kgkorchamhrd/intel-03
Feb 2025 – Feb 2025
1 Month active
Languages Used
Python
Technical Skills
Data PreprocessingDeep LearningMachine LearningModel TrainingNumPyPerceptron
chipmunk-tail
PROFILE
Chipmunk-tail
Jimin developed a machine learning script suite for the kgkorchamhrd/intel-03 repository, delivering two Python scripts that enable both deep learning and classical machine learning experimentation. The suite includes a TensorFlow-based artificial neural network for training on MNIST and Fashion-MNIST datasets, as well as a NumPy-driven perceptron implementation for modeling logic gates such as AND and OR. Jimin’s work encompassed end-to-end data loading, preprocessing, model definition, training, and prediction, providing a reproducible workflow for rapid prototyping. This contribution deepened the repository’s capabilities, offering a unified approach to model development and supporting a range of machine learning use cases.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
198
Activity Months1
Your Network
17 people
Work History
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 (2025-02) Monthly summary for kgkorchamhrd/intel-03 focusing on delivered features and their business value: - Implemented a Machine Learning Script Suite with two new Python scripts: HW5_ANN_mnist.py for training an Artificial Neural Network on MNIST and Fashion-MNIST using TensorFlow; HW5_perceptron.py implementing a NumPy-based Perceptron to model logic gates (AND, OR). - Included end-to-end capabilities: data loading, preprocessing, model definition, training, and prediction functionalities for both components. - All work committed under kgkorchamhrd/intel-03 with hash e97be983ecadd4fe6c779ce01a153feacb36bc35 (commit message 250226_ANN_exam). Overall, this work strengthens the team’s ML experimentation capabilities and creates a reusable, reproducible script suite that spans both classic ML and modern deep learning approaches.
1 Commits • 1 Features
Feb 1, 2025February 2025 (2025-02) Monthly summary for kgkorchamhrd/intel-03 focusing on delivered features and their business value: - Implemented a Machine Learning Script Suite with two new Python scripts: HW5_ANN_mnist.py for training an Artificial Neural Network on MNIST and Fashion-MNIST using TensorFlow; HW5_perceptron.py implementing a NumPy-based Perceptron to model logic gates (AND, OR). - Included end-to-end capabilities: data loading, preprocessing, model definition, training, and prediction functionalities for both components. - All work committed under kgkorchamhrd/intel-03 with hash e97be983ecadd4fe6c779ce01a153feacb36bc35 (commit message 250226_ANN_exam). Overall, this work strengthens the team’s ML experimentation capabilities and creates a reusable, reproducible script suite that spans both classic ML and modern deep learning approaches.
February 2025
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data PreprocessingDeep LearningMachine LearningModel TrainingNumPyPerceptronTensorFlow
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline