The source code for my entry to the ML challenge organised at Flipkart.com
-
Updated
Apr 5, 2017 - Python
The source code for my entry to the ML challenge organised at Flipkart.com
Implementation of Multivariate Linear Regression algorithm using Stochastic Gradient Descent technique to predict the quality of white wine using Python.
Implementation of Logistic Regression using stochastic gradient descent to predict onset of diabetes.
Multilayer Perceptron based on NumPy
Predict Ads click through rates using Logistic Regression. Implemented Stochastic Gradient Descent, L2 regularization, Hash Kernel
linear regression with stochastic gradient descent
classify mnist datasets using ridge regression, optimize the algorithem with SGD, stochastic dual coordinate ascent, and mini-batching
Tensorflow Simplified: Linear and Sigmoid Layers, Forward and Back Prop, Stochastic Gradient Descent
Contains assignments I did in ML course
Implementation of SVD without using package.
Handwritten digit classification systems
Classifying particles as supersymmetric or non-supersymmetric
Regression models on Boston Houses dataset
Implemenation of DDPG with numpy only (without Tensorflow)
MNIST Handwritten Digits Classification using 3 Layer Neural Net 98.7% Accuracy
Matrix factorization using SGD
ETH Zurich Fall 2017
Predict sales prices and practice feature engineering, RFs, and gradient boosting
Regularized Logistic Regression using mini-batch Stochastic Gradient Descent
A basic neural net built from scratch.
Add a description, image, and links to the stochastic-gradient-descent topic page so that developers can more easily learn about it.
To associate your repository with the stochastic-gradient-descent topic, visit your repo's landing page and select "manage topics."