Engineering Course Materials
Under Graduate Courses
Convolutional Neural Networks (CNNs) are deep learning models designed to process grid-like data such as images by applying convolutional filters
Continue readingUNIT II -CONVOLUTIONAL NEUAL NETWORKS-16 MARKS WITH ANSWERS
Hadoop is an open-source framework used for processing and storing large-scale data across distributed systems. It includes HDFS for storage,
Continue readingBig Data Analytics-CSS334-ALL UNITS-2 Marks and 16 Marks
Hadoop uses various data formats and tools like Streaming and Pipes to analyze and scale data processing efficiently. It relies
Continue readingBig Data Analytics-CCS334/Unit V-Notes-HADOOP RELATED TOOLS
Autoencoders are neural networks that learn to compress and reconstruct input data, mainly used for dimensionality reduction and feature learning.
Continue readingUNIT 5- AUTOENCODERS AND GENERATIVE MODELS – SUBJECT NOTES
Hadoop processes large data using HDFS for distributed storage and supports tools like Hadoop Streaming and Pipes for scalability. It
Continue readingBig Data Analytics-CCS334/Unit IV-Notes-BASICS OF HADOOP
Model evaluation is the process of assessing how well a trained machine learning or deep learning model performs on unseen
Continue readingAD3501-DEEP LEARNING – UNIT 4- MODEL EVALUATION – SUBJECT NOTES
MapReduce is a programming model for processing large datasets using map and reduce functions, managed by YARN for resource scheduling.
Continue readingBid Data Analytics- CCS334/Unit III -Notes- MAP REDUCE APPLICATIONS
NoSQL databases offer flexible, scalable solutions for handling big data using models like key-value, document, and graph. Cassandra is a
Continue readingBig Data Analytics-CCS334/Unit II- Notes-NOSQL Data Management
Recurrent Neural Networks (RNNs) are a type of neural network designed to handle sequential data by maintaining memory of previous
Continue readingUNIT 3- RECURRENT NEURAL NETWORKS – SUBJECT NOTES
Deep Learning Laboratory provides hands-on experience in designing, training, and evaluating deep learning models using tools like TensorFlow and Keras.
Continue readingAD3511- DEEP LEARNING LABORATORY – LAB MANUAL