Let Ω be an open set in some Euclidean space and v a real-valued function on Ω. Dirichlet principle Dirichlet’s…

Continue Reading# function

## Where does the seven come from?

Here’s a plot of exp(6it)/2 + exp(20it)/3: Notice that the plot has 7-fold symmetry. You might expect 6-fold symmetry from…

Continue Reading## To integrate the impossible integral

In the Broadway musical Man of La Mancha, Don Quixote sings To dream the impossible dream To fight the unbeatable…

Continue Reading## A wrinkle in Clojure

Bob Martin recently posted a nice pair of articles, A Little Clojure and A Little More Clojure. In the first…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## Scaling and memoization

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

Continue Reading## Mittag-Leffler transform

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

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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:…

Continue Reading## Demystify AWS Lex Bots

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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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.…

Continue Reading## 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.…

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