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5 Machine Learning Projects to Implement as a Beginner
Introduction
Machine Learning is a diverse area with a wide range of applications in many domains. As far as we have an abundance of usable data and a problem to solve in a particular area, Machine Learning can do wonders. Machine Learning Projects can vary in terms of complexity from simple Regression tasks for predicting sales, and wine quality to complex tasks like Object Recognition, Autonomous Vehicles, and Reinforcement Learning.
However, for someone who is a beginner in Machine Learning, the discussed below 5 projects can be highly useful.
Predicting the Quality of Wine
For folks who are a beginner in Machine Learning, the Wine Quality dataset is a great resource to get started with predicting the quality of the wine. Today, most of us want only the best quality of wine either for business or consumption. Hence it is wise to use data with Machine learning to predict the quality. The Wine Quality Dataset contains features that help in predicting the quality of wine.
Forecasting Sales
In the retail sector, the quantity of sales is the major criterion determining the growth of the industry. More sales means more revenue and more growth. Thus most retail sectors like Walmart, and Puma extensively use forecasting to their purpose to predict sales in advance in the future. Beginners can get hold of open-sourced datasets from these major Ecommerce platforms and use them to predict sales in the future. Most of this data can be in time-series format.
Sentiment Analysis on Tweets
Twitter is a platform where users can express their feeling, views, and onions via tweets. The sentiment of the tweet conveys a lot about the mood of the user or organization posting the tweet. For example, there may be a series of tweets about the celebration of a particular festival where the mood is happy, and in another such tweet, it can be anger or hatred against someone or a particular community. Thus it makes complete sense to use Machine learning to process this data for our use and help determine the sentiment using Sentiment Analysis to prevent any unfavorable outcome like violence or riot. Beginners can use the Twitter Sentiment Analysis Dataset and use Natural Language Processing and Machine Learning to do Sentiment Analysis.
Recommending Movies
Today, most of the popular content streaming platforms like Netflix, Hulu, etc use Recommender Systems to appropriately recommend new shows and movies based on the interest and liking of the users. This is proved a boon to these industries as it has not only engaged old users to the platform but attracted new users. Recommendations make life easy for users as they don't have to individually search for shows of their liking or get anxious about missing out on popular content. This is a challenging task and beginners can take this project for some advance learning.
Image Recognition / Handwritten Digits
Everything we perceive through our eyes is visual and can be captured into images that are nothing but pixels or values from 0 to 255 denoting a value on the RGB scale. All the images contain valuable information and many times we need to store the information in digitized format. Here mostly deep learning and neural networks are used to capture the essential features from the images and then store them in other formats. The Handwritten Digit Dataset contains handwritten digits from 0 to 9. The task here is to process these images and recognize the appropriate image with the correct digit. This project is highly encouraging for beginners who want to set their foot on Deep Earning, Image Processing, and Neural networks.
Conclusion
There are innumerable projects that a beginner can get his hands dirty on to learn the basics of Machine Learning and Deep Learning. In this article, we have looked at the 5 most popular projects that beginners can work on to enhance their skills and gain experience in Machine Learning.
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