Deploying AI solutions is a priority for many businesses. This article describes the eight steps needed to develop, deploy and maintain an AI project that successfully solves a business problem. Read on to learn about the complete AI project life cycle that will maximize your return on investment.
As Machine Learning (ML) gains traction, and quickly becomes a technology that every company wants to implement, those same companies start becoming aware of the challenges that come along with it. Among the challenges: creating and training a ML model is a lot simpler than actually deploying and using that ML model in a practical way.
There are many machine learning styles to choose from. In this guide, I aim to give you a brief introduction to the most important machine learning types in use today, and when to use each. Specifically, we will go over machine learning by type of training, machine learning by learning volume, and machine learning by style of learning.
What is data analytics? How about predictive analytics? How are these two different from data science? People use different terms to describe the fields of analytics and data science. Due to the exploding popularity of data science and big data analytics, many of these terms are used incorrectly and in a confusion fashion.
In this Quick Guide, we will learn markdown, a very useful and very simple markup language you can use for writing formatted plaintext.
In this quick blog post we will learn how to include comments in our code. Though comments are not executed by the computer, they are a fundamental part of writing good, maintainable code.
In this blog post we will learn a simple mental model for how computer memory works. We will then use this mental model to understand Python variables.
In this quick guide, we will cover the basics of Jupyter Notebooks. After reading this, you will be ready to make the most out of this powerful computing environment, which is the workhorse of data analysts and data scientists around the world.
Previously, we learned about data types in programming and we briefly went over the list of basic data types that we have available in Python. In this blog post, we begin diving into the Python data types to learn what they can do for us.
The terms machine learning, deep learning and artificial intelligence are often used interchangeably. But are they exactly the same thing?
Step by step instructions on how to open a Jupyter Notebook in Mac OS and Windows, with screenshots.
What is a program? What is it made of? In this article we begin exploring computer programs in more details. Particularly, we'll be looking at data types: what they are, and why they are a fundamental concept in programming.
In this article we will explore various ways of writing and running Python code.
Should you install Python locally? How about the Anaconda Distribution? What if you want to share some code?
Here are six strategies to help you learn this hard skill more easily.
Everyone says that learning to program is a slow process and I have to agree. But what exactly makes it so slow? In this blog post, I'll discuss some of these reasons in detail. Understanding them is the first step in creating a strategy for speeding up the process of learning.
In this blog post, I will share some of my tips for how to learn programming faster.
In this article, we continue our brief exploration of the command line and we learn some basic but very useful commands.
In this article, we begin to cover the basics of how to use the command line. While it can look scary at first (no colors, no buttons, and why does it look like it's from the 1980s?), the command line is a very important tool to be familiar with.
In this article, we'll quickly go over ways to get help as you progress on your path to learn programming.
In this article, we're going to talk about what programming is at a fundamental level. If you're a complete beginner, this should hopefully begin to demystify this black magic art that makes computers obey our commands.
In this article, we begin our "Intro to Programming" series, which covers basic to intermediate programming concepts with Python.
If you’ve decided to add programming as a new skill in your toolbox, or even if you’re only toying with this idea, here are the top five reasons why you should consider starting with Python.