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7 More Methods For Better Machine Learning
Many companies are now utilizing data science and machine learning, but there’s still a lot of room for improvement in terms of ROI. A 2021 VentureBeat analysis suggests that 87% of AI models never make it to a production environment and an MIT Sloan Management Review article found that... Read more
Answering Causal Questions in AI
Two of the main techniques used in order to try to discover causal relationships are Graphical Methods (such as Knowledge Graphs and Bayesian Belief Networks) and Explainable AI. These two methods form in fact the basis of the Association level in the Causality Hierarchy (Figure 1),... Read more
Exploit Your Hyperparameters: Batch Size and Learning Rate as Regularization
Gradient descent is one of the first concepts many learn when studying machine or deep learning. This optimization algorithm underlies most of machine learning, including backpropagation in neural networks. When learning gradient descent, we learn that learning rate and batch size matter. Specifically, increasing the learning rate speeds... Read more
Causal Reasoning in Machine Learning
Thanks to recent advancements in Artificial Intelligence (AI), we are now able to leverage Machine Learning and Deep Learning technologies in both academic and commercial applications. Although, relying just on correlations between the different features, can possibly lead to wrong conclusions since correlation does not necessarily... Read more
How to Bring Our World knowledge to Machine Learning?
Editor’s note: Oliver is a speaker for ODSC Europe 2022 this June 15th-16th. Be sure to check out his talk, “How to teach our world knowledge to a neural network?” there! Have a look at my small trick in the video, can you help but try... Read more
Training Learned Optimizers
Editor’s Note: Luke Metz is a speaker for ODSC East 2022 this April 19th-21st. Be sure to check out his talk, “Learned Optimizers,” there! As machine learning models continue to grow, the cost and time to train such models have grown increasingly unwieldy. These rising costs... Read more
Human-the-Loop-Machine Learning and Data Science
Editor’s note: Keith is a speaker for ODSC East 2022. Be sure to check out his talk, “What Analytics Leaders Should Know About Human-in-the-Loop,” there! Human-in-the-loop machine learning is changing the data science landscape faster than data science education can keep up. If you are working... Read more
Introduction to Few-Shot Learning
Editor’s Note: Isha is a speaker for ODSC East 2022 this April 19th-21st. Be sure to check out her talk on few-shot learning there! Machine learning has been highly successful in data-intensive applications but is often hampered when the data set is small. Few-Shot Learning (FSL)... Read more
21 Can’t-Miss Free Machine Learning Talks
Each ODSC conference is a unique opportunity to reconnect with your community and learn about trending topics and tools from incredibly talented individuals.  We are gathering attendees from around the world and that includes some of the top minds in AI.  Here’s just a sample of... Read more
Master Machine Learning: K Nearest Neighbors From Scratch With Python
K Nearest Neighbors is one of the simplest, if not the simplest, machine learning algorithms. It is a classification algorithm that makes predictions based on a defined number of nearest instances. Today you’ll get your hands dirty by implementing and tweaking the K nearest neighbors algorithm... Read more