A Quick Guide to The Most Popular Machine Learning Projects of the Era!
Projects are the cornerstone of completing proper industrial training. While completing any tech-based course, you should get involved with a few projects that will set you apart from the crowd.
If you have just finished your machine learning courses and looking for the best project ideas to imply, this blog post is for you.
Machine learning is changing the way people think about the new industrial revolution. With the help of such technology, we can easily manage massive amount of data and efficiently automate several tasks that formerly required a lot of human labor to execute.
What is Machine learning?
Machine learning, in a nutshell, is a way by which any computer or machine can compute any data without being explicitly programmed. It is one of the subsets of artificial intelligence technology that learns from data, identifies patterns, and makes predictions without the involvement of humans. Machine learning is constantly impacting and transforming several variables in real-time.
Here are a few machine learning projects that can be utilized to demonstrate how machine learning is playing an important role in today's scenario: -
1. Machine learning project for human activity identification utilizing data sets from smartphones:-
Human activity recognition (HAR) is one of the most exciting and eye-catchy machine learning projects that utilize the basic understanding of deep learning algorithms.
In such a project, you will be involved in developing a highly reliable HAR system. This can be used through a smart device, primarily a smartphone. Here, for ease of use, we'll employ an accelerometer sensor to manage time series data in a three-dimensional system.
The researchers in this project primarily focus on intelligent smartphone sensors in order to utilize a variety of ML classification algorithms. Aside from the sensor, the smartphone-compatible wearable device also plays an important role here. All this algorithm works in six categories:-
Walking up the stairs
Walking Down the stairs
Standing
Walking
Laying
Sitting
Uses:-
HAR conduct aids in the identification of emotions.
It also facilitates a person's access to their physiological state.
Additionally, continuous monitoring allows us to get day-to-day general health advice.
Tools:-
Deep learning, Supervised machine learning, Python (Pandas)
2. Machine Learning Project for Coupon Purchase Prediction
As the pandemic spread, many stores moved their operations online. The most obvious reason behind this was customers tended to buy stuff without stepping out of their homes.
Customers are now looking for excellent bargains and discounts while purchasing things online. As a result, there has been a significant increase in the number of people searching for extra discounts online. Seeing this as an opportunity, numerous websites have specialized their technologies in creating coupons for their customers.
Using the progress of this machine learning project, we can assess previous client shopping behaviors. With such prior consumer behavior, we can create better predictions about which coupons a client is likely to purchase in the future.
As the evaluation progresses, we will gain a thorough understanding of charting, data visualization, and feature engineering.
Uses:-
Better access to product-based coupons.
Sorting of coupons depending upon the need of the consumer.
Tools:-
TensorFlow, Scikit learn, Pytorch
3. Machine learning project/algorithm for analysis churn prediction:-
Adding a new customer is critical for any business looking to increase overall income and establish new long-term relationships. However, acquiring a new customer is more expensive than retaining an existing one.
Customer churn is one of the most difficult problems that all businesses and organizations confront around the world since it occurs when customers or subscribers discontinue utilizing their services. This project will assist you in obtaining a better prediction of customer churn and retaining clients.
When it becomes difficult to identify clients who are likely to leave, we need quick and accurate data to retain them. If we calculate the number of consumers in the world, it is just impossible for the human brain to process all of the data and produce a churn estimate.
When the machine learning algorithm comes into play, it assists in making a better churn prediction with all of the potential solutions. Machine learning algorithms play an important role in improving churn management because they have a strong emphasis on predicting behavior patterns that use deep learning techniques.
Uses:-
Assist in the administration of an organization's resources.
Getting a firm grip on the customer and tailoring services to their specific requirements.
Tools/algorithms:-
Decision tree, Linear regression, Random Forest
4. Using an ML model to transform a real-life image into an animated cartoon:-
Machine learning is used in image cartooning systems as a terrific approach to modifying and incorporating real-world photos into animated cartoons. We can accomplish this primarily by using the machine learning process to convert a notion into an expression that is fully extensible.
This machine learning project will undoubtedly move you one step closer to computer vision and deep learning. You can make your own emojis out of your own images by employing a GAN framework. By creating a Python model with OpenCV, you can cartoonize an idea. This is too useful if you're searching for a less complicated approach. This Python model with OpenCV is crucial to creating original cartoons and adding an additional dimension of finesse and originality to photographs.
Uses:-
It may be used to create emojis from actual photos.
This technique helps in creating filters for numerous platforms such as Facebook, Instagram, and Snapchat.
Tools:-
Imageio, easygui, Numpy, Matplotlib, OpenCV
5. Music recommendation system using machine learning algorithms:-
Today's age is well-versed with online streaming platforms such as Spotify, Netflix, wynk, and many others. All of these sites seek to use recommender system techniques. Machine learning technology used by sites like this offer similar products or content that you might be interested in based on your previous activity.
For example, you will receive preferences for the same genre of music that you frequently listen to.
One of the best and greatest examples of how the use of machine learning algorithms may help improve user experience is the recommendation system. In this project, you will gain a basic understanding of how to tailor the recommendation system and use it to understand the user's preferences better. This can save many platforms time when storing and optimizing content for their clients.
The two primary methods for developing a recommender system are:-
Collaborative filtering:- Collaborative filtering is a type of social filtering based on personalized recommendations for users with similar interests.
Content-based filtering:- Content-based filtering uses products, services, and content features to gain and generate the recommendation based on collected information.
Uses:-
Getting a better insight into customers' preferences and choices.
Making song searches and selections easy for the users utilizing the recommender system.
Tools:-
CNNs, NLP, SVM, python (LensKit)
Summing up:-
To summarize, we can easily imply the fact that machine learning projects are essential in understanding various machine learning tools and algorithms. All of these machine-learning efforts are aimed at providing automated decisions that were previously impractical or time-consuming for humans.
If you want to learn more on machine learning-related topics, you can check out Artificial Intelligence and Machine Learning Advance Program, and do follow us on Facebook, YouTube, and Linkedin for regular updates on such interesting topics.
