Here is some video commentary on the code, the code itself is below the video:
This might seem like an incredibly dull topic, and in some respects it is! However, organizing your work in a sensible folder structure will supercharge your predictive modeling efforts! There are few things in advanced computational modeling work that are simultaneously so simple to do, yet have an supersized effect on the quality of your output. […]
Follow these steps to keep your Anaconda installation up to date: Open Anaconda prompt. Typically you can search for this in windows 10, and then open the console (looks like a DOS prompt) Then you can follow the steps laid out here. The link shows how to update all packages in the current environment, as well as […]
After installing TensorFlow, you can try running the following script that shows the application of neural networks to make predictions for a continuous variable using other numeric & categorical predictors. This script has been downloaded (with minimal modifications) from: TensorFlow site.
Think of TensorFlow as a high-performance, easy-to-use framework to perform machine learning. The specific algorithm used for this machine learning is neural networks. But these are not ordinary neural nets. These are a souped-up version, including fancy stuff such as or neural nets. Created by the Google Brain team, TensorFlow provides a user-friendly python front-end, but […]
After installing TensorFlow, you can try running a quickstart / beginner script (below, downloaded from the TensorFlow site).
TensorFlow is great for creating machine learning solutions. The process of installing it is relatively straightforward: Step 1: Make sure you have Anaconda installed. If not, go to: Installing Anaconda Step 2: Installing TensorFlow. Initiate the Anaconda prompt (search for “Anaconda”, you should see the program as well as “Anaconda Prompt”). After initiating the DOS […]
There is a reason why statistical texts spill copious amounts of ink on data sampling and survey designs. Historically speaking, data was incredibly laborious to collect and to analyze with limited computational resources. This led to the development of mathematical modeling techniques that relied on small amounts of information. These models are simplistic and replete […]
This book and whole professions (e.g. predictive modelers, data scientists, economists, etc.) hinge on the assumption that the future can be predicted to some degree. But can it? The Newtonian revolution reinforced not only physical, but a causal determinism about our reality. The past and the future are inextricably linked. We can predict the motion […]