In this current technology-driven world, machine learning is a prominent area that makes our machine or electronic device intelligent. The purpose of this field is to transform a simple machine into a machine with the mind. In this article, we explore machine learning and artificial intelligence projects to boost your interest. Because these AI and ML projects are so competitive, tricky, and interesting to develop. I firmly believe these projects are the best place to invest your time and skill. Let’s move on to explore interesting, innovative as well as easy machine learning projects.
Best AI & Machine Learning Projects
Below we are narrating the 20 best machine learning startups and projects. If you are a beginner or newcomer in this world of machine learning, then I will suggest you go for a machine learning course first. Here, we have listed machine learning courses. Now let’s get started with the details.
1. Sentiment Analyzer of Social Media
This is one of the interesting and innovative machine learning projects. As, social media like Facebook, Twitter, and YouTube is the ocean of big data. Therefore, mining these data can be beneficial in a number of ways to understand user sentiments and opinions.
Additionally, this project can be effective for digital marketing and branding to understand the opinion or reaction for a product or service of a customer. To understand the functionality of this project, watch an example here.
Highlights of the Project
- This is one of the machine learning and artificial intelligence projects for beginners in python.
- To train the system, the project developer can help us with social media posts, short message tweets, or customer reviews based on system requirements.
- For beginners, Twitter data can be helpful as a tweet contains a hashtag, location, and many more, easy to analyze.
- Using a Twitter dataset, one can get plenty of data since it consists of 31,962 tweets.
- As a beginner, you can build your model to classify data as positive or negative.
2. Classification of Iris Flowers
If you are a beginner in the world of machine learning, then this easy machine learning startup for beginners in python is appropriate for you. This project is also known as the “Hello World” of machine learning projects. You can develop this project in R also.
This project can be developed using a supervised method like the support vector method of machine learning. The dataset of Irish flowers has numeric attributes, i.e., sepal and petal length and width. As a beginner, you need to figure out how to utilize the data.
Highlights of the Project
- The Iris flower dataset is small, and no need to do pre-processing.
- You can download this Iris flower dataset from here.
- To classify the flowers into among the three species – virginica, setosa, or versicolor is the task of this AI project.
- You can get the source code from GitHub.
3. Identifying Product Bundles from Sales Data
The project entitled ‘Identifying Product Bundles from Sales Data’ is one of the interesting machine learning projects in R. To develop this project in R, you have to employ a clustering technique that is the subjective segmentation to find out the product bundles from sales data.
Highlights of the Project
- To develop this project, you must have to know about data science. Here, we outlined data science courses.
- The language used: R
- Also, you must know about machine learning approaches like an unsupervised method for clustering.
- To identify bundles, Market Basket Analysis has to use.
4. A Music Recommendation System
Are you a lover of music? Always love to listen to your favorite one? Then, you will be glad to know about this interesting machine learning project idea. This can also be an innovative project. The goal of this project is to recommend music based on user listening history.
Highlights of the Project
- This artificial intelligence startup can be developed using both languages, i.e., python and R.
- To make your training and test dataset, you have to collect data from the user listening history in a given period.
- The training and testing data set are divided based on time.
- You can get the dataset and project description from here.
5. A Machine Learning Gladiator
It is a very much easy machine learning and Artificial intelligence project idea if you are a beginner. This project will help you to increase your knowledge about the workflow of model building. By developing this project, you can practice how to import data, how to clean data, pre-processing and transformation, cross-validation, and feature engineering.
Highlighting of this project
- You must know about regression, classification, and clustering algorithms.
- You can find the dataset from the UCI Machine Learning Repository or kaggle.
- You can develop this project using both languages, i.e., python and R.
- By developing this project, you will learn about the prototyping models quickly.
6. TensorFlow
Do you want to improve your machine learning skill? You may practice with this versatile artificial intelligence and machine learning software and framework to enhance your knowledge. TensorFlow is one of the best and popular machine learning open source projects. Basically, It is a part of the Google Brain team in Google’s Machine Intelligence Research organization. The GitHub link is here.
Highlights of the Project
- This is an open source software library.
- It is used for numerical computation using data flow graphs.
- Fast and flexible for a wide range of applications.
- It has an easy-to-use python interface.
- Additionally, it includes APIs for Java.
7. Sales Prediction of BigMart
Are you a beginner? Are you interested to learn how to build up a machine learning model? Then, your search ends here. This, BigMart sales prediction is one of the easiest machine learning and artificial intelligence projects for beginners in python. This is a data science project also. The purpose of this project is to develop a predictive model and find out the sales of each product at a given BigMart store.
Highlights of the Project
- This dataset consists of 2013 sales data for 1559 products across 10 different outlets.
- You have to build a regression model to predict the sales of each of 1559 products.
- By developing this project, you can understand the visualization of sales data.
- You will know about how to apply the techniques of machine learning in sales prediction in Python.
- You can access a complete solution for this project here.
8. Predict Wine Quality
If you love to develop an interesting and innovative machine learning startup like me, then this prediction of the wine quality project is just for you. You can develop this project using Wine Quality Dataset. The objective of this project is to predict the quality of the wine based on its chemical properties. This is one of the simple machine learning projects for beginners in R.
Highlights of the Project
- You will learn about data exploration by developing this project.
- To develop this project, you have to know about the regression models.
- You will learn about data visualization.
- You will also know about R and basic statistics.
9. Scikit-learn
Another open source artificial intelligence startup is scikit-learn. It’s quite easy to develop. This tool is a python module for machine learning projects. This is effectively accessible and highly reusable across various domains. You can find this project on GitHub.
Highlights of the Project
- An efficient tool for data mining and data analysis.
- You need to install a few python libraries named NumPy and pandas.
- This tool is free.
- It can be a useful tool to develop artificial intelligence projects to enter the world of machine learning.
10. Walmart Sales Forecasting
Do you want to know how to access a dataset? How to import and load it? Then, this sales forecasting Walmart dataset project is one of the interesting machine learning projects for you. The task of this project is to forecast sales for every department in every outlet to assist them in creating higher knowledge-driven choices for channel improvement and inventory designing.
Highlights of the Project
- Walmart dataset contains data for 98 products across 45 outlets.
- You have to install R-studio in your PC.
- Throughout the development process of this project, you will learn how to manipulate data in R and how to reshape the R package.
- Also, you will learn about conditional statements and loop in R.
11. MNIST Handwritten Digit Classification
If you want to become an expert in machine learning, you have to practice various domains. Deep learning and neural networks are such a scope where you can invest your time and skill as a beginner as they play a vital role in the application of image recognition. The task of this artificial intelligence project is to take an image that is a handwritten single digit and determine what that digit is.
Highlights of the Project
- The MNISt dataset is simple and easily accessible.
- The MNIST dataset consists of pre-processed and formatted 60,000 images of 28×28 pixel handwritten digits.
- You will enrich your skill in deep learning and logistic regression throughout the development of this project.
- You will learn how to convert pixel data into an image.
- For your convenience, you will find the complete solution here – MNIST Handwritten Digit Classification.
12. Theano
Theano, another open source machine learning startup or project. This tool is a python library that permits a machine learning developer to define and optimize mathematical expressions and evaluate them, including multi-dimensional arrays, efficiently.
The tool, Theano, integrates a computer algebra system (CAS) with an optimizing compiler. You can use it for your academic research also. If you use it for your educational research purpose, then you must have to cite it.
Highlights of the Project
- This tool is integrated with NumPy.
- It evaluates expression efficiently.
- This open source project can detect many types of errors.
- The GitHub URL is here.
13. Solving Multiple Classification Use Cases using H2O
If you are an expert on machine learning and have an idea about multiple domains like H20, data science, and machine learning algorithms. Then, this project is for you where you can use these skills. This is one of the machine learning and artificial intelligence projects in R. In this project, and you have to employ H20 and functionality to develop machine learning models.
Highlights of the Project
- You will learn about model scalability using H2O in a Hadoop environment.
- H20 integrates many machine learning algorithms like Linear regression, Logistic regression, Naive Bayes, K-means clustering, and word2vec.
- You have to use these: R-studio, R, and H2O.
- H2O includes a Stacked Ensembles method.
14. Keras
If you are a mid-level developer and want to enhance your skill for real-world machine learning challenges? Therefore, you must have to know about machine learning open source projects. Keras is one of the best open source machine learning projects. This tool has some prominent features like easy extensibility, user-friendliness and also you can work in python. GitHub URL is available here.
Highlights of the Project
- It’s a high-level neural networks API that is written in python.
- This open source tool permits easy and fast prototyping with its prominent features.
- This tool is compatible with: Python 2.7-3.6.
- This platform supports both convolution networks and recurrent networks, moreover the combinations of these two networks.
15. PyTorch
Do you know about NLP- Natural Language Processing? Are you interested in this promising field? If your answer is yes, then this open source project or platform is for you. Literally, PyTorch is an open source machine learning library for a python based on Torch. This tool is used for machine learning applications, such as natural language processing.
Highlights of the Project
- It has two high-level features: Tensor computation, i.e., NumPy with strong GPU acceleration, and deep neural networks built on a tape-based auto diff system.
- PyTorch uses the automatic differentiation technique.
- The hybrid front-end of this tool provides flexibility and speed.
- The detailed description of this tool is here- PyTorch.
16. Disease Prediction
If you want to deploy machine learning in medical science, then this machine learning startup on disease prediction may be interesting to you. The task of this AI project is to predict different diseases. You have to build a machine learning model in R using R Studio.
Highlights of the Project
- You may use this Breast Cancer Wisconsin (Diagnostic) Dataset. You can download it from the UC Irvine Machine Learning Repository.
- In this dataset, there are two predictor classes: malignant or benign breast mass.
- To develop this project, you have to know about the random forest.
- You get a detailed description of this project here.
17. Stock Price Prediction
If you are interested in working with the finance domain, this amazing idea might be interesting. The goal or task of this system is to predict future stock prices. This system learns from the performance of a company.
Highlights of the Project
- The Stock Market datasets can be downloaded from Quandl.com or Quantopian.com.
- The challenges to working with this project are that the stock prices data is granular, and these data are different types such as volatility indices, prices, fundamental indicators, etc.
- You can easily validate your system with new data.
- If you are a beginner, then you can limit the task of the project and can only predict six-month price movements depend on a quarterly organization report.
18. A Recommended Systems using Movielens Dataset
Today people are interested in watching a movie online rather than watching a movie on TV. If you are passionate about working with such an innovative and exciting project idea, then this idea might help you. The goal of this system is to develop an efficient recommender system.
Highlights of the Project
- Movielens Dataset consists of 1,000,209 movie ratings of 3,900 movies made by 6,040 Movielens users.
- This system can be developed using both languages, i.e., R and python.
- This machine learning project is helpful for beginners.
- You can build a world-cloud visualization of movie titles to develop a movie-recommended system.
19. Human Activity Recognition System
A human activity recognition system is a classifier model that can identify human fitness activities. To develop this project, you have to use a smartphone dataset, which contains the fitness activity of 30 people, which is captured through smartphones. This project will help you to understand the solving procedure of the multi-classification problem. If you are a beginner, then this project is absolutely for you to enhance your machine learning skill.
Highlights of the Project
- This artificial intelligence project is a classification problem. So, as a beginner developer, it will help you to increase your problem-solving skill.
- You will learn about SVM and Adaboost.
- The dataset has been divided randomly for the training and testing phase. In the training phase, there are 70% of data and 30% for the testing.
- The details of this project will be found here.
20. Neon
The open source machine learning and artificial intelligence project, neon is best for the senior or expert machine learning developers. This tool is Intel Nervana’s Python-based deep learning library. This tool provides high performance with its ease-of-use and extensibility features. The GitHub URL is here: neon.
Highlights of the Project
- It’s a framework for visualization.
- It has a swappable hardware back-end.
- You may write code once and deploy it on CPUs, GPUs, or Nervana hardware.
- This tool supports commonly used models, including convents, autoencoders, LSTMs, and RNNs.
Ending Thoughts
All the details are about the 20 best machine learning projects, and hopefully, you will get an interesting project idea by reading this article. We organized this article so that whatever your level is beginner, mid, or expert, you can learn something new, or you can know something new from this article.
Lastly, you can also see a few more interesting projects that are the Raspberry Pi and Arduino projects. Thank you so much for staying with us.
