function

What Is Argmax in Machine Learning?

Argmax is a mathematical function that you may encounter in applied machine learning. For example, you may see “argmax” or…

argmax, function, vector

Neural Networks are Function Approximation Algorithms

Supervised learning in machine learning can be described in terms of function approximation. Given a dataset comprised of inputs and…

function, mapping, networks

What are Lambda Functions? A Quick Guide to Lambda Functions in Python

Introduction For loops are the antithesis of efficient programming. They’re still necessary and are the first conditional loops taught to…

function, functions, lambda

Scaling and memoization

The previous post explained that Lobatto’s integration method is more efficient than Gaussian quadrature when the end points of the…

evaluations, function, integrate

Mittag-Leffler transform

I keep running into Mittag-Leffler. A couple days ago I wrote about his polynomials. Today I ran across his regularization…

function, mittag-leffler, transform

Fundamentals of Deep Learning – Activation Functions and When to Use Them?

Overview Activation function is one of the building blocks on Neural Network Learn about the different activation functions in deep…

activation, function, relu

Analogies between Weierstrass functions and trig functions

If you look at the Wikipedia article on Weierstrass functions, you’ll find a line that says “the relation between the…

function, weierstrass, zeta

Area of sinc and jinc function lobes

This post will include Python code to address that question. First, let me back up and explain the context. The…

function, jinc, sinc

How to Use an Empirical Distribution Function in Python

An empirical distribution function provides a way to model and sample cumulative probabilities for a data sample that does not…

distribution, function, probability

Niranjan Pramanik, Ph.D.

Multiple Linear Regression — with math and codeKernel Regression — with example and codeIn this article, how kernel function is used as a weighing function to…

function, regression — with, step

How to Implement Bayesian Optimization from Scratch in Python

Last Updated on October 9, 2019 Global optimization is a challenging problem of finding an input that results in the…

function, objective, surrogate

A Gentle Introduction to Jensen’s Inequality

It is common in statistics and machine learning to create a linear transform or mapping of a variable. An example…

function, mean, payoff

A Gentle Introduction to Generative Adversarial Network Loss Functions

A Large-Scale Study, 2018. The result is better gradient information when updating the weights of the generator and a more…

function, functions, loss

MLflow, TensorFlow, and an Open Source Show

This summer, I interned on the ML Platform team. I worked on MLflow, an open-source machine learning management framework. This…

function, tracking, training

A Detailed Guide to 7 Loss Functions for Machine Learning Algorithms with Python Code

We can consider this as a disadvantage of MAE. Here is the code for the update_weight function with MAE cost:…

function, functions, loss

Demystify AWS Lex BotsAsanka NissankaBlockedUnblockFollowFollowingJul 8Source : https://www. signitysolutions. com/chatbot-development/amazon-lex“Bot” is a popular and booming term these days and for sure an…

function, functions, lambda

Neural Networks: parameters, hyperparameters and optimization strategies

Well, if you think about a generic loss function with only one weight, the graphic representation will be something like…

activation, function, loss

How a simple mix of object-oriented programming can sharpen your deep learning prototype

Let’s demonstrate using a simple case — a DL image classification problem with the fashion MNIST dataset. Case illustration with a DL…

code, function, utility

Setting Up Automatic Alerts About Your AWS Lambda Data Pipeline

A great feature of Lambda is you can trigger it to run in a variety of ways, certainly at least…

function, lambda, want

The Hitchhikers guide to handle Big Data using Spark

The Hitchhikers guide to handle Big Data using SparkNot just an IntroductionRahul AgarwalBlockedUnblockFollowFollowingJul 3Big Data has become synonymous with Data engineering.…

function, spark, using

Notes on computing hash functions

A secure hash function maps a file to a string of bits in a way that is hard to reverse.…

function, hash, value

Apply and Lambda usage in pandas

Apply and Lambda usage in pandasLearn these to master PandasRahul AgarwalBlockedUnblockFollowFollowingJul 1Pandas is a wonderful tool to have at your disposal. I…

apply, change, function

Extending PyTorch with Custom Activation Functions

Extending PyTorch with Custom Activation FunctionsA Tutorial for PyTorch and Deep Learning BeginnersAlexandra DeisBlockedUnblockFollowFollowingJun 27IntroductionToday deep learning is going viral…

activation, custom, function

Make Data Acquisition Easy with AWS & Lambda (Python) in 12 Steps

Enter Lambda (yes I know you could also use Batch for this, but this is a Lambda tutorial). AWS has…

function, lambda, python

What is Robustness in Statistics? A Brief Intro to Robust Estimators

A Brief Intro to Robust EstimatorsEce MutluBlockedUnblockFollowFollowingJun 25Robust statistics are the statistics that are resistant to outliers. In other words,…

estimator, function, location