This repository gathers comprehensive material for the SPPU Computer Engineering Deep Learning course (2019 pattern). It includes PYQs with solutions, codes, assignment handouts, write-ups, and explanatory notes to reinforce theory and practice in neural networks, CNNs, RNNs, deep generative models, and reinforcement learning. Ideal for exam prep, project work, and self-study, it provides structured, ready-to-use resources aligned with course outcomes and objectives.
Updated 2026-05-26 00:59:04 +05:30
This repository contains vital resources for the Machine Learning course under the SPPU Computer Engineering syllabus (2019 pattern). It includes codes, handouts, notes, previous year questions (PYQs), and write-ups for assignments. The materials focus on understanding the need for machine learning, data pre-processing methods, classification techniques, multi-class classifiers, clustering algorithms, and fundamental neural network algorithms, equipping students to tackle real-time applications effectively.
Updated 2026-03-22 02:18:51 +05:30
This repository contains essential resources for the Information Retrieval course under the SPPU Computer Engineering syllabus (2019 pattern). It includes codes, handouts, notes, previous year questions (PYQs), and write-ups for assignments. The materials cover fundamental concepts of information retrieval, indexing techniques, performance analysis using classification, clustering, and filtering, as well as evaluation methods. Students will also explore parallel information retrieval and the transition from basic systems to large-scale search services.
Updated 2026-03-22 02:12:46 +05:30
This repository serves as a comprehensive resource for the Data Science and Big Data Analytics course, featuring notes, code samples, handouts, and previous year question papers. It supports course outcomes such as analyzing challenges in data science, applying statistics, implementing big data analytics with Python, and utilizing visualization tools. Additionally, it covers the design of big databases using the Hadoop ecosystem, ensuring a thorough understanding of the technologies and strategies essential for effective data analytics.
Updated 2025-06-11 14:45:54 +05:30