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cnn_mnist_dataset

This notebook shows the convolution neural network implementation for mnist data set in a very basic way.

course-v3

The 3rd edition of course.fast.ai

covid19_data_analytica

The repository contains the data exploration of COVID-19 dataset available from kaggle

d2l-pytorch

This is an attempt to modify Dive into Deep Learning, Berkeley STAT 157 (Spring 2019) textbook's code into PyTorch.

ds_exercises

fashion_mnist_pytorch

This repo shows the CNN implementation based in pytorch for the fashion mnist dataset. The basic structure of the CNN is : fashion_model( (layer1): Sequential( (0): Conv2d(1, 16, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2)) (1): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (2): ReLU() (3): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) ) (layer2): Sequential( (0): Conv2d(16, 32, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2)) (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (2): ReLU() (3): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False) ) (fc1): Linear(in_features=1568, out_features=1000, bias=True) (fc2): Linear(in_features=1000, out_features=10, bias=True) )

fast-neural-style

generativeimagemodellingwithdnns

Here I will share the code from the lectures of the course: Generative Image Modelling with Deep Neural Networks taught in the Summer Term 2017 at the Graduate School for Neural Information Processing, University of Tuebingen.

house-wins

A simple monte carlo simulation for betting

mlcourse.ai

Open Machine Learning course mlcourse.ai, both in English and Russian

multi_step_time_series

Time series predictive model to forecast the airline monthly passenger

physcis-deep-learning

The repository is the Pytorch implementation of physics guided neural network

plotly-dashboards-with-dash

This is the repo for the Udemy Course Python Dashboards with Plotly's Dash

practical-machine-learning-with-python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

pressure-drop-prediction

The repository is the implementation of a research paper concluding the performance analysis of machine learning algorithm on complex non-Newtonian fluids.

pytorchneuralstyletransfer

Implementation of Neural Style Transfer in Pytorch

rnn_practice

The repository contains implementation of RNN along with its variants such as LSTM for NLP with examples of generating names, text in shakespear style and addition of two number in binary code.