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Model Deployment

Model Deployment Chapter 2 – Building REST APIs for ML | Flask and FastAPI

Building REST APIs for Machine Learning Using Flask and FastAPI Once a machine learning model is trained and serialized, it must be exposed to users or applications for predictions. The.

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Model Deployment

Model Deployment Chapter 1 – Model Serialization for ML | Pickle and Joblib

Model Serialization in Machine Learning (Pickle and Joblib) After training a machine learning or deep learning model, the next crucial step is saving the model so it can be reused.

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Big Data

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

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

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

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

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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Big Data

Big Data Chapter 1 – Introduction to Big Data and Hadoop Ecosystem

Introduction to Big Data and Hadoop Ecosystem In today’s digital world, massive amounts of data are generated every second from social media, sensors, mobile devices, transactions, and online platforms. Traditional.

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NLP

NLP Chapter 7 – Introduction to Transformers and BERT | Modern NLP Models

Introduction to Transformers and BERT in Natural Language Processing Traditional NLP models such as RNNs and LSTMs struggle with long-range dependencies and parallel processing. Transformers revolutionized NLP by enabling models.

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NLP

NLP Chapter 6 – Topic Modeling in NLP | LDA and Topic Extraction Techniques

Topic Modeling in Natural Language Processing Topic modeling is an unsupervised learning technique used to automatically discover hidden themes or topics within a large collection of text documents. Unlike text.

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