SPPU-BE-IT-DL-ASSIGNMENTS and TE_IT_ML_ASSIGNMENTS_SPPU

Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 15/25
Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 14/25
Stars: 10
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 14
Forks: 3
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About SPPU-BE-IT-DL-ASSIGNMENTS

RanjeetKumbhar01/SPPU-BE-IT-DL-ASSIGNMENTS

BE IT (2019 Course) || 414447: Lab Practice IV

This collection of assignments provides practical examples for students learning deep learning. It walks through building neural networks, image classifiers, anomaly detectors, and natural language processing models. Learners will input datasets like MNIST/CIFAR10 images or text, and output trained models capable of classification, detection, or understanding word relationships, along with performance evaluations. It is designed for students in an IT program studying deep learning.

deep-learning-education neural-networks image-classification anomaly-detection natural-language-processing

About TE_IT_ML_ASSIGNMENTS_SPPU

RanjeetKumbhar01/TE_IT_ML_ASSIGNMENTS_SPPU

314448 : Laboratory Practice-I (Machine Learning) SPPU

This project provides practical examples for students learning machine learning concepts. It offers guidance on common tasks like analyzing heart disease data for patient outcomes, predicting monthly temperatures, or identifying admission chances for graduate school. Students in information technology programs will find these assignments helpful for understanding real-world machine learning applications.

academic-assignments data-analysis predictive-modeling student-admissions customer-segmentation

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