It has been found that artificial intelligence and machine learning has become very popular among engineering and non-engineering students in recent times. With so many developments in this area, one can only be intrigued by the immense scope and demand that lies in this field. It is very important for every aspiring ML enthusiast to work on their own projects before joining the software industry. Here are some interesting machine learning project ideas to give you some hands-on experience in this area of work.
1) Sentiment Analysis
Sentiment analysis is one of the most popular machine learning projects among engineering students. This is a very import project idea in today’s times as with every passing day, it is important that we get to know about the real sentiment of a person than the one he puts in front of the world. Sentiment analysis can be done from the facial features, voice features or from text. Sentiment analysis is largely used in areas such as video game testing, customer feedback at stores, testing the emotions of a driver, and other such similar areas of work. Sentiment analysis happens to be a great idea for your upcoming project as it is the need of the hour. In recent times, when emotions can be faked easily on social media, psychological treatments and in areas such as police custody, it is important that we know the real emotions behind a person’s face.
Recommended Python Libraries:
- Stanford CoreNLP
2) Stock Prices Predictor
Building stock prices predictor is one of the best ways to get started with machine learning. Stock price prediction software that can keep a check on the stocks and predict future stock prices have a high demand in business firms. Data scientists find a huge bundle of opportunities in this sector as there are so much data available in modern times. It is important that before one gets started with the project one must have a fair share of knowledge in the following areas: regression analysis, predictive analysis, action analysis, and statistical modeling.
3) Enhanced Healthcare Systems
It would be great to know that AI and machine learning have made a huge impact on the healthcare industry. In recent times, machine learning is rapidly taking over all domains in the healthcare industry. These domains of utility were machine learning algorithms that are very prominent including robotic surgery, telemedicine, remote monitoring, etc. These ML-based softwares are a huge benefit to the doctors as they reduce the dependency on the doctor by a significant amount.
Here are some interesting ML based techniques that have taken over the healthcare industry with a storm:
- Pattern Image analytics
- Robotic Surgery
- Identifying diseases and diagnostics
- Personalized treatment
- Clinical trial research
- Personalized treatment and behavioral modification
- Epidemic outbreaks prediction
- Maintenance of healthcare records
- Manufacturing drugs after their discovery
4) Prepare A Neural Network Which Can Read And Understand Handwritten Material
Handwriting analysis is a crucial tool in the crime investigation department. This can be made successfully, thanks to technological marvels such as neural networks and deep learning. Next time you plan to develop software that can read handwriting, you can refer to MNIST Handwritten Digit Classification Challenge as it provides its users with a beginner level and easy user interface. MNSIT dataset is used worldwide to train machines for handwritten digit recognition.
5) Object Detection
Object detection is among the most intriguing ML projects that one can make. Deep Neural Networks (DNN), is popularly used for image classification. Object detection models have the capability of detecting the object, classifying it and then recognizing the object shown in the scale. Object detection problems are detected in bounding box masks.
Despite this comprehensive guide to ML projects, a lot more interesting projects remain unnamed yet. It is only the beginning of machine learning as the developers have a lot of exciting things in store giving us the opportunity to contribute in this field of work. The best way to kick-start with your machine learning journey is by starting with making your own personal hands on projects.
In this modern world, along with artificial intelligence, another term which goes hand in hand is machine learning. Machine learning is implemented for bringing out the power in an exciting way. Most engineers find ML to be complex because of its excessive involvement with computational tasks. So, we bring you a list of the most important machine learning libraries every ML enthusiast must know of in order to kick-start their ML journey.