Explore >> Select a destination
|
You are here 
|
teddykoker.com | ||
| | | | |
utkuufuk.com
|
|
| | | | | Logistic regression is a simple classification method which is widely used in the field of machine learning. Today were going to talk about how to train our own logistic regression model in Python to | |
| | | | |
fa.bianp.net
|
|
| | | | | A naive implementation of the logistic regression loss can results in numerical indeterminacy even for moderate values. This post takes a closer look into the source of these instabilities and discusses more robust Python implementations. hljs.initHighlightingOnLoad(); MathJax.Hub.Config({ extensions: ["tex2jax.js"], jax: ["input/TeX", "output/HTML-CSS"], tex2jax: { inlineMath ... | |
| | | | |
senthil.learntosolveit.com
|
|
| | | | | This is a coin flip simulator. It compare theoretical binomial distribution with experimental results. listings/python/coinflip.py (Source) import random import math import matplotlib.pyplot as plt | |
| | | | |
coornail.net
|
|
| | | Neural networks are a powerful tool in machine learning that can be trained to perform a wide range of tasks, from image classification to natural language processing. In this blog post, well explore how to teach a neural network to add together two numbers. You can also think about this article as a tutorial for tensorflow. | ||
