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In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
Use the Zillow dataset to follow a test-driven approach and build a regression machine learning model to predict the price of the house based on other variables.
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
Music Recommendation Project using Machine Learning - Use the KKBox dataset to predict the chances of a user listening to a song again after their very first noticeable listening event.
In this ML Project, you will use the Avocado dataset to build a machine learning model to predict the average price of avocado which is continuous in nature based on region and varieties of avocado.
Use the Mercari Dataset with dynamic pricing to build a price recommendation algorithm using machine learning in Python to automatically suggest the right product prices.
In this deep learning project, you will build a convolutional neural network using MNIST dataset for handwritten digit recognition.
In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.
In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.
In this machine learning project, we will build a predictive model to find out the sales of each product at a particular store.
In this data science project, we will look at few examples where we can apply various time series forecasting techniques.
In this project, we will automate the loan eligibility process (real-time) based on customer details while filling the online application form.
In this data science project, we will predict internal failures of Bosch using thousands of measurements and tests made for each component along the assembly line.
In this data science project with Python, we will complete the analysis of what sorts of people were likely to survive.You will learn to use various machine learning tools to predict which passengers survived the tragedy.
In this machine learning project, you will build a model to predict the purchase amount of customer against various products which will help the company create personalized offer for customers against different products.
In this data science project, we will predict the number of inquiries a new listing receives based on the listing's creation date and other features.
In this project, we will build a model to predict the purchase amount of customers against various products which will help a retail company to create personalized offer for customers against different products.
In this machine learning project, we will implement Back-propagation Algorithm from scratch for classification problems.
In this project, we are going to predict how capable each applicant is repaying a loan.
In this project, we are going to predict different qualities of wine using different ML models.
Machine learning is among the most in-demand and exciting careers today. With the increasing demand for machine learning professionals and lack of skills, it is crucial to have the right exposure, relevant skills and academic background to make the most out of these rewarding opportunities. ProjectPro’s Machine Learning Projects help candidates make this transition to highly rewarding careers in Data Science and Machine Learning.
Exhausted by applying for machine learning jobs and not being shortlisted? One of the key benefits of working on ProjectPro’s machine learning project ideas is that you learn skills as you build and apply new concepts in every project.
You will not regret working on any of these machine learning project suggestions. See what you'll learn -
If you are a beginner in Data Science, then you can choose from the following list of machine learning projects with source code in Python. These basic machine learning projects for beginners in Python have been designed by ProjectPro experts to motivate their interest further.