Data Science involves cleaning raw data and deriving some sort of conclusion from it. While Machine Learning does involve Data Analysis in the first step, the thing to note here is that while data science is a part of all machine learning projects, it is an entity on its own as well.
What are some of the Best Data Science & Machine Learning Projects?
Data science deals with statistics, mathematics, and computer programming to extract information from any given data. It is called Exploratory Data Analysis. Data analysis is the fundamental building block of machine learning.
One of the most important skills for a Data Science career is to understand Python. One has to learn to code in Python since Python has been the top language for analytics experts in the recent past, with 66% of Data Scientists reporting that they use it regularly.
This list is an honest attempt to cover both Data Science and Machine Learning Projects. So read along!
- Every application requires a recommender system to recommend products to a customer based on their preferences and bring value to them.
- With such a wide application range, you are in for a few questions if it is not there in your resume or portfolio.
- That is the very reason why it finds its place in every other resume these days. So, you must make it different to stand out from the crowd.
- For example, a movie recommendation system where you have a simple list of movies from every genre, to begin with. With every click on a particular movie, you get a list of 5-10 similar movies.
- Now, that is pretty simple. To make it stand out, you can integrate an API from IMDB, and populate all the information regarding the movie.
EDA Project involving Country Dataset from Kaggle
- This particular project falls purely under Data Analysis.
- It is also recommended to show the interviewer that you are good at Data Cleaning and Preprocessing as well.
- The age-old Titanic dataset has now begun to annoy most of the interviewers.
- I would recommend you to use Country Statistics- UNData from Kaggle.
- You can make an Exploratory Data Analysis using some core metrics like surface area, population, GDP of the country, etc.
- You can also make a web application and display the metrics in proper graphs to score a few brownie points because graphs are a key aspect of Data Science.
- It is important to know which graph to use based on the kind of data you are plotting.
Commodity Price Predictor
- It is a regression-based project where you can enter the details of the commodity and the model will give you the ideal price of the commodity.
- For example, you can enter the specifications of a laptop and the predictor will give you the ideal price.
- Similarly, you can also build a car price predictor for those who want to sell their used cars which are being employed in many businesses as well.
- You can take in the brand, year of purchase, fuel type, and the kilometres are driven recession model would predict the price it could fetch you.
- You have to do a bit of web scraping or use a third-party API to get the data of the different commodities.
New York City Taxi Trip Regression Model
- This dataset is in the form of an SQLite database on Kaggle. So you’d have to first convert it into a Pandas data frame to work on it.
- The dataset is around 12 GB in size.
- It certainly gives you an edge over your competitors if you can handle such huge datasets.
- You can use the dataset to build a regression model to predict the trip ending time based on the day, trip start time, distance, etc.
- The challenging part of the project is that you have to bring the dataset to work on either by creating a data warehouse or by converting it into a Pandas data frame.
- The other challenging aspect is the scale of the dataset.
Time Series Prediction of Covid Cases
- This kind of project is very important because there are a lot of real-world datasets that vary with time like cryptocurrency price, the number of covid cases, etc.
- You should build a project that would predict the number of covid cases in the future with the peak time as well.
- A resume without a time series project can adversely affect your candidature. You must consider the recent advancements when doing a project. For example, LSTMs are in huge demand these days.
- In addition to that, you can also do a project on some APIs like Azure Time Series Insights API or the Timeseries Insights API from the Google Cloud Platform.
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A Deep Learning-Based Project
- It is highly recommended that you include a Deep Learning-based project because it shows that you don’t shy away from trying a new trend.
- An apt example of such a project in recent times could be a face mask detector.
- The other option could be a pose detector which falls under Computer Vision.
- You can make a project which could map the facial features and the skeleton of the person in front of the camera.
- This project could find its use in places like online proctoring for exams, especially in recent times.
- It could also be used at Gyms and Yoga Classes where it could detect if a person performing an exercise is doing it correctly or not.
An Expense Tracker
- Last but not the least, what better way to show that data science and machine learning are always on your mind than to do a project that you relate to.
- You can make a machine learning model to train on your expenses and income dataset that you could very easily get from your bank.
- The model could give you a few insights like your spending pattern based on the day of the week it is and the articles you are most likely to spend your most money on.
- You could show that you started managing your finances better after coming up with the model.
On an ending note, the projects that you choose to build should show a wide variety of traits you can exhibit. Some should show the high level of expertise required to accomplish the task. Some should show that even though a particular topic has been explored to the core, you can drive it up a notch. Your focus should be to have a hint of everything on your resume. To learn Python, you can use websites like python for beginners.
Disclosure of Material Connection: Some of the links in the post above are “affiliate links.” This means if you click on the link and purchase the item, I will receive an affiliate commission. Regardless, I only recommend products or services I use personally and believe will add value to my readers.