https://github.com/arvinsingh/ml-and-dl

Machine Learning and Deep Learning projects on various datasets.
https://github.com/arvinsingh/ml-and-dl

cnn deep-learning keras machine-learning object-recognition

Last synced: 2 days ago
JSON representation

Machine Learning and Deep Learning projects on various datasets.

• Host: GitHub
• URL: https://github.com/arvinsingh/ml-and-dl
• Owner: arvinsingh
• License: mit
• Created: 2024-01-26T12:47:22.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-04-24T04:44:33.000Z (7 months ago)
• Last Synced: 2024-04-24T10:34:40.429Z (7 months ago)
• Topics: cnn, deep-learning, keras, machine-learning, object-recognition
• Language: Jupyter Notebook
• Homepage:
• Size: 2.64 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
## **Machine Learning Notebooks**

#### **Datasets analyzed**

- [Fisher Iris](https://archive.ics.uci.edu/dataset/53/iris)

- [Wine Data](https://archive.ics.uci.edu/dataset/109/wine)

- [MNIST Digits](https://www.tensorflow.org/datasets/catalog/mnist)

- [CIFAR 10 and CIFAR-100](https://www.cs.toronto.edu/%7Ekriz/cifar.html)

- Random datasets

#### **Algorithms used**

	- KMeans

	- Naive Bayes Classifer 

	- Gaussian Mixture Model

	- Scree Test

	- Linear Regression

	- Multiclass Support Vector Machine

	- Neural Network

	- Convolutional Neural Network

#### **Frameworks used**

	- Keras with TensorFlow backend

	- NumPy

	- Matplotlib

	- SciPy

	- Scikit Learn

#### **Capstone**

	- Convolutional Neural Network 

		vs 

			Support Vector Machine

	on CIFAR-100 and CIFAR-10 datasets

#### Experiment Report:

[Computer Vision: Implementing and studying performance of two different algorithms for Object Recognition on CIFAR-10 and CIFAR-100 datasets.](http://dx.doi.org/10.13140/RG.2.2.29830.34881)

#### **Outcome**

	- Deep understanding of Machine Learning and Deep Learning algorithms

	- Data Analysis

	- Data Visualization

	- Linear Algebra

	- Probability

	- Sample generation