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Human language is astoundingly complex and diverse. When we write, we often misspell or abbreviate words, or omit punctuation. There is a lot of unstructured data around us. Natural language processing helps computers communicate with humans in their own language and scales other language-related tasks. NLP makes it possible for computers to read text, interpret it, measure sentiment and determine which parts are important.
Understanding this will enable you to build the core component of any conversational chatbot. In this NLP application we will create the core engine of a chat bot. We will learn text classification using the techniques of natural language processing by using the nltk library.
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.
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 spark project, you will use the real-world production logs from NASA Kennedy Space Center WWW server in Florida to perform scalable log analytics with Apache Spark, Python, and Kafka.
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.
Learn to design Hadoop Architecture and understand how to store data using data acquisition tools in Hadoop.
Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.
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.
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.
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 machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.