Image Caption Generator with Python
- Kaggle Skills Practiced: Deep learning model, Python, neural networks, Keras library
This Kaggle project idea revolves around deep learning, advanced Python, computer vision, natural language processing, and artificial neural network concepts. You will use Python and train a machine to automatically generate image captions using neural networks.
This is an advanced project that requires you to know Jupyterlab, NumPy, deep neural networks, Python, and convolutional neural networks. You will use the Kaggle dataset and Keras library to prepare text data, develop a deep learning model, and generate new caption descriptions.
Advanced Time Series Analysis in Python
- Kaggle Skills Practiced: Python, time series analysis, data visualization
This time series distribution project offers three primary tasks involving data seasonality, trends, and autocorrelation components. You will build visualizations, correlate multiple time series, and evaluate the relationships between the components. You can use Kaggle’s dataset to predict air pollution measurements using time series analysis and datasets for weather information.
Predict Personality Types on Myers-Briggs Personality Application
- Kaggle Skills Practiced: Machine learning models, data pre-processing, logistic regression, app creation
Most personality tests offer a result after completion of 15 to 20 questions, but this project uses machine learning to predict a user’s personality based on a single sentence. You will use Kaggle’s dataset on the Myers-Briggs type indicator to train and build a multi-class model.
You will use data pre-processing and logistic regression to train your machine learning model. You will build an app and integrate your model with the application to generate personality type prediction. This project requires app creation, machine learning, and logistic regression skills.
Kaggle Starter Project Templates
Kaggle starter project templates are beneficial to both data science newbies looking to complete projects and data science experts wanting to take part in Kaggle competitions. Starter templates make your overall project creation and development process easier and allow you to further understand the platform.
- Get started with Kaggle projects. This template is for Kaggle newbies looking to do their first project on the platform. It offers a template with the basic structure for the platform’s Python environment, Kaggle API, and Kernel.
- Starter template for IP network traffic flows. This template will help you perform an exploratory analysis project on IP network traffic flows on Kaggle. It includes starter code and step-by-step instructions.
- Starter template for win-go and color prediction. For everyone looking to build a prediction and exploratory analysis project, this color prediction starter template will help you get started.
- Starter template for tagged anime illustration. This is yet another starter template for exploratory analysis. It will help you complete machine learning projects related to image tagging and facial recognition.
- Template for Kernel metadata. If you want to run a Kernel on Kaggle, then this template will provide the API command and file specification for it.
Next Steps: Start Organizing Your Kaggle Portfolio
If you are looking to land lucrative data science jobs, you should start organizing your Kaggle portfolio. Be sure to include projects relevant to your desired professional goals. Read below to find three tips for your Kaggle portfolio.
Include Data Analysis
The first Kaggle tip is to add data analysis projects to your portfolio. Depending on your data analytics background, you can find Kaggle projects related to time series analysis, exploratory analysis, and segment analysis.
Complete Machine Learning Model Training Projects
Kaggle offers several beginner and advanced machine learning model training projects and datasets on its platform. You can take part in Kaggle competitions and add your project solutions to your portfolio. According to PayScale, the average salary for people with machine learning skills is $108,000.
Add Kaggle Certifications to Your Portfolio
This tip applies to data science newbies looking to enhance their candidacy. Kaggle offers tons of certifications and courses that cover Python, feature engineering, deep learning, SQL, AI ethics, and natural language processing. You can acquire certifications that are in demand in your desired profession.
Kaggle Projects FAQ
Depending on your skillset and expertise, you can create projects on Kaggle using Python, machine learning, exploratory analysis, artificial intelligence, and time series analysis. Kaggle is a crowdsourced data science and machine learning platform that offers a wide array of data-related projects.
Kaggle competitions are public data science competitions, where Kaggle offers relevant datasets and problem descriptions. Participants will upload their solutions to the platform to be considered. Kaggle collaborates with several top organizations including IBM, Google, and the World Health Organization to provide complex datasets for competitions.
Yes, the courses offered by Kaggle are free. Students can learn several artificial intelligence and data science fields including deep learning, Jupyter environment, Python, R, Julia, machine learning, data analysis, and data visualization. Kaggle also offers free certifications for these courses.
Some of the top data science projects on Kaggle include real estate sales prediction, facial recognition, image caption generator, heart disease prediction, and COVID-19 open research.
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