Data Science is an umbrella-term which is a process of collecting data, cleaning data, analyzing data, building a statistical model and communicating results. Machine learning is a subset of Artificial Intelligence. It is a set of statistical techniques used for a system to learn and make predictions using data. Machine learning can be used within … Continue reading Data Science versus Machine Learning
Technology moves fast. In this video I talk about how to be productive with so many technology options. Continue reading Fast-Paced Technology in Data Science
Data-driven is the use of infrastructure, tools, and software to find patterns in data and inform business decisions. Continue reading What is Data-Driven?
Data visualization is part of the data science analysis step, however, visualization also plays a role in communicating results. In this video, I discuss 3 tips on communicating data through visualization. Continue reading 3 Tips for Data Visualization
The conversation about ethics in data science, machine learning, and AI is increasingly important. The goal of Deon is to push the conversation forward and provide concrete, actionable reminders to the developers that have influence over how data science gets done. http://deon.drivendata.org Continue reading DEON – Data Ethics Checklist for Data Science Projects
Having industry experience (or domain knowledge) gives you a head-start on understanding the data within your industry. Continue reading Start Data Science with Industry Experience
This is a lighthearted analysis done in the spirit of Thanksgiving. I am using a Thanksgiving survey dataset as an opportunity to show how surveys can be used to support marketing strategy. My original post is linked below: Continue reading Thanksgiving Dinner – Marketing Survey Data Analysis
Last night I had a dream where I was talking with a friend who told me he needed an app for his new company. We were discussing the purpose of the app, and I asked him “how will you create the app?” His response, “I’ll manage the process myself.” At this point in the dream, … Continue reading Why is Delivering Software Hard?
This is a log of my pledge to code or study machine learning for a minimum of 1 hour every day for the next 100 days. Based on Siraj Raval’s 100 Days of ML Code Challenge. Day 1: Nov 19, 2018 Progress: Continue reading about assessing model accuracy in An Introduction to Statistical Learning. Thoughts: Good … Continue reading 100DaysOfMLCode Challenge Log
I’ve been watching Siraj Raval’s YouTube channel for over a year, and today I stumbled on his video 100 Days of ML Code Challenge where he challenges viewers to spend 1 hour per day studying or coding machine learning. I’m almost 5 months late to the party, but that’s ok. I’m going to start the challenge for fun … Continue reading Starting 100 Days of Machine Learning Code Challenge