Working on machine learning projects can make you an expert in machine learning. As a beginner, you only work on projects that are very common in the data science community. But if you want to become an expert, you have to work on advanced machine learning projects. So if you are looking for advanced machine learning projects, this article is for you. In this article, I will introduce you to advanced machine learning projects solved and explained using Python.
Advanced Machine Learning Projects
Facebook Posts Sentiment Analysis:
Facebook is a great platform to share your life, your opinions and even do business promotions. As a Facebook user, you must have shared a lot of posts so far so that you don’t get better data than a dataset about your Facebook posts to create an advanced machine learning project.
So you can download your Facebook data and perform sentiment analysis on it. It will help you analyze the sentiments of a real-world dataset and in the end, it will help you show an amazing project on your resume. You can find this advanced machine learning project solved and explained using Python from here.
Gender detection is another great problem for working on an advanced machine learning project. If you are looking for a data science job at a company that is heavily involved in building computer vision applications, this project is for you. It will help you learn how to detect a person’s gender and at the same time, such kind of advanced machine learning projects can boost your resume.
We can detect the gender of a human using both male and female facial appearance samples. There are many libraries and frameworks that you can use for this task. You can find this advanced machine learning project solved and explained using Python from here.
Spotify Recommendation System:
Spotify is one of those applications that use the scikit-learn library in Python on their platform. Yes, Spotify uses the scikit-learn library to recommend music and podcasts to its users. So you can also train a machine learning model to recommend songs like Spotify.
You can use any clustering technique to create such a recommendation system. Scikit-learn provides all the clustering algorithms you can use to create this advanced machine learning project. You can also use natural language processing techniques for this task. You can find this advanced machine learning project solved and explained using Python from here.
End to End Machine Learning Project:
As a data scientist, you should add at least four advanced machine learning projects to your resume. But out of all the projects you do, at least one should be an end-to-end machine learning project. It helps you show that you know how a machine learning model can be prepared and used to add value to an organization.
There are many methods you can use to build an end-to-end application for your model. In this project, you will learn how to build an end-to-end application for your model using the streamlit library in Python. You can find this advanced machine learning project solved and explained using Python from here.
So these were some of the machine learning projects that you should try to become a machine learning expert. As a beginner, you only work on projects that are very common in the data science community. But if you want to become an expert, you have to work on advanced machine learning projects. Hope you liked this article on advanced Machine Learning Projects solved and explained using Python. Please feel free to ask your valuable questions in the comments section below.