Some common module used in deep learning and machine learning

TVLARS - A Fast Convergence Optimizer for Large Batch Training

Convenience classes/functions for common machine learning tasks

Building Deep Neural Network for Google Street View Dataset

This repository focuses on the Neural Networks and deep learning. It is a workbook you can refer it for a reference. I'll Include following content here: Neurons, perceptrons, weight and biases, learning rate, activation form, hyper parameters, RNN, CNN and other popular concepts.

Investigating Gradient Descent behavior in linear regression

Interactive Learning Rate Scheduler for PyTorch

Neural net solver with auto-tuned hyperparameters (Python 3.5)

This repository contains additional features, extended to the traditional Word2Vec library, launched in 2013

Stock price forecasting using time series data with Sequential model developed on LSTM architecture utilizing optimizer with learning rate

Univariate linear regression model to predict food truck profits | Multivariate linear regression model to predict housing prices

Customizible neural net constructor.

useful function for applying discriminative learning rates to a model children

Some tools for large mini-batch deep learning in standalone and distributed (main) scenarios.

Propulsive Rocket Landing Simulation Using Q - Learning

Statistical Digital Signal Processing and Modeling

Analyze the performance of 7 optimizers by varying their learning rates

Реализация алгоритма обратного распространения ошибки для обучения нейронной сети для распознавания рукописных цифр

The main concentration of this project lies on image calssification using traditional CNN(Convolution Neural Networks), and also a couple of "BASE MODELS" such as "RestNet50", "DenseNet121" and "EfficientNetB0" that upgraded the performance of our CNN, followed by the Fully Connected NN, that we are using to train our model on.