-
You’ve Hit a Wall in Your Data Project, Now What?
This article provides strategies for overcoming obstacles in data analytics development. The author suggests stepping away from the problem to gain a fresh perspective, reframing assumptions about the data or code, isolating individual segments of code for troubleshooting, analyzing one example record to identify issues, and approaching problems systematically. The article emphasizes the importance of…
-
A Simple Guide to Understand the apply() Functions in R
This article provides an overview of the apply family of functions in R, including apply(), lapply(), sapply(), and tapply(). The apply() function applies a specified function to all the elements of a row or column in a dataset. The lapply() function is used to apply a function to each element of a list. sapply() is…
-
Forget RAG, the Future is RAG-Fusion
RAG (Retrieval Augmented Generation) is revolutionizing search and information retrieval by using generative AI and vector search to produce direct answers based on trusted data. While RAG has many advantages, it also has limitations, such as constraints with current search technologies and human search inefficiencies. To address these issues, RAG-Fusion has been developed, which generates…
-
Retro-Engineering a Database Schema: GPT vs. Bard vs. LLama2 (Episode 2)
This article discusses the performance of the Llama-2 AI model in analyzing a dataset and suggesting a database schema. Llama-2 successfully identifies categorical and confidential columns in the dataset and suggests a database schema with separate tables for different categories. It also provides SQL scripts to create the tables and suggests data quality checks for…
-
What are the Data Scientist Qualifications in the USA?
The article highlights the importance of data scientists in leveraging the potential of data in today’s data-driven world. Companies are recognizing the need for expert manpower and human intelligence to effectively utilize accumulated data. Data scientists play a crucial role in empowering machines to analyze and interpret data.
-
Researchers at Stanford Present A Novel Artificial Intelligence Method that can Effectively and Efficiently Decompose Shading into a Tree-Structured Representation
Stanford researchers introduce a novel approach to inferring detailed object shading from a single image. By utilizing shade tree representations, they break down object surface shading into an interpretable and user-friendly format, allowing for efficient and intuitive editing. Their method combines auto-regressive inference with optimization algorithms, outperforming existing techniques. Experimental results demonstrate its effectiveness across…
-
Meet Concept2Box: Bridging the Gap Between High-Level Concepts and Fine-Grained Entities in Knowledge Graphs – A Dual Geometric Approach
The Concept2Box approach bridges the gap between high-level concepts and specific entities in knowledge graphs. It employs dual geometric representations, with concepts represented as box embeddings and entities represented as vectors. This approach allows for the learning of hierarchical structures and complex relationships within knowledge graphs. Experimental evaluations have shown the effectiveness of Concept2Box in…
-
Researchers at the Shibaura Institute of Technology Revolutionize Face Direction Detection with Deep Learning: Navigating Challenges of Hidden Facial Features and Expanding Horizon Angles
Researchers from the Shibaura Institute of Technology have developed a novel AI solution for face orientation estimation. By combining deep learning techniques with gyroscopic sensors, they have overcome the limitations of traditional methods and achieved accurate results with a smaller training dataset. This innovation has potential applications in driver monitoring systems, human-computer interaction, and healthcare…
-
New tools are available to help reduce the energy that AI models devour
A team at the MIT Lincoln Laboratory Supercomputing Center (LLSC) is developing techniques to reduce energy consumption in data centers, specifically in relation to artificial intelligence (AI) models. Their methods include power capping hardware and stopping AI training early, with minimal impact on model performance. The team hopes their work will inspire other data centers…
-
Improve prediction quality in custom classification models with Amazon Comprehend
This article discusses how organizations can use Amazon Comprehend, an AI/ML service, to build and optimize custom classification models. It provides guidelines on data preparation, model creation, and model tuning. The article also explores techniques for handling underrepresented data classes and mentions the cost of using Amazon Comprehend.