Data Science Archives - Page 2 of 4 - Tutorial Rays

Data Science

Tutorial Rays Interview Questions and Answers Python Data Science
Model Deployment
  • December 30, 2025
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Model Deployment Chapter 4 – Cloud Platforms for ML | AWS, GCP and Azure Overview

<div class=”bloc-syllabus”> <h2>Cloud Platforms Overview for Model Deployment (AWS, GCP, Azure)</h2> <p class=”blog_p”> Modern machine learning systems rarely run on local machines in production. Instead, they are deployed on cloud.

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Model Deployment
  • December 30, 2025
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Model Deployment Chapter 3 – Introduction to Docker for ML Deployment

Introduction to Docker for Model Deployment When machine learning models move from development to production, differences in environments often cause deployment failures. Docker solves this problem by packaging applications, dependencies,.

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Big Data
  • December 30, 2025
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Big Data Chapter 6 – NoSQL Databases | MongoDB and Cassandra Explained

NoSQL Databases in Big Data (MongoDB and Cassandra) Traditional relational databases struggle with scalability, flexibility, and performance when handling massive volumes of unstructured and semi-structured data. NoSQL databases were designed.

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Big Data
  • December 30, 2025
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Big Data Chapter 5 – Working with Streaming Data | Spark Streaming Basics

Working with Streaming Data in Big Data In many real-world applications, data is not generated in batches but arrives continuously in real time. Examples include sensor data, financial transactions, social.

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Big Data
  • December 30, 2025
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Big Data Chapter 4 – Spark SQL and DataFrames | Structured Data Processing

Spark SQL and DataFrames While RDDs give low-level control, most real-world Big Data applications work with structured or semi-structured data. Spark SQL and DataFrames provide a high-level, optimized, and user-friendly.

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Big Data
  • December 30, 2025
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Big Data Chapter 3 – Apache Spark Basics | Fast Distributed Data Processing

Apache Spark Basics Apache Spark is a powerful, open-source Big Data processing framework designed for fast, in-memory computation. Unlike MapReduce, Spark processes data in memory, making it significantly faster for.

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Big Data
  • December 30, 2025
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Big Data Chapter 2 – HDFS and MapReduce | Distributed Storage and Processing

HDFS and MapReduce in Big Data HDFS and MapReduce are the two core pillars of the Hadoop framework. HDFS handles the storage of massive datasets, while MapReduce processes those datasets.

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Numpy Python
  • April 21, 2025
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📘 Chapter 3: Array Dimensions and Attributes in NumPy – Know Your Data Inside Out

🧠 “If data is the new oil, then knowing your array’s dimensions is like knowing where your oil rigs are.” Welcome to Chapter 3 of our NumPy journey! By now,.

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Pandas
  • April 12, 2025
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10.3. Real-World Projects: Automating Data Tasks with Python and Pandas

Great! Here’s the next blog post for “11. Real-World Projects: Automating Data Tasks”, focused on automating common data processes using Python and Pandas. It includes practical examples, explanations, a summary,.

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Pandas
  • April 12, 2025
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11.Real-World Projects: Analyzing Sales Data with Pandas

Real-World Projects: Analyzing Sales Data with Pandas Real-world projects are the best way to learn data analysis. In this blog, we’ll walk through a practical project: analyzing sales data using.

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