​ A recommendation engine is only as good as the data used to prepare it. Transforming raw data into a format that is suitable for a model is key to getting better personalized recommendations for end-users. In this post, we walk through how to prepare… Read More »Prepare your data for Amazon Personalize with Amazon SageMaker Data Wrangler Maysara Hamdan AWS Machine Learning Blog

​ Home Table of Contents Getting Used to Docker for Machine Learning Introduction A Quick Recap Dockerfile > Docker Image > Docker Container Dockerfile Docker Image Docker Container Example: Deploying a Flask API Container from Scratch Python Code for Flask API to Sum 2 Numbers… Read More »Getting Used to Docker for Machine Learning Suvaditya Mukherjee PyImageSearch

​ In recent years, language models have demonstrated remarkable proficiency in understanding and generating human-like text. However, despite their impressive language capabilities, these models often need to catch up regarding complex reasoning tasks. Whether it’s solving mathematical problems, generating code, or deducing logical conclusions, traditional… Read More »Enhancing Language Models with Analogical Prompting for Improved Reasoning Madhur Garg Artificial Intelligence Category – MarkTechPost

​ The rapid advancement in the field of generative Artificial Intelligence has brought about significant changes in the landscape of digital content creation. These AI algorithms have advanced and become more widely available, allowing for the creation of fake digital content that is incredibly compelling.… Read More »Can We Truly Trust Artificial Intelligence AI Watermarking? This AI Paper Unmasks the Vulnerabilities in Current Deepfake Method’s Defense Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ Decision trees are a popular machine learning algorithm that can be used for both classification and regression tasks. They operate by recursively dividing the dataset into subsets according to the most important property at each node. A tree structure illustrates the decision-making process, with… Read More »Stanford Researchers Propose MAPTree: A Bayesian Approach to Decision Tree Induction with Enhanced Robustness and Performance Rachit Ranjan Artificial Intelligence Category – MarkTechPost

​ Diffusion models have revolutionized generative modeling across various data types. However, in practical applications like generating aesthetically pleasing images from text descriptions, fine-tuning is often needed. Text-to-image diffusion models employ techniques like classifier-free guidance and curated datasets such as LAION Aesthetics to improve alignment… Read More »Google DeepMind Introduces Direct Reward Fine-Tuning (DRaFT): An Effective Artificial Intelligence Method for Fine-Tuning Diffusion Models to Maximize Differentiable Reward Functions Janhavi Lande Artificial Intelligence Category – MarkTechPost

​ The human brain is an extraordinarily complex organ, often considered one of the most intricate and sophisticated systems in the known universe. The brain is hierarchically organized, with lower-level sensory processing areas sending information to higher-level cognitive and decision-making regions. This hierarchy allows for… Read More »Researchers from ITU Denmark Introduce Neural Developmental Programs: Bridging the Gap Between Biological Growth and Artificial Neural Networks Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​ Large Language Models (LLMs) have gained a lot of attention for their human-imitating properties. These models are capable of answering questions, generating content, summarizing long textual paragraphs, and whatnot. Prompts are essential for improving the performance of LLMs like GPT-3.5 and GPT-4. The way… Read More »Google DeepMind Researchers Introduce Promptbreeder: A Self-Referential and Self-Improving AI System that can Automatically Evolve Effective Domain-Specific Prompts in a Given Domain Tanya Malhotra Artificial Intelligence Category – MarkTechPost