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.
Deep Learning Project to implement an Abstractive Text Summarizer using Google's Transformers-BART Model to generate news article headlines.
Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.
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.
In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.
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.
Given big data at taxi service (ride-hailing) i.e. OLA, you will learn multi-step time series forecasting and clustering with Mini-Batch K-means Algorithm on geospatial data to predict future ride requests for a particular region at a given time.
In this project, we will use time-series forecasting to predict the values of a sensor using multiple dependent variables. A variety of machine learning models are applied in this task of time series forecasting. We will see a comparison between the LSTM, ARIMA and Regression models. Classical forecasting methods like ARIMA are still popular and powerful but they lack the overall generalizability that memory-based models like LSTM offer. Every model has its own advantages and disadvantages and that will be discussed. The main objective of this article is to lead you through building a working LSTM model and it's different variants such as Vanilla, Stacked, Bidirectional, etc. There will be special focus on customized data preparation for LSTM.
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.