date_rangeMay 26, 2020
Machine Learning (ML) is an innovative and lucrative technology to pursue a career in. With an increase in its applications across sectors like entertainment, healthcare, tourism, etc. it has been gaining a lot of popularity. If you aspire to learn ML and start a career in it, then working on some projects will not just improve your understanding of the subject concepts, but it will also be a valuable addition to your resume. In this article, let’s look at some exciting ML projects. We will also briefly discuss the skills you need for ML.
Fake news is a big problem that has been affecting the society. Easy access to the internet, mobile phones, and social media have increased the circulation of fake news. Fake news not just creates unnecessary panic and worry among masses, but it can also cause serious issues.
Machine Learning (primarily Natural Language Processing NLP and Deep Learning algorithms) can be used to detect fake news, and this is an exciting project to consider.
Machine Learning can be used to see if a person is eligible for a loan, and if so, what loan amount can he take. Research, based on data like a person’s job, salary, gender, age, location, number of dependents, etc. can help in calculating his loan. ML algorithms like Random Forest, Logistic Regression, and Decision Tree can be used to solve this supervised classification problem. This is another good project idea.
Video streaming apps and sites have become very popular these days. With more and more people preferring to watch movies at their convenient time and place, OTT platforms have become famous. Rising movie ticket and snack costs, busy schedules of people, traffic, and commute related issues have also contributed to making people move to OTT platforms.
Machine Learning can help recommend movies and series to us based on our past movie history as well as based on our interests. It does so by carefully studying data. Movie Recommendation can be a fun and exciting project idea.
Sentiment Analysis is the study of whether the expression of the subject is positive, negative, or neutral. It is used to understand the underlying emotion behind a comment or a statement. For example, the comment “I like the color of your bag” is positive.
Sentiment Analyzer makes use of supervised learning algorithms like Naïve-Bayes, support vector machine, etc. It is widely used by businesses to study customer sentiment and behavior towards brands and products. They make business decisions based on the results.
Sentiment Analyser is an exciting project idea.
Gone are the days when people listen to cassettes and CDs. This is the time of music apps and live streaming music. Music streaming apps and sites show us recommendations and create playlists based on our previous music history. Machine Learning algorithms create recommendations. Deep Learning and Deep Neural Networks are used for music recommendation.
Music Recommendation is another excellent ML project idea.
Some of the skills that could help you in the field of Machine Learning are:
Machine Learning consists of a lot of algorithms. To understand them, create them, and work with them, a good understanding of certain Mathematical concepts helps. Concepts like Calculus, Probability, Linear Algebra, and Numerical Analysis are essential.
Statistics have a significant role in understanding and applying ML concepts. Descriptive Statistics (the method of summarizing and organizing data in a dataset) and Gaussian distribution, Variable Correlation, Hypothesis Tests, Estimation Stats, Non-parametric statistics are some of the concepts needed.
ML makes use of a lot of algorithms like Naïve-Bayes, K-Nearest Neighbors, CART, Logistic Regression, etc. A comfort with algorithms is essential, and so is the ability to create new ML algorithms.
Machine Learning algorithms need a lot of data. One of the main processes in Machine Learning is the analysis of random, unprocessed data from different sources. Understanding of data modeling, data processing techniques, data cleaning methods, and DBMS are needed in ML.
The knowledge of programming languages like Python, R, and C++ is useful in ML. The implementation of algorithms and other processes is done using programming languages. Python is widely used since it has a lot of supportive libraries that make the tasks easier. Python is very easy and versatile and has considerable community support. Machine Learning also used languages like R and C++.
It is always a great idea to work on projects if you plan to work in Machine Learning. With so many ideas around, you have a lot of choices. Projects help you gain a good understanding of concepts, improve your analytical thinking abilities, and enhances your problem-solving skills. You can start with simple ML projects and, with time, move to more complex and intermediate-difficulty ones. The more you practice, the more your knowledge will improve.
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