Attributes in different scales are common in Machine Learning projects. For example, a medical record dataset can include in the columns weight, height, and blood pressure. These attributes have different units of measure and vary in different intervals, making their comparison difficult.
In this post, we discuss how big and complex projects are demotivating, and how we can overcome the demotivation building smaller and simpler projects.
This page contains a list of links to small machine learning projects, which you can use as examples or to bootstrap a more significant projects.
In this post, we present Linear Regression analysis using a one variable example. Although real Linear Regression models use multiple input variables, the idea here is to keep the examples as simple and straightforward as possible, so you can focus on the intuition behind Linear Regression and don't get confused with too much data preparation ... Read More
Google Colab is the right tool to get started with data science. You don't need to install software, you have proper documentation, and you can share your work easily. Int this article, we list five reasons that make Google Colab the right tool for beginner data scientists.
In this tutorial, we are going to create our first machine learning model using the most famous Python libraries and the Google Colab environment, so we don't have to waste any time installing and configuring new software.
Markov Decision Process is a fundamental concept in the Reinforcement Learning. In this post we selected more than 40 resources about Markov Decision Process, including blog posts, books, and videos.
Learn how to create random maps for the FrozenLake environment.
In this article, we are going to learn how to create and explore the Frozen Lake environment using the Gym library, an open source project created by OpenAI used for reinforcement learning experiments.
In this post, we introduce Reinforcement Learning basic concepts using the Frozen Lake game example.