Short description for quick search
-
Updated
Jan 31, 2019 - Python
Short description for quick search
Regularized Logistic Regression
Фреймворк для построения нейронных сетей, комитетов, создания агентов с параллельными вычислениями.
Logistic Regression technique in machine learning both theory and code in Python. Includes topics from Assumptions, Multi Class Classifications, Regularization (l1 and l2), Weight of Evidence and Information Value
Curso Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization. Segundo curso del programa especializado Deep Learning. Este repositorio contiene todos los ejercicios resueltos. https://www.coursera.org/learn/neural-networks-deep-learning
Repository for Assignment 1 for CS 725
Simple Demo to show how L2 Regularization avoids overfitting in Deep Learning/Neural Networks
An OOP Deep Neural Network using a similar syntax as Keras with many hyper-parameters, optimizers and activation functions available.
A Deep Learning framework for CNNs and LSTMs from scratch, using NumPy.
MITx - MicroMasters Program on Statistics and Data Science - Data Analysis: Statistical Modeling and Computation in Applications - Second Project
Code for Stochastic Gradient Descent for Linear Regression with L2 Regularization
1. Understand how neural networks work 2. Implement a simple neural network 3. Understand the role of different parameters of a neural network, such as learning rate
Satellite imagery provides unique insights into various markets, including agriculture, defense and intelligence, energy, and finance. New commercial imagery providers, such as Planet, are using constellations of small satellites to capture images of the entire Earth every day. This flood of new imagery is outgrowing the ability for organization…
A framework for implementing convolutional neural networks and fully connected neural network.
Modifiable neural network
Logistic regression with l1 and l2 regularization VS Linear SVM
Classification Using Logistic Regression by Making a Neural Network Model. This project also includes comparison of Model performance when different regularization techniques are used
A simple python repository for developing perceptron based text mining involving dataset linguistics preprocessing for text classification and extracting similar text for a given query.
Fully connected neural network with Adam optimizer, L2 regularization, Batch normalization, and Dropout using only numpy
Just exploring Deep Learning
Add a description, image, and links to the l2-regularization topic page so that developers can more easily learn about it.
To associate your repository with the l2-regularization topic, visit your repo's landing page and select "manage topics."