Implementations of deep learning algorithms
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Updated
Jan 8, 2019 - Jupyter Notebook
Implementations of deep learning algorithms
Some coding stuff from various machine learning books
Digit recognition neural network
Notebooks containing various tools useful for data science
In the series of Python notebooks I am going to practice solving questions with common data science and machine learning techniques and I am going to share the notebooks here.
Notebook examples with tensorboard.dev
Notebooks on PCA(Principal Component Analysis)
Exercise notebooks for COFI winter school on QML
Notes and Jupyter notebooks exploring deep learning and Tensorflow framework
python code, notebooks and Images used for AI502 Midterm Project.
A series of documented Jupyter notebooks implementing various neural nets.
jupyter notebook to play with mnist data set and scikit-learn
This is the code for "MNIST using CNN in Keras" By M.Junaid Fiaz
This repository contains simple usage examples for basic machine learning libraries. These notebooks are tested in Colab.
A deep learning implementation to recognize single integers from integers. Implemented with tensorflow. **Requires IPython Notebooks to be run ;)
Stores the basic Deep Learning models that I've worked on and learned from using Kaggle, Google Colab and Jupyter Notebook
This notebook, which is part of the EPFL's Visual Intelligence course assignments, implements a vision transformer for classification as well as a GPT model for image generation.
A jupyter notebook containing code to train a model on the MNIST dataset as well as a Flask web application that allows users draw a number into a canvas and submit it to the model with a response prediction from the model. Final year Software Development Project for Emerging Technologies.
Files and Notebooks for Kaggle MNIST
This repository contains a notebook to take you through step by step guide on recognizing handwritten digits using a Multi-Layer-Perceptron(MLP)
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