Image Classification The use of image classification in the medical field is a growing area of study and interest. From identifying tumors in MRIs to creating AI that can detect cancer cells in blood, there are many applications for image classification. Creating these AI’s will help with early detection, more accurate diagnosis…

A list of some shortcuts I think are essential Jupyter Notebook Jupyter notebooks are an open source application that allows you to create notebooks with live code. The notebooks help you stay organized with easy to annotate code and I find them essential for any project. I got my first experience with…

Prepping a Kaggle Data set for Logistic Regression — The Data For this quick walkthrough, I chose a stroke dataset from Kaggle. More than 700,000 people in the US suffer from a stroke each year. There are multiple factors that contribute to someones risk of having a stroke. Understanding a patients potential risk for a stroke may help physicians administer precautionary…

A quick review of some essential Genome Sequence analysis terminology Next Generation Sequence Analysis Next Generation Sequencing or (NGS) is the current method for sequencing genomic data. The process is a massive parallel sequencing of DNA that allows for fast and accurate genome sequencing. An accurate genome is essential for…

Some EDA and Visualizations made with Tableau Overwatch Overwatch is my favorite game. The amount of hours I have personally logged into this game over the years boarders on embarrassing. My obsession with this game, should explain why an Overwatch Kaggle dataset got me a little more excited about data then…

A quick guide pooling layers when building a CNN What are Pooling Layers Pooling layers are an essential component of to a convoluted neural nets architecture. Pooling layers act to subsample the input image. Subsampling the image helps alleviate the computational load of the CNN and can help with overfitting the model. Pooling layers…

Missing values in data are an inevitability and how you choose to deal with them is entirely dependent on your specific data. Lucky for us Pandas offers multiple options for filling in the missing values which can expedite any data cleaning process. …

Revisiting a simple skill with some new tricks Missing Data Dealing with missing values in data is an inevitability in data science. Finding those missing values and determining what to do with them will make or break any project. …

Creating a dashboard for the Kings County Housing Data Set Looking Back on a Previous Project In Phase 2 of Flatirons Data Science Program, we where given the Kings County housing data set and asked to create a Linear Regression model to predict the prices of housing listings from a hold out set of data. …