PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
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.
Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.
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 data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.
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.
CRNNs combine both convolutional and recurrent architectures and is widely used in text detection and optical character recognition (OCR). In this project, we are going to use a CRNN architecture to detect text in sample images. The data we are going to use is TRSynth100k from Kaggle. Given an image containing some text, the goal here is to correctly identify the text using the CRNN architecture. We are going to train the model end-to-end from scratch.
In this deep learning project, you will learn to implement Unet++ models for medical image segmentation to detect and classify colorectal polyps.
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.