Web Development

An introduction to AWS Step Functions which is a diagram based system to manage complex state based functions that tie in multiple AWS microservices.

Using AWS EventBridge to schedule automations, and the automations available to us.

Training and Testing XGBoost Algorithm using Sagemaker built in algorithm. Deploy and test model.

Using Python to manipulate data fields/CSV files/spreadsheets

Merging Datasets and creating a machine learning model with XGBoost Algorithm

Train Artificial Neural Networks for Regression Tasks

Multiple Linear-Regression With SageMaker Algorithm

Multiple Linear-Regression metrics and KPI's. Measuring error and accuracy of regression models.

Multiple Linear-Regression

Training a linear learner model in SageMaker Studio with built in algorithms

Using Sagemaker and Sagemaker studio to launch Jupyter notebook instances, build, train and deploy a machine learning model.

Notes on various sagemaker algorithms. Pre-processing, training, validation acceptable data formats etc.

A reference of common general terminology used in Artificial Intelligence/Machine Learning

How to properly configure requests to the Amazon Advertising API. Sample requests in Postman.

Ideal export settings to inline SVG graphics for websites and React components

How to package and upload dependencies to a Lambda function so that you can use external libraries like Axios

A reference for common Integration Request mapping template variables

The basics of testing React applications using Jest.

Getting up to speed with modern Redux methods.

Creating a React CI/CD Pipeline for a React application that triggers from Github and pushes built files into S3 Bucket