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A notebook is a code execution environment that allows for creating, sharing code and its execution, visualization and other text information (like markups). It enables an interactive computing in the area of data exploration or analysis. It is logical to a sharable Grunt shell for Pig, or scala shell and PySpark shell for Spark, or beeline for Hive but with visualization, discovery and collaboration.
In this big data Project, we will talk about one of this notebook - Apache Zeppelin. With Zeppelin, we will do a number of data analysis by answering some questions on the crime dataset using Hive, Spark and Pig. We will prepare some chart to better represent our results and finally share our results with the collaborative or sharing feature of the notebook.
On completing this big data project using zeppelin, participants will have known what Zeppelin is, gained the ability to install new interpreters, use Zeppelin for performing data analysis, sharing results with their friends or colleagues. Also, the participant will be informed of other notebooks in the data ecosystem like Jupyter or the databricks cloud notebooks.
Use the RACE dataset to extract a dominant topic from each document and perform LDA topic modeling in python.
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 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 time series project, you will forecast Walmart sales over time using the powerful, fast, and flexible time series forecasting library Greykite that helps automate time series problems.
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.
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.
Learn to design Hadoop Architecture and understand how to store data using data acquisition tools in Hadoop.
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 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.
In this PySpark project, you will simulate a complex real-world data pipeline based on messaging. This project is deployed using the following tech stack - NiFi, PySpark, Hive, HDFS, Kafka, Airflow, Tableau and AWS QuickSight.