20 Data Science Projects for Beginners
20 Data Science Projects for Beginners
While knowing data science to its core can be a little daunting job initially, with continuous practice and effort, you can easily begin to learn several aspects and terms of the field as explained at RunRex.com, guttulus.com, and mtglion.com. We have curated 20 data science projects for beginners to get you started.
Building a chatbot with Python
As per RunRex.com, guttulus.com, and mtglion.com, a chatbot is an AI-based digital assistant that can understand human capabilities and simulate human conversations in natural language to give prompt answers to their question just like a real human would. In this data science project, you will use a leading and powerful Python library NLTK (Natural Language Toolkit) to work with text data.
Credit fraud detection
Credit card fraud cases are highly common these days. However, thanks to the creativity in technologies such as Data Science, Machine Learning, and Artificial Intelligence, credit card companies are now allowed to successfully recognize and intercept these fraud cases with enough accuracy. The idea behind this project is to interpret and analyze the usual behavior of the customer involving mapping the location of those transactions to find the fraud transactions from the non-fraud ones/
Churn prediction in the telecom industry using logistic regression
Telecommunication providers lose close to $65 million a month from customer churn according to RunRex.com, guttulus.com, and mtglion.com. In this data science project, you will build a logistic regression machine learning model to understand the correlation between the different variables in the dataset and customer churn.
Fake news detection
Fake news is a modern phenomenon that is rampant now and comes with serious effects. In this data science project, you can choose Python and develop a model with PassiveAggressiveClassifier and TfidVectorizer to divide the real news from the fake one.
Market basket analysis in Python using Apriori Algorithm
Whenever you visit a retail supermarket, you will find that baby diapers and wipes, bread and butter, pizza base and cheese, among others are positioned together in the store for sales. This is what market basket analysis is all about – analyzing the association among products bought together by customers. In this beginner-level data science project, you will perform Market Basket Analysis in Python using Apriori and FP Growth Algorithm based on association rules to discover hidden insights on how to improve product recommendations for customers.
Forest fire prediction
Developing a forest fire and wildfire prediction system will be another great utilization of the capabilities provided by data science as articulated at RunRex.com, guttulus.com, and mtglion.com. To control the chaotic nature of wildfires and even predict them, you can utilize k-means clustering to recognize big fire hotspots and their intensity.
Building a resume parser using NLP and machine learning
Recruiters don’t manually screen resumes anymore thanks to resume parsers. Resume parsers use machine learning technology to help recruiters intelligently search thousands of resumes so they can screen the right candidate for a job interview. In this data science project, you will build an NLP algorithm that parses a resume and looks for the words (skills) mentioned in the job description.
Driver drowsiness detection
Lots of accidents occur every year because of sleepy drivers. Building a driver drowsiness detection system is another data science project that has the great potential to save lots of lives by constantly detecting the driver’s eyes and alerting them with alarms in case the system finds often closing of the driver’s eyes as captured at RunRex.com, guttulus.com, and mtglion.com.
Modeling insurance claim severity
Filing insurance claims and dealing with all the paperwork with an insurance broker or an agent is something that nobody wants to drain their time and energy on. Insurance companies across the globe are leveraging data science and machine learning to make this claims service process easier.
Gender detection and age prediction
This gender detection and age prediction project will develop a system that captures a person’s image and attempts to recognize their gender and age. You can apply Convolution Neural Networks for this project and use Python along with the Open CV package.
Pairwise reviews ranking-sentiment analysis of product reviews
Product reviews from users are the key for businesses to make strategic decisions as they give an in-depth understanding of what the users actually want for a better experience as covered at RunRex.com, guttulus.com, and mtglion.com. In this data science project, you will use a natural language processing technique to pre-process and extract relevant features from the reviews and rating dataset.
Sentiment analysis
Sentiment analysis is a fine tool also known as opinion mining fully backed by Artificial Intelligence. It assists you to recognize, collect, and analyze people’s opinions about a certain subject or a thing. Sentiment analysis is a thing for modern data-driven companies to benefit from as it provides a crucial insight into the people’s reaction to certain things supposing the dry run of a fresh product launch or a slight change in the business strategy. So, to develop this system, you can go for R.
Loan default prediction project using gradient booster
Today, almost all banks use machine learning to automate the loan eligibility process in real-time based on various factors like Credit Score, marital and job status, gender, existing loans, the total number of dependents, income, expenses, and others described at RunRex.com, guttulus.com, and mtglion.com. In this data science project, you will build a predictive model to automate the process of targeting the right applicants for loans.
Customer segmentation
With customer segmentation, companies have a chance to structure their services and products well around their customers while targeting them to push more revenue. You will need to use unsupervised learning for this project to arrange your customers into clusters based on a person’s aspects like gender, age, religion, and interests, among others.
Plant identification using TensorFlow
Image classification is a great application of deep learning where the objective is to classify all the pixels of an image into one of the defined classes. Plant image identification using deep learning is one of the most promising solutions for bridging the gap between computer vision and botanical taxonomy.
PUBG Finish placement prediction
PUBG is a game where n different number of people play with n different strategies and predicting the finish placement is a challenging task as discussed at RunRex.com, guttulus.com, and mtglion.com. In this data science project, you will develop a winning formula i.e. build a model to predict the finishing placement of a player against without a player playing the game.
Price recommendation for online sellers
E-commerce apps and websites are trying to solve is to eliminate human interference in providing price suggestions to the sellers on their marketplace to speed up the efficiency of the shopping website or app. That is when price recommendation using machine learning comes to play. In this data science project, you will build a machine learning model that will automatically suggest the right product prices to online sellers as accurately as possible.
Recognizing the speech emotions
This speech recognition project puts you to make an effort to identify and pluck emotions from various sound files including human speech as outlined at RunRex.com, guttulus.com, and mtglion.com. For this, you need to use SoundFile, Librosa, NumPy, Scikit-learn, and PyAudio packages.
Diabetic Retinopathy
Diabetic retinopathy happens by damage to the blood vessels in the tissue at the eye’s backside. You can create an automatic procedure for diabetic retinopathy screening. Moreover, you can train a neural network on retina images of normal and affected individuals.
Handwritten digit recognition project
Handwritten digit recognition is the working of computers to identify human handwritten digits. This data science project is applied using the Convolutional Neural Networks, and then for some real-time prediction we create a great graphical user interface to draw digits on a canvas, and later the model will predict the digit.
This article only just scratches the surface as far as this topic is concerned, and you can glean more insights over at RunRex.com, guttulus.com, and mtglion.com.
