Hugo is one of the most popular static site generators and has been around for almost 10 years. If you have a basic understanding of web development and know how to use command line tools, you’ll be able to create a basic website within a few hours.
I’ll explain step by step how I created my freelance product management portfolio website www.sischreiber.com with Hugo and host it on GitHub Pages.
How is a product management portfolio different from other portfolios?
Portfolios are primarily used in creative professions to showcase creative work. For example in web design or photography. However, portfolio websites are also suitable in product management or product ownership…
I’ve been in Product Management for over 10 years now and I’ve picked up a thing or two along the way. In this post, I’m explaining my Product Backlog best practices. Creating a sorted list of software requirements sounds straightforward. In practice, however, exactly the opposite is the case.
Have a Pre-backlog Before the Actual Backlog
One of the worst things you can do is to use the Product Backlog as an idea pool (“we may need that in the future”). This inflates the Backlog with unnecessary ballast in the form of a wish list, which in case of doubt creates no added value for the user…
Machine learning is a discipline of AI. It uses statistics to solve user problems. So, if you want to develop a machine learning product you need to understand the underlying algorithms. And surprise: statistics. This article is a non-technical overview of 8 proven algorithms to use in Machine Learning products.
Algorithms
Generally speaking, an algorithm is a procedure in the form of program code. An algorithm is used to solve a problem using a proven procedure [1]. For illustration purposes, all algorithms [2] are explained below with examples from the online real estate market.
(Learning) Decision Trees
Decision trees are a popular method of…
Use KPIs, proxy metrics and OKRs to quantify the value of an AI product
Like any digital product, an AI product’s success should be determined by its profit contribution. Business performance indicators such as operating cash flow (OCF) or the monthly recurring revenue (MRR) are suitable for measuring the product’s contribution to the company’s success.
But in order to quantify the accuracy of the underlying algorithm or the interaction of the AI product with the user, business indicators are not enough. This requires operational KPIs and proxy metrics for data driven decision making:
Operational KPI
Reminder: what is a key performance indicator? I like this short and memorable definition:
In 2017 I shipped my first Artificial Intelligence (AI) product. Today the product is an integral part of Europe’s leading mobility marketplace with 8 million monthly unique users. Here are 13 AI Product Management basics I learned during that time.
Terminology
At the beginning briefly the definition of three important terms to calibrate the terminology:
Artificial Intelligence (AI)
The generic term for simulating human intelligence.
Machine Learning
Algorithms trained with a data set provide forecasts (sub-area of AI).
Deep learning.
Classification tasks are learned independently from examples (sub-area of AI).
The environment is crucial
In the design of an AI product such as intelligent personal assistants, self-driving cars or real time pattern…
