In my previous blog on Sigmoid function, I touched on its usefulness and how it’s used to solve Logistic Regression problems either in binary or multiclass classification scenarios. Be sure to check that out https://flyingsalmon.net/?p=3879 first! In this blog, we’ll be using a dataset containing people’s ages and whether or not they bought life insurance […]
Tag: ml
What is Sigmoid function and why?
In this blog, I touch on a core function that’s used in many machine learning scenarios whether explicitly or as a part solving a given problem. This is extremely useful for recoding values for classification (binary or multiclass) where we need to map some categorical values into a finite range of values (e.g. 0 or […]
Creating music and teaching coding
Have you heard of Earsketch? It’s an amazing, fun way to create music while learning, practicing, teaching coding! Yes, music and coding all in one with its online, free platform (for students)…you just need a browser. It supports Python and Javascript coding in their online editor and you can compile and run the code on […]
Machine Learning (Prediction with Dummy Variables)
I already shared ways to leverage Python for Machine Learning and predict values in univariate and multivariate regression models. Be sure to read those before proceeding to this as this builds on those concepts. In this post, we’ll also make prediction using regression model but this time we have categorical values to deal with. Categorical […]
Machine Learning In Python (Multivariate Linear Regression)
In my previous post, I shared how to predict using a single criteria leveraging machine learning in Python. If you haven’t read that, be sure to read that first here to get a better understanding of what we’re trying to do. In this post, I’ll let computer predict something based on multiple criteria. For example, […]
Machine Learning in Python (Univariate Linear Regression)
In this post, I share a method to utilize Machine Learning using Python. I have collected some data from CDC site about birth rate in the USA over several years. What I’d like to show you is how we can predict birth rate for a year that is NOT present in the dataset. For example, […]
Text-to-Speech (TTS) and Pandas (POTUS data)
In this post, I introduce you to my Python 3.x program that reads an external data file containing all president names of the USA to-date (2022), and that allows users to enter a query to and hear the names of presidents as the result. The query can be a number such as a first N […]
Network graphs explained with scenarios (Python) – Part 2
This is Part 2 of the series “Network graphs explained with scenarios“. Please read Part 1 first for proper continuity. A few of the scenarios I cover in this blog series here: Project scheduling example – Shows how to compute critical path on a network of related tasks. Covered in Part 1.Routing example – Shows […]
Network graphs explained with scenarios (Python) – Part 1
Network graphs are quite fascinating to me. They are all around us and used daily in a multitude of real-world applications from supply-chain, routing, mapping, social media, scheduling, to networking. In this two-part blog series, I’ll go over some real-world applications of graphs and how to generate them dynamically using Python. There are many complex […]
Speech Recognition and back (using AI/Python)
In one of my earlier blogs, I shared tips on how to build a Text-To-Speech application in Python, which you can read in the post: Interactive Text-To-Speech App… In this post, I’ll show you the reverse…where we can take our voice, and even an audio-recording, and transcript them into English text. Once I do that, […]