Machine Learning Projects for Resume

5 Best Machine Learning Projects for Resume Solved and Explained with Python

With the growth in the use of artificial intelligence in enterprises, the demand for machine learning skills has increased a lot in every organization. In such a competition, your resume should contain machine learning projects that show most of your skills. In this article, I will introduce you to the 5 best machine learning projects for your resume.

Machine Learning Projects for Resume

All machine learning projects mentioned below are solved and explained using the Python programming language. Here, I will introduce you to the 5 best machine learning projects for resume where each of the projects will fall into 5 different types of categories, as mentioned below:

  1. Computer Vision
  2. Recommendation System
  3. Future Prediction
  4. Natural Language Processing
  5. Image Recognition

Let’s go through all machine learning projects for resume based on the categories mentioned above.

Computer Vision: Face Mask Detection

Indoor places, such as restaurants and grocery stores, are legally required to have rules in place for the mandatory use of face masks. Having a worker manually examining each person to make sure their mask is on simply defeats the goal of limiting contact with people as much as possible. So, a real-time face mask detection system can be used to address this issue that will not only maximize efficiency but will also ensure to potentially save lives.

The technology behind the real-time face mask detection system is not new. In Machine Learning, face mask detection is the problem of computer vision. Too often we see computer vision applications of this technology in our daily lives. A common example is a face unlocking in smartphones.

The goal of a face mask detection system is to create an image recognition system that understands how image classification works, and it should work with great accuracy so that our model can be applied in the realtime situations. It will work by recognizing the boundaries of the face and predicting whether or not you are wearing a face mask in real-time.

Recommendation system: Fashion Recommendation System

A recommendation system is a system that is programmed to predict future preferable items from a large set of collections. A recommendation system works either by using user preferences or by using the items most preferred by all users. The main challenge in building a fashion recommendation system is that it is a very dynamic industry. It changes very often when it comes to seasons, festivals, pandemic conditions like coronavirus and many more.

Unlike other areas, fashion recommendations shouldn’t be based solely on personal taste and past activity of the customer. There are many external factors (many of which are emotional) that make creating a fashion recommendation system all the more complex. Public perceptions must be taken into account, as well as fashion rules, dress rules and current trends.

Future Prediction: Rainfall Prediction

Rainfall Prediction is one of the difficult and uncertain tasks that have a significant impact on human society. Timely and accurate forecasting can proactively help reduce human and financial loss. 

This project presents a set of experiments that involve the use of common machine learning techniques to create models that can predict whether it will rain tomorrow or not based on the weather data for that day in major cities in Australia.

NLP: Named Entity Recognition

Named entities generally mean the semantic identification of people, organizations, and certain numeric expressions such as date, time, and quantities. The concept of named entities was introduced in the applications of natural language processing.

The NER plays a very important role in information extraction tasks such as identifying relationships and producing scenario models. Some other applications where the NER is used are semantic annotations and opinion mining.

Image Recognition: Google Landmark Detection Model

Have you ever looked through your vacation photos and wondered: what is the name of this temple I visited in India? Who created this monument that I saw in California? Landmark Detection can help us detect the names of these places. 

Landmark Detection is a task of detecting popular man-made sculptures, structures, and monuments within an image. We already have a very famous application for such tasks which is popularly known as the Google Landmark Detection, which is used by Google Maps.

Also, Read – 100+ Machine Learning Projects Solved and Explained.

So these were the 5 best machine learning projects for a resume that will help you to show most of your skills. I hope you liked this article on the best Machine Learning projects for resume. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
Articles: 1050

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