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Optuna: An Automatic Hyperparameter Optimization Framework
Note: Please go here to see a high-resolution version of the title image) Preferred Networks has released a beta version of an open-source, automatic hyperparameter optimization framework called Optuna. In this blog, we will introduce the motivation behind the development of Optuna as well as its features. [Related Article:... Read more
IBM Research Launches Explainable AI Toolkit
Explainability or interpretability of AI is a huge deal these days, especially due to the rise in the number of enterprises depending on the decisions made by machine learning and deep learning. Naturally, stakeholders want a level of transparency for how the algorithms came up with their recommendations. The... Read more
What is Augmented Programming?
Ed Note: Gideon is speaking at ODSC Europe 2019, see his talk “Augmented Programming” there. Over the past decade, deep learning research has led to significant advances in perceptual tasks, such as object detection, face recognition, and speech recognition. In each of these use cases, raw real-world inputs have... Read more
The Interplay of Experimentation and ML to Aid in Repayment of Micro-Loans in Sub-Saharan Africa
Editor’s Note: Brianna is speaking at ODSC West 2019 and ODSC Europe 2019, see her talk “The Interplay of Experimentation and ML to Aid in Repayment of Micro-Loans in Sub-Saharan Africa” there Imagine that through a twist of fate, rather than living the life that brought you to reading this... Read more
Building a Convolutional Neural Network: Male vs Female
In this blog, we are going to classify images using Convolutional Neural Network (CNN), and for deployment, you can use Colab, Kaggle, or even use your local machine since the dataset size is not very large. At the end of this, you will be able to build your own... Read more
RAPIDS 0.8: Same Community New Freedoms
RAPIDS released 0.8 a few weeks back. And afterwards, like most Americans, we took off for the 4th of July holiday. Over that break, I reflected on the purpose of RAPIDS. Speed is great, building a strong community is awesome, but the true power of RAPIDS is in the enablement... Read more
Cracking the Box: Interpreting Black Box Machine Learning Models
Intro To kick off this article, I’d like to explain the interpretability of a machine learning (ML) model. According to Merriam-Webster, interpretability describes the process of making something plain or understandable. In the context of ML, interpretability provides us with an understandable explanation of how a model behaves. Basically,... Read more
Smart Image Analysis for Omnichannel Retail Applications
Editor’s note: Abon is a speaker for ODSC West this Fall! Consider attending his talk, “Computer Vision for E-Commerce: Intelligent Analysis and Selection of Product Images at Scale” then. In retail, the role of product images is critical in delivering satisfactory customer experience. Images help online shoppers gain confidence... Read more
Model Interpretation: What and How?
Editor’s note: Brian is a speaker for ODSC West in California this November! Be sure to check out his talk, “Advanced Methods for Explaining XGBoost Models” there! As modern machine learning methods become more ubiquitous, increasing attention is being paid to understanding how these models work — model interpretation instead... Read more
Redefining Robotics: Next Generation Warehouses
People picture robots changing to look more like humans, but in reality, the evolution of robotics involves things you can’t actually see. For Bastiane Huang at Osaro, the development of robots means greater advances in autonomy. Building brains for robots gives them more flexibility for tasks and creates more... Read more