邏輯迴歸(logistic regression)之實作範例

Finding Donor for CharityML - Machine Learning Nanodegree from Udacity

A neural network (one input, three hidden, one output layer) to classify the MNIST handwritten digits

Basic level implementation of Neural Network

Fundamentals of Artificial Intelligence and Deep Learning Frameworks

Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties.

Simple convolutional neural network (purely numpy) to classify the original MNIST dataset. My first project with a convnet. 🖼

Gradient Descent is a technique used to fine-tune machine learning algorithms with differentiable loss functions. It's an open-ended mathematical expression, tirelessly calculating the first-order derivative of a loss function and making precise parameter adjustments.

Week 1 assignment form Coursera's "Advanced Machine Learning - Introduction to Deep Learning"

Simple DNN code, adapted from Nielsen

Explore Linear Regression with Gradient Descent, Stochastic Gradient Descent, and Ridge Regression. Uncover algorithmic insights in data modeling. 📊🎶🚀

Homemade neural network-class with a train/backpropagation method.

Machine learning algorithms from scratch and package

Code for Stochastic Gradient Descent for Linear Regression with L2 Regularization

This repository contains codes of deep deducing solving blank Sudoku.

Recurrent neural network for building a character-level language model and its application to generating new dinosaur names

Implementation of Gradient descent optimization algorithm from scratch

An API that uses machine learning to categorise messages received during a crisis.