Collaborating Authors

Teaching Methods

Active Learning: A Practical Approach to Improve Your Data Labeling Experience


Okay, let's talk about the one thing which doesn't get that much attention in the data science realm: labeling your data. It's a painful process, and that may lead to its disregard in tutorials you found on the internet or bootcamps you joined. However, it's one of the most crucial components in the data pipeline, you know, garbage in garbage out. A bad label leads to a bad model and a bad production practice. A data-centric approach to machine learning recently has sparked this idea into a whole new research playground.

Artificial intelligence as a self-learning marketing adviser


Our newsletters regularly provide extensive news and background information on projects and current developments of the international business location Hamburg and its business clusters.

Raising Survey Response Rates by Using Machine Learning to Predict Gold Providers


The model based response propensity approach used a machine learning method called the random forests with regression trees method.

Solving the challenges of robot pizza making – Cosmos Magazine


A new machine learning method to teach robots how to deal with pliable substances such as pizza dough or fabric.

Inside DeepMind's New Efforts to Use Deep Learning to Advance Mathematics - KDnuggets


I recently started a new newsletter focus on AI education and already has over 50,000 subscribers. TheSequence is a no-BS (meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Deep learning is becoming increasingly important across different core scientific disciplines such as biology or physics. Obviously, mathematics is the foundation behind every deep learning method but could these be used to advance math research itself?

Artificial Intelligence


The Predict Vision AI platform will enable regular people to engage and participate in the new Artificial Intelligence-based future. Artificial Intelligence and other emerging technologies will take the global markets by storm. It will introduce, adapt, and retrain ordinary people, allowing you to grow and have an opportunity in a new leading-edge marketplace that will require a new, advanced workforce. A platform that will join A.I., Blockchain and Crypto at the same time, allowing ordinary people to enter both worlds and share wealth. We want to create a global AI ecosystem and community-based platform for knowledge sharing and collaborative learning and make AI accessible to everyone- empowering ordinary people to become extraordinary.

Following Reinforcement Learning Methods in Telecom Networks


Reinforcement learning (RL) has shown promise in creating complex logic in controlled settings. On the other hand, what are the prospects for using RL in a more complicated context like telecom networks? Let's learn the basics first. What is reinforcement learning, and how does it work? In machine learning, the three methodologies are reinforcement learning (RL), supervised learning, and unsupervised learning.

Labeling with Active Learning -


We are in the age of data. In recent years, many companies have already started collecting large amounts of data about their business. On the other hand, many companies are just starting now. If you are working in one of these companies, you might be wondering what can be done with all that data. What about using the data to train a supervised machine learning (ML) algorithm? The ML algorithm could perform the same classification task a human would, just so much faster!

Active Learning in Machine Learning Explained


The focus of this article will be on explaining the concept, intuition and a simple implementation of a active learning pipeline. The pipeline will be built out in Python and we'll be using active learning to improve the performance of a binary classification model.