web scraping

🕸️ Web Scraping with Selenium and Beautiful Soup

This is my first article in a while. There are a couple of reasons for that. First, I have been working VERY hard on a substantial project that I am very excited about and have barely looked up from it to do much else. And secondly, a tree fell on

prophet

🔭 PROPHET: the good & the meh

Prophet, formerly known as fbprophet, is a time series prediction machine learning model that is praised for ease of use, functionality, and performance. I have seen it drastically outperform ARIMA and SARIMAX models, and so I decided to put it to the test with some challenging data.  What I found

APIs

📈 Alpha Vantage API Overview

I spent some time recently working with the Alpha Vantage API for financial data, and while the experience left me slightly underwhelmed, there were still some worthwhile aspects of the API that I feel deserve acknowledgement. The first thing I really appreciate about Alpha Vantage is the people. When I

time series data

🛠️ Custom Jupyter Helper Functions

I live inside Jupyter notebooks for the vast majority of my waking hours. And I love it there. But I have also put in some serious hours toward making my Jupyter home beautiful, happy, and efficient. In this article, I will share with you some of my very favorite custom

time series

💪 XGBoost Time Series Prediction

In the world of time series prediction, often LSTM models, as well as the newer trend toward transformers, are primarily what are thought of as leading edge. But I personally have a great admiration for XGBoost models and the raw power they offer, and there are times when XGBoost can

pytorch

◮ Ethereum Price Prediction with LSTM

The time series aspect of time series data can feel like a bit of a hurdle to jump over, and predicting stock and crypto prices is a whole other time series beast to tame. So in this article, I will walk you through the steps of creating a basic architecture

📈 Yahoo! Finance with Python and Pandas

For data science, Yahoo Finance  is an ideal resource for quick, up-to-the-minute financial data, and it is not just for stocks. There is a wealth of information available through the API, including extensive company data, covering not only traded companies but also currency exchange, cryptocurrency, mutual funds, and treasury yields.

python

↔️ Navigation and Organization: Making Python Do the Work

I love just about anything that is logical, well-organized, and flows.  And I get somewhat (or quite, depending on the level of the offense) frustrated with just about anything that is lazily arranged, illogically planned, or otherwise leaves me feeling like "you had ONE job!"  While I know not everyone

technology

📚 💻 Homeschool, Education, Society, and Technology

This article is a little deviation from my norm, but the sentiments herein apply to the overall drive in all the work that I do. As humans and technology advance, so must our approach to education. We must learn flexibility for productive development and true growth as a species. Flexibility

data analysis

🏅 The Olympics: Deep Data Analysis

This is a comprehensive project on data import, data cleaning, data merging, and statistical analysis, as well as advanced data visualization with Seaborn. The data for this project is incredibly interesting and provocative, covering all of the Olympic medal-winning athletes from the beginning of the Olympics up through recent games.

data analysis

💰 Finance, Stocks, & Index Tracking with Python & Pandas

Think of this as a beginner's DEEP dive into finance, stocks, and index tracking by way of Python and Pandas, meaning that it stays fairly surface level, but it still covers a great deal of material in the process. I will be working with the Dow Jones Index and exhibiting

data analysis

Names and What They Say

An investigation into names, trends, and what they reflectGitHub Gist  |  Interactive Jupyter  | PDF Notebook It has been a while since I becameas enmeshed with a set of data as I did with this one. While a huge part of me repeatedly found places where I could easily call the project

big data

📊 Name Popularity

My most recent project has been centered around the data.gov's API containing all of the names and their counts that represent all babies born and registered at birth in the United States. It is a fascinating body of data. And while most of my work has been on aggregating

SQL

😀 JSON to Pandas to SQL: "The Happy Family"

In the world of big data, it is inefficient to work with individual, large files that contain the entirety of the data we are working with. It can become slow and unmanageable. So it is often more efficient and economical to save the large amounts of data in a long-term,

API

🧹 APIs, JSON, and Data Cleaning

Real world data is NEVER as clean as the nicely prepared files data science nuts like to download for projects from Kaggle and the like. But the plus side to real world data is that there are no limits to the data available, as long as you know how to

pandas

🎬 The Power of Pandas! 🎥

(To view the complete notebooks related to this project, please visit my resources page, and navigate to the 12 Advanced Projects: Data Science with Pandas section.) There is A LOT to Pandas, and because the possibilities are so vast when working with this essential library, sometimes it is hard to

gans

🎥 Celebrity GAN: Generating Faces Out of Stars

Reformed Opera Singer Takes on GANs:A year ago, I was an opera singer, a voice-teacher, and a songwriter; i.e. many facets of who and what I am would have me labeled the creative type.  And I do not think many people realize how much creativity there is in

gans

🌷 My GAN Gave Me Flowers

Not very long ago, I began working with GANs. After about 10 min into my first project, and I was already in love. And for me, it is not about what I can make with it as much as having the visual representation that shows me every epoch along the

neural networks

👩🏻 Regression with Images

Recently, I have been spent a lot of time on the Fast.ai Practical Deep Learning for Coders course, and at the same time I have been delving more deeply into the inner structures and workings of neural networks with Jovian's Deep Learning: Zero to GANs.  Experiencing both of these

resnet

Visual / Code Map of Resnet

I put this image together tonight as I was trying to internalize all the things that go on in a Resnet model. I am the kind of person who has to feel like I know something intimately to feel like I KNOW it at all. So this code and I

neural networks

🐩 Teaching a Model 37 Dog and Cat Breeds

I find it hard not to be intimidated when a neural network model can differentiate between dog and cat breeds that I honestly just cannot. But instead, I just get really excited about the possibilities and potential and am just grateful for all the work that so many amazing humans

machine learning

🛳️ The Titanic: Predicting Survival

I have been working A LOT with Fast.ai lately, and I am loving it. I am learning so many new approaches that I feel like get overlooked by many in the field when discussions arise. But I have to admit: I was a little nervous when it came to

neural networks

🐸 CIFAR10 with Fast.ai

I had a project where I was meant to get the highest accuracy possible on this set with PyTorch, no convolution, no pooling, not even a learning rate scheduler, just linear neural networks. Ask me how frustrating that was! The highest I could get was 52%, after HOURS and HOURS

fast.ai

👗 Fashion MNIST vs. Fast.ai

First of all, I really like working with this dataset, but it is not without its issues. For example, I, being a human of high intelligence and mental capacity, look at some of the shirts vs t-shirts vs pullovers vs coats vs dresses, and there are MANY of them that

neural networks

🔥 Hot or Not? Beauty in the Eye of the Mainstream

I know it sounds a bit callous, but hear me out. After I made my first three little web apps using fast.ai neural network methods, for classifying cats vs dogs, 3 different types of bears, and 3 human emotions/facial expressions, I watched my children spend literally HOURS playing