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Food delivery supported through advanced applications has emerged as one of the fastest growing developments in the e-commerce space. We all love to order online, one thing that we don't like to experience is variable pricing for delivery charges. Delivery charges highly depend on the availability of riders in your area, demand of orders in your area, and distance covered. Due to driver unavailability, there is a surge in delivery pricing and many customers drop off resulting in loss to the company.
To tackle such issues if we track the number of hours a particular delivery executive is active, we can efficiently allocate certain drivers to a particular area depending on demand.
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.
Learn to design Hadoop Architecture and understand how to store data using data acquisition tools in Hadoop.
In this deep learning project, you will build your own face recognition system in Python using OpenCV and FaceNet by extracting features from an image of a person's face.
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.
Use the RACE dataset to extract a dominant topic from each document and perform LDA topic modeling in python.
Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.
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 Databricks Azure tutorial project, you will use Spark Sql to analyse the movielens dataset to provide movie recommendations. As part of this you will deploy Azure data factory, data pipelines and visualise the analysis.
In this deep learning project, you will learn how to build your custom OCR (optical character recognition) from scratch by using Google Tesseract and YOLO to read the text from any images.