SageMaker Training and Deployment with Custom Images
How and Why to Use Custom SageMaker Images If you have used SageMaker for data science modeling work, you have likely used the AWS-provided images to train your models and possibly deploy them to an endpoint. These provide images for scikit-learn, xgboost and deep-learning among other common frameworks. This article will address an issue we […]
The Problem of Underfitting in Machine Learning
ChatGPT generated image What Underfitting is and How to Test for It and Minimize its Impact Machine learning stands as a pivotal element in contemporary data science, fundamentally altering the landscape of predictive analytics and decision-making across various domains. We have written many articles on machine learning concepts, but this one takes us back to […]
Computer Vision: Image Generator Networks
ChatGPT Generated Understanding of this Article A Look at the Core Concepts and How T2I has Evolved I am a Machine Learning Engineer by trade and a Computer Vision scientist by education, so any use case where computers are trying to learn the wonderful world outside (machine learning), primarily using visual information (computer vision) gives […]
The Melody of Data: Turning Unary Encoding into Bird-like Audio
Exploring the Intersection of Information Theory and Natural Sound Introduction In our increasingly digital world, the way we store and transmit information is becoming ever more crucial. Imagine trying to pack a suitcase with as much efficiency as possible, fitting in everything you need without wasting any space. In information theory, this idea translates into […]
Leveraging Sentiment Analysis for Informed Investment Decisions
A Practical Guide Introduction In today’s fast-paced financial markets, information is power. Every news article, analyst report, and social media post has the potential to influence investor sentiment and, in turn, impact stock prices. For investors and financial analysts, understanding these subtle shifts in market sentiment is critical for making informed decisions. However, with the […]
Predicting Telecom Fraud with Linear Regression:
Leveraging Infutor Phone ID and Machine Learning Features Introduction Telecom fraud is a costly and pervasive issue that affects millions of people worldwide. From identity theft to subscription fraud, the tactics employed by fraudsters are continually evolving, making it increasingly challenging for telecom providers to detect and prevent fraudulent activities. In this complex landscape, traditional […]
Revolutionize Your Development Workflow with VS Code’s June 2024 Features
Learn to the exciting new features in the latest VS Code Release Introduction Visual Studio Code (VS Code), known for its versatility and powerful features, continues to evolve, offering developers innovative solutions to enhance their workflows. The June 2024 release of VS Code brings a plethora of updates designed to streamline development processes, boost productivity, […]
Navigating the Ethical Landscape: Generative AI in Data Engineering
Exploring the integration of generative AI in data engineering and its ethical implications. Introduction The integration of generative AI into data engineering marks a significant evolution in the way data ecosystems are managed and utilized. As these advanced technologies take on more complex tasks traditionally performed by humans, they bring forth not only enhanced efficiency […]
The Problem of Overfitting in Machine Learning
By Lena Qian Introduction Machine learning stands as a pivotal element in contemporary data science, fundamentally altering the landscape of predictive analytics and decision-making across various domains. Despite its widespread adoption, a significant impediment persists in the form of overfitting, wherein machine learning models have high accuracy with training data but fail when presented with […]
Boost AI Fairness and Explainability with Amazon SageMaker Clarify
From hiring decisions to loan approvals and even healthcare recommendations, machine learning (ML) impacts our lives daily. Fairness and explainability are crucial in this context. Fairness means data is balanced, and model predictions are fair across groups. Checking for fairness ensures that negative outcomes are fair across all groups, such as age or gender. Explainability […]
